Add files using upload-large-folder tool

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@@ -985,3 +985,6 @@ omnilmm/lib/python3.10/site-packages/nvidia/cuda_cupti/lib/libcupti.so.12 filter
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+omnilmm/lib/python3.10/site-packages/nvidia/cuda_nvrtc/lib/libnvrtc-builtins.so.12.1 filter=lfs diff=lfs merge=lfs -text
+omnilmm/lib/python3.10/site-packages/nvidia/cuda_cupti/lib/libnvperf_host.so filter=lfs diff=lfs merge=lfs -text
+omnilmm/lib/python3.10/site-packages/nvidia/cudnn/lib/libcudnn_ops_train.so.8 filter=lfs diff=lfs merge=lfs -text

omnilmm/lib/python3.10/site-packages/nvidia/cuda_cupti/lib/libnvperf_host.so

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omnilmm/lib/python3.10/site-packages/nvidia/cuda_nvrtc/lib/libnvrtc-builtins.so.12.1

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omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/common_functions.h

@@ -0,0 +1,65 @@
+/*
+ * Copyright 1993-2018 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__)
+#if defined(_MSC_VER)
+#pragma message("common_functions.h is an internal header file and must not be used directly.  This file will be removed in a future CUDA release.  Please use cuda_runtime_api.h or cuda_runtime.h instead.")
+#else
+#warning "common_functions.h is an internal header file and must not be used directly.  This file will be removed in a future CUDA release.  Please use cuda_runtime_api.h or cuda_runtime.h instead."
+#endif
+#define __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
+#define __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_COMMON_FUNCTIONS_H_WRAPPER__
+#endif
+
+#include "crt/common_functions.h"
+
+#if defined(__UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_COMMON_FUNCTIONS_H_WRAPPER__)
+#undef __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
+#undef __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_COMMON_FUNCTIONS_H_WRAPPER__
+#endif

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups.h

@@ -0,0 +1,1690 @@
+/*
+ * Copyright 1993-2021 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#ifndef _COOPERATIVE_GROUPS_H_
+#define _COOPERATIVE_GROUPS_H_
+
+#if defined(__cplusplus) && defined(__CUDACC__)
+
+#include "cooperative_groups/details/info.h"
+#include "cooperative_groups/details/driver_abi.h"
+#include "cooperative_groups/details/helpers.h"
+#include "cooperative_groups/details/memory.h"
+
+#if defined(_CG_HAS_STL_ATOMICS)
+#include <cuda/atomic>
+#define _CG_THREAD_SCOPE(scope) _CG_STATIC_CONST_DECL cuda::thread_scope thread_scope = scope;
+#else
+#define _CG_THREAD_SCOPE(scope)
+#endif
+
+_CG_BEGIN_NAMESPACE
+
+namespace details {
+    _CG_CONST_DECL unsigned int coalesced_group_id = 1;
+    _CG_CONST_DECL unsigned int multi_grid_group_id = 2;
+    _CG_CONST_DECL unsigned int grid_group_id = 3;
+    _CG_CONST_DECL unsigned int thread_block_id = 4;
+    _CG_CONST_DECL unsigned int multi_tile_group_id = 5;
+    _CG_CONST_DECL unsigned int cluster_group_id = 6;
+}
+
+/**
+ * class thread_group;
+ *
+ * Generic thread group type, into which all groups are convertible.
+ * It acts as a container for all storage necessary for the derived groups,
+ * and will dispatch the API calls to the correct derived group. This means
+ * that all derived groups must implement the same interface as thread_group.
+ */
+class thread_group
+{
+protected:
+    struct group_data {
+        unsigned int _unused : 1;
+        unsigned int type : 7, : 0;
+    };
+
+    struct gg_data  {
+        details::grid_workspace *gridWs;
+    };
+
+#if defined(_CG_CPP11_FEATURES) && defined(_CG_ABI_EXPERIMENTAL)
+    struct mg_data  {
+        unsigned long long _unused : 1;
+        unsigned long long type    : 7;
+        unsigned long long handle  : 56;
+        const details::multi_grid::multi_grid_functions *functions;
+    };
+#endif
+
+    struct tg_data {
+        unsigned int is_tiled : 1;
+        unsigned int type : 7;
+        unsigned int size : 24;
+        // packed to 4b
+        unsigned int metaGroupSize : 16;
+        unsigned int metaGroupRank : 16;
+        // packed to 8b
+        unsigned int mask;
+        // packed to 12b
+        unsigned int _res;
+    };
+
+    friend _CG_QUALIFIER thread_group tiled_partition(const thread_group& parent, unsigned int tilesz);
+    friend class thread_block;
+
+    union __align__(8) {
+        group_data  group;
+        tg_data     coalesced;
+        gg_data     grid;
+#if defined(_CG_CPP11_FEATURES) && defined(_CG_ABI_EXPERIMENTAL)
+        mg_data     multi_grid;
+#endif
+    } _data;
+
+    _CG_QUALIFIER thread_group operator=(const thread_group& src);
+
+    _CG_QUALIFIER thread_group(unsigned int type) {
+        _data.group.type = type;
+        _data.group._unused = false;
+    }
+
+#ifdef _CG_CPP11_FEATURES
+    static_assert(sizeof(tg_data) <= 16, "Failed size check");
+    static_assert(sizeof(gg_data) <= 16, "Failed size check");
+#  ifdef _CG_ABI_EXPERIMENTAL
+    static_assert(sizeof(mg_data) <= 16, "Failed size check");
+#  endif
+#endif
+
+public:
+    _CG_THREAD_SCOPE(cuda::thread_scope::thread_scope_device)
+
+    _CG_QUALIFIER unsigned long long size() const;
+    _CG_QUALIFIER unsigned long long num_threads() const;
+    _CG_QUALIFIER unsigned long long thread_rank() const;
+    _CG_QUALIFIER void sync() const;
+    _CG_QUALIFIER unsigned int get_type() const {
+        return _data.group.type;
+    }
+
+};
+
+template <unsigned int TyId>
+struct thread_group_base : public thread_group {
+    _CG_QUALIFIER thread_group_base() : thread_group(TyId) {}
+    _CG_STATIC_CONST_DECL unsigned int id = TyId;
+};
+
+#if defined(_CG_HAS_MULTI_GRID_GROUP)
+
+/**
+ * class multi_grid_group;
+ *
+ * Threads within this this group are guaranteed to be co-resident on the
+ * same system, on multiple devices within the same launched kernels.
+ * To use this group, the kernel must have been launched with
+ * cuLaunchCooperativeKernelMultiDevice (or the CUDA Runtime equivalent),
+ * and the device must support it (queryable device attribute).
+ *
+ * Constructed via this_multi_grid();
+ */
+
+
+# if defined(_CG_CPP11_FEATURES) && defined(_CG_ABI_EXPERIMENTAL)
+class multi_grid_group;
+
+// Multi grid group requires these functions to be templated to prevent ptxas from trying to use CG syscalls
+template <typename = void>
+__device__ _CG_DEPRECATED multi_grid_group this_multi_grid();
+
+class multi_grid_group : public thread_group_base<details::multi_grid_group_id>
+{
+private:
+    template <typename = void>
+    _CG_QUALIFIER multi_grid_group() {
+        _data.multi_grid.functions = details::multi_grid::load_grid_intrinsics();
+        _data.multi_grid.handle = _data.multi_grid.functions->get_intrinsic_handle();
+    }
+
+    friend multi_grid_group this_multi_grid<void>();
+
+public:
+    _CG_THREAD_SCOPE(cuda::thread_scope::thread_scope_system)
+
+    _CG_QUALIFIER bool is_valid() const {
+        return (_data.multi_grid.handle != 0);
+    }
+
+    _CG_QUALIFIER void sync() const {
+        if (!is_valid()) {
+            _CG_ABORT();
+        }
+        _data.multi_grid.functions->sync(_data.multi_grid.handle);
+    }
+
+    _CG_QUALIFIER unsigned long long num_threads() const {
+        _CG_ASSERT(is_valid());
+        return _data.multi_grid.functions->size(_data.multi_grid.handle);
+    }
+
+    _CG_QUALIFIER unsigned long long size() const {
+        return num_threads();
+    }
+
+    _CG_QUALIFIER unsigned long long thread_rank() const {
+        _CG_ASSERT(is_valid());
+        return _data.multi_grid.functions->thread_rank(_data.multi_grid.handle);
+    }
+
+    _CG_QUALIFIER unsigned int grid_rank() const {
+        _CG_ASSERT(is_valid());
+        return (_data.multi_grid.functions->grid_rank(_data.multi_grid.handle));
+    }
+
+    _CG_QUALIFIER unsigned int num_grids() const {
+        _CG_ASSERT(is_valid());
+        return (_data.multi_grid.functions->num_grids(_data.multi_grid.handle));
+    }
+};
+# else
+class multi_grid_group
+{
+private:
+    unsigned long long _handle;
+    unsigned int _size;
+    unsigned int _rank;
+
+    friend _CG_QUALIFIER multi_grid_group this_multi_grid();
+
+    _CG_QUALIFIER multi_grid_group() {
+        _handle = details::multi_grid::get_intrinsic_handle();
+        _size = details::multi_grid::size(_handle);
+        _rank = details::multi_grid::thread_rank(_handle);
+    }
+
+public:
+    _CG_THREAD_SCOPE(cuda::thread_scope::thread_scope_system)
+
+    _CG_QUALIFIER _CG_DEPRECATED bool is_valid() const {
+        return (_handle != 0);
+    }
+
+    _CG_QUALIFIER _CG_DEPRECATED void sync() const {
+        if (!is_valid()) {
+            _CG_ABORT();
+        }
+        details::multi_grid::sync(_handle);
+    }
+
+    _CG_QUALIFIER _CG_DEPRECATED unsigned long long num_threads() const {
+        _CG_ASSERT(is_valid());
+        return _size;
+    }
+
+    _CG_QUALIFIER _CG_DEPRECATED unsigned long long size() const {
+        return num_threads();
+    }
+
+    _CG_QUALIFIER _CG_DEPRECATED unsigned long long thread_rank() const {
+        _CG_ASSERT(is_valid());
+        return _rank;
+    }
+
+    _CG_QUALIFIER _CG_DEPRECATED unsigned int grid_rank() const {
+        _CG_ASSERT(is_valid());
+        return (details::multi_grid::grid_rank(_handle));
+    }
+
+    _CG_QUALIFIER _CG_DEPRECATED unsigned int num_grids() const {
+        _CG_ASSERT(is_valid());
+        return (details::multi_grid::num_grids(_handle));
+    }
+};
+# endif
+
+/**
+ * multi_grid_group this_multi_grid()
+ *
+ * Constructs a multi_grid_group
+ */
+# if defined(_CG_CPP11_FEATURES) && defined(_CG_ABI_EXPERIMENTAL)
+template <typename>
+__device__
+#else
+_CG_QUALIFIER
+# endif
+_CG_DEPRECATED
+multi_grid_group this_multi_grid()
+{
+    return multi_grid_group();
+}
+#endif
+
+/**
+ * class grid_group;
+ *
+ * Threads within this this group are guaranteed to be co-resident on the
+ * same device within the same launched kernel. To use this group, the kernel
+ * must have been launched with cuLaunchCooperativeKernel (or the CUDA Runtime equivalent),
+ * and the device must support it (queryable device attribute).
+ *
+ * Constructed via this_grid();
+ */
+class grid_group : public thread_group_base<details::grid_group_id>
+{
+    _CG_STATIC_CONST_DECL unsigned int _group_id = details::grid_group_id;
+    friend _CG_QUALIFIER grid_group this_grid();
+
+private:
+    _CG_QUALIFIER grid_group(details::grid_workspace *gridWs) {
+        _data.grid.gridWs = gridWs;
+    }
+
+ public:
+    _CG_THREAD_SCOPE(cuda::thread_scope::thread_scope_device)
+
+    _CG_QUALIFIER bool is_valid() const {
+        return (_data.grid.gridWs != NULL);
+    }
+
+    _CG_QUALIFIER void sync() const {
+        if (!is_valid()) {
+            _CG_ABORT();
+        }
+        details::grid::sync(&_data.grid.gridWs->barrier);
+    }
+
+    _CG_STATIC_QUALIFIER unsigned long long size() {
+        return details::grid::size();
+    }
+
+    _CG_STATIC_QUALIFIER unsigned long long thread_rank() {
+        return details::grid::thread_rank();
+    }
+
+    _CG_STATIC_QUALIFIER dim3 group_dim() {
+        return details::grid::grid_dim();
+    }
+
+    _CG_STATIC_QUALIFIER unsigned long long num_threads() {
+        return details::grid::num_threads();
+    }
+
+    _CG_STATIC_QUALIFIER dim3 dim_blocks() {
+        return details::grid::dim_blocks();
+    }
+
+    _CG_STATIC_QUALIFIER unsigned long long num_blocks() {
+        return details::grid::num_blocks();
+    }
+
+    _CG_STATIC_QUALIFIER dim3 block_index() {
+        return details::grid::block_index();
+    }
+
+    _CG_STATIC_QUALIFIER unsigned long long block_rank() {
+        return details::grid::block_rank();
+    }
+
+# if defined(_CG_HAS_CLUSTER_GROUP)
+    _CG_STATIC_QUALIFIER dim3 dim_clusters() {
+        return details::grid::dim_clusters();
+    }
+
+    _CG_STATIC_QUALIFIER unsigned long long num_clusters() {
+        return details::grid::num_clusters();
+    }
+
+    _CG_STATIC_QUALIFIER dim3 cluster_index() {
+        return details::grid::cluster_index();
+    }
+
+    _CG_STATIC_QUALIFIER unsigned long long cluster_rank() {
+        return details::grid::cluster_rank();
+    }
+# endif
+};
+
+_CG_QUALIFIER grid_group this_grid() {
+    // Load a workspace from the driver
+    grid_group gg(details::get_grid_workspace());
+#ifdef _CG_DEBUG
+    // *all* threads must be available to synchronize
+    gg.sync();
+#endif // _CG_DEBUG
+    return gg;
+}
+
+#if defined(_CG_HAS_CLUSTER_GROUP)
+/**
+ * class cluster_group
+ *
+ * Every GPU kernel is executed by a grid of thread blocks. A grid can be evenly
+ * divided along all dimensions to form groups of blocks, each group of which is
+ * a block cluster. Clustered grids are subject to various restrictions and
+ * limitations. Primarily, a cluster consists of at most 8 blocks by default
+ * (although the user is allowed to opt-in to non-standard sizes,) and clustered
+ * grids are subject to additional occupancy limitations due to per-cluster
+ * hardware resource consumption. In exchange, a block cluster is guaranteed to
+ * be a cooperative group, with access to all cooperative group capabilities, as
+ * well as cluster specific capabilities and accelerations. A cluster_group
+ * represents a block cluster.
+ *
+ * Constructed via this_cluster_group();
+ */
+class cluster_group : public thread_group_base<details::cluster_group_id>
+{
+    // Friends
+    friend _CG_QUALIFIER cluster_group this_cluster();
+
+    // Disable constructor
+    _CG_QUALIFIER cluster_group()
+    {
+    }
+
+ public:
+    //_CG_THREAD_SCOPE(cuda::thread_scope::thread_scope_cluster)
+
+    using arrival_token = struct {};
+
+    // Functionality exposed by the group
+    _CG_STATIC_QUALIFIER void sync()
+    {
+        return details::cluster::sync();
+    }
+
+    _CG_STATIC_QUALIFIER arrival_token barrier_arrive()
+    {
+        details::cluster::barrier_arrive();
+        return arrival_token();
+    }
+
+    _CG_STATIC_QUALIFIER void barrier_wait()
+    {
+        return details::cluster::barrier_wait();
+    }
+
+    _CG_STATIC_QUALIFIER void barrier_wait(arrival_token&&)
+    {
+        return details::cluster::barrier_wait();
+    }
+
+    _CG_STATIC_QUALIFIER unsigned int query_shared_rank(const void *addr)
+    {
+        return details::cluster::query_shared_rank(addr);
+    }
+
+    template <typename T>
+    _CG_STATIC_QUALIFIER T* map_shared_rank(T *addr, int rank)
+    {
+        return details::cluster::map_shared_rank(addr, rank);
+    }
+
+    _CG_STATIC_QUALIFIER dim3 block_index()
+    {
+        return details::cluster::block_index();
+    }
+
+    _CG_STATIC_QUALIFIER unsigned int block_rank()
+    {
+        return details::cluster::block_rank();
+    }
+
+    _CG_STATIC_QUALIFIER unsigned int thread_rank()
+    {
+        return details::cluster::thread_rank();
+    }
+
+    _CG_STATIC_QUALIFIER dim3 dim_blocks()
+    {
+        return details::cluster::dim_blocks();
+    }
+
+    _CG_STATIC_QUALIFIER unsigned int num_blocks()
+    {
+        return details::cluster::num_blocks();
+    }
+
+    _CG_STATIC_QUALIFIER dim3 dim_threads()
+    {
+        return details::cluster::dim_threads();
+    }
+
+    _CG_STATIC_QUALIFIER unsigned int num_threads()
+    {
+        return details::cluster::num_threads();
+    }
+
+    // Legacy aliases
+    _CG_STATIC_QUALIFIER unsigned int size()
+    {
+        return num_threads();
+    }
+};
+
+/*
+ * cluster_group this_cluster()
+ *
+ * Constructs a cluster_group
+ */
+_CG_QUALIFIER cluster_group this_cluster()
+{
+    cluster_group cg;
+#ifdef _CG_DEBUG
+    cg.sync();
+#endif
+    return cg;
+}
+#endif
+
+#if defined(_CG_CPP11_FEATURES)
+class thread_block;
+template <unsigned int MaxBlockSize>
+_CG_QUALIFIER thread_block this_thread_block(block_tile_memory<MaxBlockSize>& scratch);
+#endif
+
+/**
+ * class thread_block
+ *
+ * Every GPU kernel is executed by a grid of thread blocks, and threads within
+ * each block are guaranteed to reside on the same streaming multiprocessor.
+ * A thread_block represents a thread block whose dimensions are not known until runtime.
+ *
+ * Constructed via this_thread_block();
+ */
+class thread_block : public thread_group_base<details::thread_block_id>
+{
+    // Friends
+    friend _CG_QUALIFIER thread_block this_thread_block();
+    friend _CG_QUALIFIER thread_group tiled_partition(const thread_group& parent, unsigned int tilesz);
+    friend _CG_QUALIFIER thread_group tiled_partition(const thread_block& parent, unsigned int tilesz);
+
+#if defined(_CG_CPP11_FEATURES)
+    template <unsigned int MaxBlockSize>
+    friend _CG_QUALIFIER thread_block this_thread_block(block_tile_memory<MaxBlockSize>& scratch);
+    template <unsigned int Size>
+    friend class __static_size_multi_warp_tile_base;
+
+    details::multi_warp_scratch* const tile_memory;
+
+    template <unsigned int MaxBlockSize>
+    _CG_QUALIFIER thread_block(block_tile_memory<MaxBlockSize>& scratch) :
+        tile_memory(details::get_scratch_ptr(&scratch)) {
+#ifdef _CG_DEBUG
+        if (num_threads() > MaxBlockSize) {
+            details::abort();
+        }
+#endif
+#if !defined(_CG_HAS_RESERVED_SHARED)
+        tile_memory->init_barriers(thread_rank());
+        sync();
+#endif
+    }
+#endif
+
+    // Disable constructor
+    _CG_QUALIFIER thread_block()
+#if defined(_CG_CPP11_FEATURES)
+    : tile_memory(details::get_scratch_ptr(NULL))
+#endif
+    { }
+
+    // Internal Use
+    _CG_QUALIFIER thread_group _get_tiled_threads(unsigned int tilesz) const {
+        const bool pow2_tilesz = ((tilesz & (tilesz - 1)) == 0);
+
+        // Invalid, immediately fail
+        if (tilesz == 0 || (tilesz > 32) || !pow2_tilesz) {
+            details::abort();
+            return (thread_block());
+        }
+
+        unsigned int mask;
+        unsigned int base_offset = thread_rank() & (~(tilesz - 1));
+        unsigned int masklength = min((unsigned int)size() - base_offset, tilesz);
+
+        mask = (unsigned int)(-1) >> (32 - masklength);
+        mask <<= (details::laneid() & ~(tilesz - 1));
+        thread_group tile = thread_group(details::coalesced_group_id);
+        tile._data.coalesced.mask = mask;
+        tile._data.coalesced.size = __popc(mask);
+        tile._data.coalesced.metaGroupSize = (details::cta::size() + tilesz - 1) / tilesz;
+        tile._data.coalesced.metaGroupRank = details::cta::thread_rank() / tilesz;
+        tile._data.coalesced.is_tiled = true;
+        return (tile);
+    }
+
+ public:
+    _CG_STATIC_CONST_DECL unsigned int _group_id = details::thread_block_id;
+    _CG_THREAD_SCOPE(cuda::thread_scope::thread_scope_block)
+
+    _CG_STATIC_QUALIFIER void sync() {
+        details::cta::sync();
+    }
+
+    _CG_STATIC_QUALIFIER unsigned int size() {
+        return details::cta::size();
+    }
+
+    _CG_STATIC_QUALIFIER unsigned int thread_rank() {
+        return details::cta::thread_rank();
+    }
+
+    // Additional functionality exposed by the group
+    _CG_STATIC_QUALIFIER dim3 group_index() {
+        return details::cta::group_index();
+    }
+
+    _CG_STATIC_QUALIFIER dim3 thread_index() {
+        return details::cta::thread_index();
+    }
+
+    _CG_STATIC_QUALIFIER dim3 group_dim() {
+        return details::cta::block_dim();
+    }
+
+    _CG_STATIC_QUALIFIER dim3 dim_threads() {
+        return details::cta::dim_threads();
+    }
+
+    _CG_STATIC_QUALIFIER unsigned int num_threads() {
+        return details::cta::num_threads();
+    }
+
+};
+
+/**
+ * thread_block this_thread_block()
+ *
+ * Constructs a thread_block group
+ */
+_CG_QUALIFIER thread_block this_thread_block()
+{
+    return (thread_block());
+}
+
+#if defined(_CG_CPP11_FEATURES)
+template <unsigned int MaxBlockSize>
+_CG_QUALIFIER thread_block this_thread_block(block_tile_memory<MaxBlockSize>& scratch) {
+    return (thread_block(scratch));
+}
+#endif
+
+/**
+ * class coalesced_group
+ *
+ * A group representing the current set of converged threads in a warp.
+ * The size of the group is not guaranteed and it may return a group of
+ * only one thread (itself).
+ *
+ * This group exposes warp-synchronous builtins.
+ * Constructed via coalesced_threads();
+ */
+class coalesced_group : public thread_group_base<details::coalesced_group_id>
+{
+private:
+    friend _CG_QUALIFIER coalesced_group coalesced_threads();
+    friend _CG_QUALIFIER thread_group tiled_partition(const thread_group& parent, unsigned int tilesz);
+    friend _CG_QUALIFIER coalesced_group tiled_partition(const coalesced_group& parent, unsigned int tilesz);
+    friend class details::_coalesced_group_data_access;
+
+    _CG_QUALIFIER unsigned int _packLanes(unsigned laneMask) const {
+        unsigned int member_pack = 0;
+        unsigned int member_rank = 0;
+        for (int bit_idx = 0; bit_idx < 32; bit_idx++) {
+            unsigned int lane_bit = _data.coalesced.mask & (1 << bit_idx);
+            if (lane_bit) {
+                if (laneMask & lane_bit)
+                    member_pack |= 1 << member_rank;
+                member_rank++;
+            }
+        }
+        return (member_pack);
+    }
+
+    // Internal Use
+    _CG_QUALIFIER coalesced_group _get_tiled_threads(unsigned int tilesz) const {
+        const bool pow2_tilesz = ((tilesz & (tilesz - 1)) == 0);
+
+        // Invalid, immediately fail
+        if (tilesz == 0 || (tilesz > 32) || !pow2_tilesz) {
+            details::abort();
+            return (coalesced_group(0));
+        }
+        if (size() <= tilesz) {
+            return (*this);
+        }
+
+        if ((_data.coalesced.is_tiled == true) && pow2_tilesz) {
+            unsigned int base_offset = (thread_rank() & (~(tilesz - 1)));
+            unsigned int masklength = min((unsigned int)size() - base_offset, tilesz);
+            unsigned int mask = (unsigned int)(-1) >> (32 - masklength);
+
+            mask <<= (details::laneid() & ~(tilesz - 1));
+            coalesced_group coalesced_tile = coalesced_group(mask);
+            coalesced_tile._data.coalesced.metaGroupSize = size() / tilesz;
+            coalesced_tile._data.coalesced.metaGroupRank = thread_rank() / tilesz;
+            coalesced_tile._data.coalesced.is_tiled = true;
+            return (coalesced_tile);
+        }
+        else if ((_data.coalesced.is_tiled == false) && pow2_tilesz) {
+            unsigned int mask = 0;
+            unsigned int member_rank = 0;
+            int seen_lanes = (thread_rank() / tilesz) * tilesz;
+            for (unsigned int bit_idx = 0; bit_idx < 32; bit_idx++) {
+                unsigned int lane_bit = _data.coalesced.mask & (1 << bit_idx);
+                if (lane_bit) {
+                    if (seen_lanes <= 0 && member_rank < tilesz) {
+                        mask |= lane_bit;
+                        member_rank++;
+                    }
+                    seen_lanes--;
+                }
+            }
+            coalesced_group coalesced_tile = coalesced_group(mask);
+            // Override parent with the size of this group
+            coalesced_tile._data.coalesced.metaGroupSize = (size() + tilesz - 1) / tilesz;
+            coalesced_tile._data.coalesced.metaGroupRank = thread_rank() / tilesz;
+            return coalesced_tile;
+        }
+        else {
+            // None in _CG_VERSION 1000
+            details::abort();
+        }
+
+        return (coalesced_group(0));
+    }
+
+ protected:
+    _CG_QUALIFIER coalesced_group(unsigned int mask) {
+        _data.coalesced.mask = mask;
+        _data.coalesced.size = __popc(mask);
+        _data.coalesced.metaGroupRank = 0;
+        _data.coalesced.metaGroupSize = 1;
+        _data.coalesced.is_tiled = false;
+    }
+
+    _CG_QUALIFIER unsigned int get_mask() const {
+        return (_data.coalesced.mask);
+    }
+
+ public:
+    _CG_STATIC_CONST_DECL unsigned int _group_id = details::coalesced_group_id;
+    _CG_THREAD_SCOPE(cuda::thread_scope::thread_scope_block)
+
+    _CG_QUALIFIER unsigned int num_threads() const {
+        return _data.coalesced.size;
+    }
+
+    _CG_QUALIFIER unsigned int size() const {
+        return num_threads();
+    }
+
+    _CG_QUALIFIER unsigned int thread_rank() const {
+        return (__popc(_data.coalesced.mask & details::lanemask32_lt()));
+    }
+
+    // Rank of this group in the upper level of the hierarchy
+    _CG_QUALIFIER unsigned int meta_group_rank() const {
+        return _data.coalesced.metaGroupRank;
+    }
+
+    // Total num partitions created out of all CTAs when the group was created
+    _CG_QUALIFIER unsigned int meta_group_size() const {
+        return _data.coalesced.metaGroupSize;
+    }
+
+    _CG_QUALIFIER void sync() const {
+        __syncwarp(_data.coalesced.mask);
+    }
+
+#ifdef _CG_CPP11_FEATURES
+    template <typename TyElem, typename TyRet = details::remove_qual<TyElem>>
+    _CG_QUALIFIER TyRet shfl(TyElem&& elem, int srcRank) const {
+        unsigned int lane = (srcRank == 0) ? __ffs(_data.coalesced.mask) - 1 :
+            (size() == 32) ? srcRank : __fns(_data.coalesced.mask, 0, (srcRank + 1));
+
+        return details::tile::shuffle_dispatch<TyElem>::shfl(
+            _CG_STL_NAMESPACE::forward<TyElem>(elem), _data.coalesced.mask, lane, 32);
+    }
+
+    template <typename TyElem, typename TyRet = details::remove_qual<TyElem>>
+    _CG_QUALIFIER TyRet shfl_down(TyElem&& elem, unsigned int delta) const {
+        if (size() == 32) {
+            return details::tile::shuffle_dispatch<TyElem>::shfl_down(
+                _CG_STL_NAMESPACE::forward<TyElem>(elem), 0xFFFFFFFF, delta, 32);
+        }
+
+        unsigned int lane = __fns(_data.coalesced.mask, details::laneid(), delta + 1);
+
+        if (lane >= 32)
+            lane = details::laneid();
+
+        return details::tile::shuffle_dispatch<TyElem>::shfl(
+            _CG_STL_NAMESPACE::forward<TyElem>(elem), _data.coalesced.mask, lane, 32);
+    }
+
+    template <typename TyElem, typename TyRet = details::remove_qual<TyElem>>
+    _CG_QUALIFIER TyRet shfl_up(TyElem&& elem, int delta) const {
+        if (size() == 32) {
+            return details::tile::shuffle_dispatch<TyElem>::shfl_up(
+                _CG_STL_NAMESPACE::forward<TyElem>(elem), 0xFFFFFFFF, delta, 32);
+        }
+
+        unsigned lane = __fns(_data.coalesced.mask, details::laneid(), -(delta + 1));
+        if (lane >= 32)
+            lane = details::laneid();
+
+        return details::tile::shuffle_dispatch<TyElem>::shfl(
+            _CG_STL_NAMESPACE::forward<TyElem>(elem), _data.coalesced.mask, lane, 32);
+    }
+#else
+    template <typename TyIntegral>
+    _CG_QUALIFIER TyIntegral shfl(TyIntegral var, unsigned int src_rank) const {
+        details::assert_if_not_arithmetic<TyIntegral>();
+        unsigned int lane = (src_rank == 0) ? __ffs(_data.coalesced.mask) - 1 :
+            (size() == 32) ? src_rank : __fns(_data.coalesced.mask, 0, (src_rank + 1));
+        return (__shfl_sync(_data.coalesced.mask, var, lane, 32));
+    }
+
+    template <typename TyIntegral>
+    _CG_QUALIFIER TyIntegral shfl_up(TyIntegral var, int delta) const {
+        details::assert_if_not_arithmetic<TyIntegral>();
+        if (size() == 32) {
+            return (__shfl_up_sync(0xFFFFFFFF, var, delta, 32));
+        }
+        unsigned lane = __fns(_data.coalesced.mask, details::laneid(), -(delta + 1));
+        if (lane >= 32) lane = details::laneid();
+        return (__shfl_sync(_data.coalesced.mask, var, lane, 32));
+    }
+
+    template <typename TyIntegral>
+    _CG_QUALIFIER TyIntegral shfl_down(TyIntegral var, int delta) const {
+        details::assert_if_not_arithmetic<TyIntegral>();
+        if (size() == 32) {
+            return (__shfl_down_sync(0xFFFFFFFF, var, delta, 32));
+        }
+        unsigned int lane = __fns(_data.coalesced.mask, details::laneid(), delta + 1);
+        if (lane >= 32) lane = details::laneid();
+        return (__shfl_sync(_data.coalesced.mask, var, lane, 32));
+    }
+#endif
+
+    _CG_QUALIFIER int any(int predicate) const {
+        return (__ballot_sync(_data.coalesced.mask, predicate) != 0);
+    }
+    _CG_QUALIFIER int all(int predicate) const {
+        return (__ballot_sync(_data.coalesced.mask, predicate) == _data.coalesced.mask);
+    }
+    _CG_QUALIFIER unsigned int ballot(int predicate) const {
+        if (size() == 32) {
+            return (__ballot_sync(0xFFFFFFFF, predicate));
+        }
+        unsigned int lane_ballot = __ballot_sync(_data.coalesced.mask, predicate);
+        return (_packLanes(lane_ballot));
+    }
+
+#ifdef _CG_HAS_MATCH_COLLECTIVE
+
+    template <typename TyIntegral>
+    _CG_QUALIFIER unsigned int match_any(TyIntegral val) const {
+        details::assert_if_not_arithmetic<TyIntegral>();
+        if (size() == 32) {
+            return (__match_any_sync(0xFFFFFFFF, val));
+        }
+        unsigned int lane_match = __match_any_sync(_data.coalesced.mask, val);
+        return (_packLanes(lane_match));
+    }
+
+    template <typename TyIntegral>
+    _CG_QUALIFIER unsigned int match_all(TyIntegral val, int &pred) const {
+        details::assert_if_not_arithmetic<TyIntegral>();
+        if (size() == 32) {
+            return (__match_all_sync(0xFFFFFFFF, val, &pred));
+        }
+        unsigned int lane_match = __match_all_sync(_data.coalesced.mask, val, &pred);
+        return (_packLanes(lane_match));
+    }
+
+#endif /* !_CG_HAS_MATCH_COLLECTIVE */
+
+};
+
+_CG_QUALIFIER coalesced_group coalesced_threads()
+{
+    return (coalesced_group(__activemask()));
+}
+
+namespace details {
+    template <unsigned int Size> struct verify_thread_block_tile_size;
+    template <> struct verify_thread_block_tile_size<32> { typedef void OK; };
+    template <> struct verify_thread_block_tile_size<16> { typedef void OK; };
+    template <> struct verify_thread_block_tile_size<8>  { typedef void OK; };
+    template <> struct verify_thread_block_tile_size<4>  { typedef void OK; };
+    template <> struct verify_thread_block_tile_size<2>  { typedef void OK; };
+    template <> struct verify_thread_block_tile_size<1>  { typedef void OK; };
+
+#ifdef _CG_CPP11_FEATURES
+    template <unsigned int Size>
+    using _is_power_of_2 = _CG_STL_NAMESPACE::integral_constant<bool, (Size & (Size - 1)) == 0>;
+
+    template <unsigned int Size>
+    using _is_single_warp = _CG_STL_NAMESPACE::integral_constant<bool, Size <= 32>;
+    template <unsigned int Size>
+    using _is_multi_warp =
+    _CG_STL_NAMESPACE::integral_constant<bool, (Size > 32) && (Size <= 1024)>;
+
+    template <unsigned int Size>
+    using _is_valid_single_warp_tile =
+        _CG_STL_NAMESPACE::integral_constant<bool, _is_power_of_2<Size>::value && _is_single_warp<Size>::value>;
+    template <unsigned int Size>
+    using _is_valid_multi_warp_tile =
+        _CG_STL_NAMESPACE::integral_constant<bool, _is_power_of_2<Size>::value && _is_multi_warp<Size>::value>;
+#else
+    template <unsigned int Size>
+    struct _is_multi_warp {
+        static const bool value = false;
+    };
+#endif
+}
+
+template <unsigned int Size>
+class __static_size_tile_base
+{
+protected:
+    _CG_STATIC_CONST_DECL unsigned int numThreads = Size;
+
+public:
+    _CG_THREAD_SCOPE(cuda::thread_scope::thread_scope_block)
+
+    // Rank of thread within tile
+    _CG_STATIC_QUALIFIER unsigned int thread_rank() {
+        return (details::cta::thread_rank() & (numThreads - 1));
+    }
+
+    // Number of threads within tile
+    _CG_STATIC_CONSTEXPR_QUALIFIER unsigned int num_threads() {
+        return numThreads;
+    }
+
+    _CG_STATIC_CONSTEXPR_QUALIFIER unsigned int size() {
+        return num_threads();
+    }
+};
+
+template <unsigned int Size>
+class __static_size_thread_block_tile_base : public __static_size_tile_base<Size>
+{
+    friend class details::_coalesced_group_data_access;
+    typedef details::tile::tile_helpers<Size> th;
+
+#ifdef _CG_CPP11_FEATURES
+    static_assert(details::_is_valid_single_warp_tile<Size>::value, "Size must be one of 1/2/4/8/16/32");
+#else
+    typedef typename details::verify_thread_block_tile_size<Size>::OK valid;
+#endif
+    using __static_size_tile_base<Size>::numThreads;
+    _CG_STATIC_CONST_DECL unsigned int fullMask = 0xFFFFFFFF;
+
+ protected:
+    _CG_STATIC_QUALIFIER unsigned int build_mask() {
+        unsigned int mask = fullMask;
+        if (numThreads != 32) {
+            // [0,31] representing the current active thread in the warp
+            unsigned int laneId = details::laneid();
+            // shift mask according to the partition it belongs to
+            mask = th::tileMask << (laneId & ~(th::laneMask));
+        }
+        return (mask);
+    }
+
+public:
+    _CG_STATIC_CONST_DECL unsigned int _group_id = details::coalesced_group_id;
+
+    _CG_STATIC_QUALIFIER void sync() {
+        __syncwarp(build_mask());
+    }
+
+#ifdef _CG_CPP11_FEATURES
+    // PTX supported collectives
+    template <typename TyElem, typename TyRet = details::remove_qual<TyElem>>
+    _CG_QUALIFIER TyRet shfl(TyElem&& elem, int srcRank) const {
+        return details::tile::shuffle_dispatch<TyElem>::shfl(
+            _CG_STL_NAMESPACE::forward<TyElem>(elem), build_mask(), srcRank, numThreads);
+    }
+
+    template <typename TyElem, typename TyRet = details::remove_qual<TyElem>>
+    _CG_QUALIFIER TyRet shfl_down(TyElem&& elem, unsigned int delta) const {
+        return details::tile::shuffle_dispatch<TyElem>::shfl_down(
+            _CG_STL_NAMESPACE::forward<TyElem>(elem), build_mask(), delta, numThreads);
+    }
+
+    template <typename TyElem, typename TyRet = details::remove_qual<TyElem>>
+    _CG_QUALIFIER TyRet shfl_up(TyElem&& elem, unsigned int delta) const {
+        return details::tile::shuffle_dispatch<TyElem>::shfl_up(
+            _CG_STL_NAMESPACE::forward<TyElem>(elem), build_mask(), delta, numThreads);
+    }
+
+    template <typename TyElem, typename TyRet = details::remove_qual<TyElem>>
+    _CG_QUALIFIER TyRet shfl_xor(TyElem&& elem, unsigned int laneMask) const {
+        return details::tile::shuffle_dispatch<TyElem>::shfl_xor(
+            _CG_STL_NAMESPACE::forward<TyElem>(elem), build_mask(), laneMask, numThreads);
+    }
+#else
+    template <typename TyIntegral>
+    _CG_QUALIFIER TyIntegral shfl(TyIntegral var, int srcRank) const {
+        details::assert_if_not_arithmetic<TyIntegral>();
+        return (__shfl_sync(build_mask(), var, srcRank, numThreads));
+    }
+
+    template <typename TyIntegral>
+    _CG_QUALIFIER TyIntegral shfl_down(TyIntegral var, unsigned int delta) const {
+        details::assert_if_not_arithmetic<TyIntegral>();
+        return (__shfl_down_sync(build_mask(), var, delta, numThreads));
+    }
+
+    template <typename TyIntegral>
+    _CG_QUALIFIER TyIntegral shfl_up(TyIntegral var, unsigned int delta) const {
+        details::assert_if_not_arithmetic<TyIntegral>();
+        return (__shfl_up_sync(build_mask(), var, delta, numThreads));
+    }
+
+    template <typename TyIntegral>
+    _CG_QUALIFIER TyIntegral shfl_xor(TyIntegral var, unsigned int laneMask) const {
+        details::assert_if_not_arithmetic<TyIntegral>();
+        return (__shfl_xor_sync(build_mask(), var, laneMask, numThreads));
+    }
+#endif //_CG_CPP11_FEATURES
+
+    _CG_QUALIFIER int any(int predicate) const {
+        unsigned int lane_ballot = __ballot_sync(build_mask(), predicate);
+        return (lane_ballot != 0);
+    }
+    _CG_QUALIFIER int all(int predicate) const {
+        unsigned int lane_ballot = __ballot_sync(build_mask(), predicate);
+        return (lane_ballot == build_mask());
+    }
+    _CG_QUALIFIER unsigned int ballot(int predicate) const {
+        unsigned int lane_ballot = __ballot_sync(build_mask(), predicate);
+        return (lane_ballot >> (details::laneid() & (~(th::laneMask))));
+    }
+
+#ifdef _CG_HAS_MATCH_COLLECTIVE
+    template <typename TyIntegral>
+    _CG_QUALIFIER unsigned int match_any(TyIntegral val) const {
+        details::assert_if_not_arithmetic<TyIntegral>();
+        unsigned int lane_match = __match_any_sync(build_mask(), val);
+        return (lane_match >> (details::laneid() & (~(th::laneMask))));
+    }
+
+    template <typename TyIntegral>
+    _CG_QUALIFIER unsigned int match_all(TyIntegral val, int &pred) const {
+        details::assert_if_not_arithmetic<TyIntegral>();
+        unsigned int lane_match = __match_all_sync(build_mask(), val, &pred);
+        return (lane_match >> (details::laneid() & (~(th::laneMask))));
+    }
+#endif
+
+};
+
+template <unsigned int Size, typename ParentT>
+class __static_parent_thread_block_tile_base
+{
+public:
+    // Rank of this group in the upper level of the hierarchy
+    _CG_STATIC_QUALIFIER unsigned int meta_group_rank() {
+        return ParentT::thread_rank() / Size;
+    }
+
+    // Total num partitions created out of all CTAs when the group was created
+    _CG_STATIC_QUALIFIER unsigned int meta_group_size() {
+        return (ParentT::size() + Size - 1) / Size;
+    }
+};
+
+/**
+ * class thread_block_tile<unsigned int Size, ParentT = void>
+ *
+ * Statically-sized group type, representing one tile of a thread block.
+ * The only specializations currently supported are those with native
+ * hardware support (1/2/4/8/16/32)
+ *
+ * This group exposes warp-synchronous builtins.
+ * Can only be constructed via tiled_partition<Size>(ParentT&)
+ */
+
+template <unsigned int Size, typename ParentT = void>
+class __single_warp_thread_block_tile :
+    public __static_size_thread_block_tile_base<Size>,
+    public __static_parent_thread_block_tile_base<Size, ParentT>
+{
+    typedef __static_parent_thread_block_tile_base<Size, ParentT> staticParentBaseT;
+    friend class details::_coalesced_group_data_access;
+
+protected:
+    _CG_QUALIFIER __single_warp_thread_block_tile() { };
+    _CG_QUALIFIER __single_warp_thread_block_tile(unsigned int, unsigned int) { };
+
+    _CG_STATIC_QUALIFIER unsigned int get_mask() {
+        return __static_size_thread_block_tile_base<Size>::build_mask();
+    }
+};
+
+template <unsigned int Size>
+class __single_warp_thread_block_tile<Size, void> :
+    public __static_size_thread_block_tile_base<Size>,
+    public thread_group_base<details::coalesced_group_id>
+{
+    _CG_STATIC_CONST_DECL unsigned int numThreads = Size;
+
+    template <unsigned int, typename ParentT> friend class __single_warp_thread_block_tile;
+    friend class details::_coalesced_group_data_access;
+
+    typedef __static_size_thread_block_tile_base<numThreads> staticSizeBaseT;
+
+protected:
+    _CG_QUALIFIER __single_warp_thread_block_tile(unsigned int meta_group_rank, unsigned int meta_group_size) {
+        _data.coalesced.mask = staticSizeBaseT::build_mask();
+        _data.coalesced.size = numThreads;
+        _data.coalesced.metaGroupRank = meta_group_rank;
+        _data.coalesced.metaGroupSize = meta_group_size;
+        _data.coalesced.is_tiled = true;
+    }
+
+    _CG_QUALIFIER unsigned int get_mask() const {
+        return (_data.coalesced.mask);
+    }
+
+public:
+    using staticSizeBaseT::sync;
+    using staticSizeBaseT::size;
+    using staticSizeBaseT::num_threads;
+    using staticSizeBaseT::thread_rank;
+
+    _CG_QUALIFIER unsigned int meta_group_rank() const {
+        return _data.coalesced.metaGroupRank;
+    }
+
+    _CG_QUALIFIER unsigned int meta_group_size() const {
+        return _data.coalesced.metaGroupSize;
+    }
+};
+
+/**
+ * Outer level API calls
+ * void sync(GroupT) - see <group_type>.sync()
+ * void thread_rank(GroupT) - see <group_type>.thread_rank()
+ * void group_size(GroupT) - see <group_type>.size()
+ */
+template <class GroupT>
+_CG_QUALIFIER void sync(GroupT const &g)
+{
+    g.sync();
+}
+
+// TODO: Use a static dispatch to determine appropriate return type
+// C++03 is stuck with unsigned long long for now
+#ifdef _CG_CPP11_FEATURES
+template <class GroupT>
+_CG_QUALIFIER auto thread_rank(GroupT const& g) -> decltype(g.thread_rank()) {
+    return g.thread_rank();
+}
+
+
+template <class GroupT>
+_CG_QUALIFIER auto group_size(GroupT const &g) -> decltype(g.num_threads()) {
+    return g.num_threads();
+}
+#else
+template <class GroupT>
+_CG_QUALIFIER unsigned long long thread_rank(GroupT const& g) {
+    return static_cast<unsigned long long>(g.thread_rank());
+}
+
+
+template <class GroupT>
+_CG_QUALIFIER unsigned long long group_size(GroupT const &g) {
+    return static_cast<unsigned long long>(g.num_threads());
+}
+#endif
+
+
+/**
+ * tiled_partition
+ *
+ * The tiled_partition(parent, tilesz) method is a collective operation that
+ * partitions the parent group into a one-dimensional, row-major, tiling of subgroups.
+ *
+ * A total of ((size(parent)+tilesz-1)/tilesz) subgroups will
+ * be created where threads having identical k = (thread_rank(parent)/tilesz)
+ * will be members of the same subgroup.
+ *
+ * The implementation may cause the calling thread to wait until all the members
+ * of the parent group have invoked the operation before resuming execution.
+ *
+ * Functionality is limited to power-of-two sized subgorup instances of at most
+ * 32 threads. Only thread_block, thread_block_tile<>, and their subgroups can be
+ * tiled_partition() in _CG_VERSION 1000.
+ */
+_CG_QUALIFIER thread_group tiled_partition(const thread_group& parent, unsigned int tilesz)
+{
+    if (parent.get_type() == details::coalesced_group_id) {
+        const coalesced_group *_cg = static_cast<const coalesced_group*>(&parent);
+        return _cg->_get_tiled_threads(tilesz);
+    }
+    else {
+        const thread_block *_tb = static_cast<const thread_block*>(&parent);
+        return _tb->_get_tiled_threads(tilesz);
+    }
+}
+
+// Thread block type overload: returns a basic thread_group for now (may be specialized later)
+_CG_QUALIFIER thread_group tiled_partition(const thread_block& parent, unsigned int tilesz)
+{
+    return (parent._get_tiled_threads(tilesz));
+}
+
+// Coalesced group type overload: retains its ability to stay coalesced
+_CG_QUALIFIER coalesced_group tiled_partition(const coalesced_group& parent, unsigned int tilesz)
+{
+    return (parent._get_tiled_threads(tilesz));
+}
+
+namespace details {
+    template <unsigned int Size, typename ParentT>
+    class internal_thread_block_tile : public __single_warp_thread_block_tile<Size, ParentT> {};
+
+    template <unsigned int Size, typename ParentT>
+    _CG_QUALIFIER internal_thread_block_tile<Size, ParentT> tiled_partition_internal() {
+        return internal_thread_block_tile<Size, ParentT>();
+    }
+
+    template <typename TyVal, typename GroupT, typename WarpLambda, typename InterWarpLambda>
+    _CG_QUALIFIER TyVal multi_warp_collectives_helper(
+            const GroupT& group,
+            WarpLambda warp_lambda,
+            InterWarpLambda inter_warp_lambda) {
+                return group.template collectives_scheme<TyVal>(warp_lambda, inter_warp_lambda);
+            }
+
+    template <typename T, typename GroupT>
+    _CG_QUALIFIER T* multi_warp_scratch_location_getter(const GroupT& group, unsigned int warp_id) {
+        return group.template get_scratch_location<T>(warp_id);
+    }
+
+    template <typename GroupT>
+    _CG_QUALIFIER details::barrier_t* multi_warp_sync_location_getter(const GroupT& group) {
+        return group.get_sync_location();
+    }
+
+}
+/**
+ * tiled_partition<tilesz>
+ *
+ * The tiled_partition<tilesz>(parent) method is a collective operation that
+ * partitions the parent group into a one-dimensional, row-major, tiling of subgroups.
+ *
+ * A total of ((size(parent)/tilesz) subgroups will be created,
+ * therefore the parent group size must be evenly divisible by the tilesz.
+ * The allow parent groups are thread_block or thread_block_tile<size>.
+ *
+ * The implementation may cause the calling thread to wait until all the members
+ * of the parent group have invoked the operation before resuming execution.
+ *
+ * Functionality is limited to native hardware sizes, 1/2/4/8/16/32.
+ * The size(parent) must be greater than the template Size parameter
+ * otherwise the results are undefined.
+ */
+
+#if defined(_CG_CPP11_FEATURES)
+template <unsigned int Size>
+class __static_size_multi_warp_tile_base : public __static_size_tile_base<Size>
+{
+    static_assert(details::_is_valid_multi_warp_tile<Size>::value, "Size must be one of 64/128/256/512");
+
+    template <typename TyVal, typename GroupT, typename WarpLambda, typename InterWarpLambda>
+    friend __device__ TyVal details::multi_warp_collectives_helper(
+            const GroupT& group,
+            WarpLambda warp_lambda,
+            InterWarpLambda inter_warp_lambda);
+    template <typename T, typename GroupT>
+    friend __device__ T* details::multi_warp_scratch_location_getter(const GroupT& group, unsigned int warp_id);
+    template <typename GroupT>
+    friend __device__ details::barrier_t* details::multi_warp_sync_location_getter(const GroupT& group);
+    template <unsigned int OtherSize>
+    friend class __static_size_multi_warp_tile_base;
+    using WarpType = details::internal_thread_block_tile<32, __static_size_multi_warp_tile_base<Size>>;
+    using ThisType = __static_size_multi_warp_tile_base<Size>;
+    _CG_STATIC_CONST_DECL int numWarps = Size / 32;
+
+protected:
+    details::multi_warp_scratch* const tile_memory;
+
+    template <typename GroupT>
+    _CG_QUALIFIER __static_size_multi_warp_tile_base(const GroupT& g) : tile_memory(g.tile_memory) {
+#if defined(_CG_HAS_RESERVED_SHARED)
+        details::sync_warps_reset(get_sync_location(), details::cta::thread_rank());
+        g.sync();
+#endif
+    }
+
+
+private:
+    _CG_QUALIFIER details::barrier_t* get_sync_location() const {
+        // Different group sizes use different barriers, all groups of a given size share one barrier.
+        unsigned int sync_id = details::log2(Size / 64);
+        return &tile_memory->barriers[sync_id];
+    }
+
+    template <typename T>
+    _CG_QUALIFIER T* get_scratch_location(unsigned int warp_id) const {
+        unsigned int scratch_id = (details::cta::thread_rank() - thread_rank()) / 32 + warp_id;
+        return reinterpret_cast<T*>(&tile_memory->communication_memory[scratch_id]);
+    }
+
+    template <typename T>
+    _CG_QUALIFIER T* get_scratch_location() const {
+        unsigned int scratch_id = details::cta::thread_rank() / 32;
+        return reinterpret_cast<T*>(&tile_memory->communication_memory[scratch_id]);
+    }
+
+    template <typename TyVal>
+    _CG_QUALIFIER TyVal shfl_impl(TyVal val, unsigned int src) const {
+        unsigned int src_warp = src / 32;
+        auto warp = details::tiled_partition_internal<32, ThisType>();
+        details::barrier_t* sync_location = get_sync_location();
+
+        // Get warp slot of the source threads warp.
+        TyVal* warp_scratch_location = get_scratch_location<TyVal>(src_warp);
+
+        if (warp.meta_group_rank() == src_warp) {
+            warp.sync();
+            // Put shuffled value into my warp slot and let my warp arrive at the barrier.
+            if (thread_rank() == src) {
+                *warp_scratch_location = val;
+            }
+            details::sync_warps_arrive(sync_location, details::cta::thread_rank(), numWarps);
+            TyVal result = *warp_scratch_location;
+            details::sync_warps_wait(sync_location, details::cta::thread_rank());
+            return result;
+        }
+        else {
+            // Wait for the source warp to arrive on the barrier.
+            details::sync_warps_wait_for_specific_warp(sync_location,
+                    (details::cta::thread_rank() / 32 - warp.meta_group_rank() + src_warp));
+            TyVal result = *warp_scratch_location;
+            details::sync_warps(sync_location, details::cta::thread_rank(), numWarps);
+            return result;
+        }
+    }
+
+    template <typename TyVal, typename WarpLambda, typename InterWarpLambda>
+    _CG_QUALIFIER TyVal collectives_scheme(const WarpLambda& warp_lambda, const InterWarpLambda& inter_warp_lambda) const {
+        static_assert(sizeof(TyVal) <= details::multi_warp_scratch::communication_size,
+                      "Collectives with tiles larger than 32 threads are limited to types smaller then 8 bytes");
+        auto warp = details::tiled_partition_internal<32, ThisType>();
+        details::barrier_t* sync_location = get_sync_location();
+        TyVal* warp_scratch_location = get_scratch_location<TyVal>();
+
+        warp_lambda(warp, warp_scratch_location);
+
+        if (details::sync_warps_last_releases(sync_location, details::cta::thread_rank(), numWarps)) {
+            auto subwarp = details::tiled_partition_internal<numWarps, decltype(warp)>();
+            if (subwarp.meta_group_rank() == 0) {
+                TyVal* thread_scratch_location = get_scratch_location<TyVal>(subwarp.thread_rank());
+                inter_warp_lambda(subwarp, thread_scratch_location);
+            }
+            warp.sync();
+            details::sync_warps_release(sync_location, warp.thread_rank() == 0, details::cta::thread_rank(), numWarps);
+        }
+        TyVal result = *warp_scratch_location;
+        return result;
+    }
+
+public:
+    _CG_STATIC_CONST_DECL unsigned int _group_id = details::multi_tile_group_id;
+
+    using __static_size_tile_base<Size>::thread_rank;
+
+    template <typename TyVal>
+    _CG_QUALIFIER TyVal shfl(TyVal val, unsigned int src) const {
+        static_assert(sizeof(TyVal) <= details::multi_warp_scratch::communication_size,
+                      "Collectives with tiles larger than 32 threads are limited to types smaller then 8 bytes");
+        return shfl_impl(val, src);
+    }
+
+    _CG_QUALIFIER void sync() const {
+        details::sync_warps(get_sync_location(), details::cta::thread_rank(), numWarps);
+    }
+
+    _CG_QUALIFIER int any(int predicate) const {
+        auto warp_lambda = [=] (WarpType& warp, int* warp_scratch_location) {
+                *warp_scratch_location = __any_sync(0xFFFFFFFF, predicate);
+        };
+        auto inter_warp_lambda =
+            [] (details::internal_thread_block_tile<numWarps, WarpType>& subwarp, int* thread_scratch_location) {
+                *thread_scratch_location = __any_sync(0xFFFFFFFFU >> (32 - numWarps), *thread_scratch_location);
+        };
+        return collectives_scheme<int>(warp_lambda, inter_warp_lambda);
+    }
+
+    _CG_QUALIFIER int all(int predicate) const {
+        auto warp_lambda = [=] (WarpType& warp, int* warp_scratch_location) {
+                *warp_scratch_location = __all_sync(0xFFFFFFFF, predicate);
+        };
+        auto inter_warp_lambda =
+            [] (details::internal_thread_block_tile<numWarps, WarpType>& subwarp, int* thread_scratch_location) {
+                *thread_scratch_location = __all_sync(0xFFFFFFFFU >> (32 - numWarps), *thread_scratch_location);
+        };
+        return collectives_scheme<int>(warp_lambda, inter_warp_lambda);
+    }
+};
+
+
+template <unsigned int Size, typename ParentT = void>
+class __multi_warp_thread_block_tile :
+    public __static_size_multi_warp_tile_base<Size>,
+    public __static_parent_thread_block_tile_base<Size, ParentT>
+{
+    typedef __static_parent_thread_block_tile_base<Size, ParentT> staticParentBaseT;
+    typedef __static_size_multi_warp_tile_base<Size> staticTileBaseT;
+protected:
+    _CG_QUALIFIER __multi_warp_thread_block_tile(const ParentT& g) :
+        __static_size_multi_warp_tile_base<Size>(g) {}
+};
+
+template <unsigned int Size>
+class __multi_warp_thread_block_tile<Size, void> : public __static_size_multi_warp_tile_base<Size>
+{
+    const unsigned int metaGroupRank;
+    const unsigned int metaGroupSize;
+
+protected:
+    template <unsigned int OtherSize, typename ParentT>
+    _CG_QUALIFIER __multi_warp_thread_block_tile(const __multi_warp_thread_block_tile<OtherSize, ParentT>& g) :
+        __static_size_multi_warp_tile_base<Size>(g), metaGroupRank(g.meta_group_rank()), metaGroupSize(g.meta_group_size()) {}
+
+public:
+    _CG_QUALIFIER unsigned int meta_group_rank() const {
+        return metaGroupRank;
+    }
+
+    _CG_QUALIFIER unsigned int meta_group_size() const {
+        return metaGroupSize;
+    }
+};
+#endif
+
+template <unsigned int Size, typename ParentT = void>
+class thread_block_tile;
+
+namespace details {
+    template <unsigned int Size, typename ParentT, bool IsMultiWarp>
+    class thread_block_tile_impl;
+
+    template <unsigned int Size, typename ParentT>
+    class thread_block_tile_impl<Size, ParentT, false>: public __single_warp_thread_block_tile<Size, ParentT>
+    {
+    protected:
+        template <unsigned int OtherSize, typename OtherParentT, bool OtherIsMultiWarp>
+        _CG_QUALIFIER thread_block_tile_impl(const thread_block_tile_impl<OtherSize, OtherParentT, OtherIsMultiWarp>& g) :
+            __single_warp_thread_block_tile<Size, ParentT>(g.meta_group_rank(), g.meta_group_size()) {}
+
+        _CG_QUALIFIER thread_block_tile_impl(const thread_block& g) :
+            __single_warp_thread_block_tile<Size, ParentT>() {}
+    };
+
+#if defined(_CG_CPP11_FEATURES)
+    template <unsigned int Size, typename ParentT>
+    class thread_block_tile_impl<Size, ParentT, true> : public __multi_warp_thread_block_tile<Size, ParentT>
+    {
+        protected:
+        template <typename GroupT>
+        _CG_QUALIFIER thread_block_tile_impl(const GroupT& g) :
+            __multi_warp_thread_block_tile<Size, ParentT>(g) {}
+    };
+#else
+    template <unsigned int Size, typename ParentT>
+    class thread_block_tile_impl<Size, ParentT, true>
+    {
+        protected:
+        template <typename GroupT>
+        _CG_QUALIFIER thread_block_tile_impl(const GroupT& g) {}
+    };
+#endif
+}
+
+template <unsigned int Size, typename ParentT>
+class thread_block_tile : public details::thread_block_tile_impl<Size, ParentT, details::_is_multi_warp<Size>::value>
+{
+    friend _CG_QUALIFIER thread_block_tile<1, void> this_thread();
+
+protected:
+    _CG_QUALIFIER thread_block_tile(const ParentT& g) :
+        details::thread_block_tile_impl<Size, ParentT, details::_is_multi_warp<Size>::value>(g) {}
+
+public:
+    _CG_QUALIFIER operator thread_block_tile<Size, void>() const {
+        return thread_block_tile<Size, void>(*this);
+    }
+};
+
+template <unsigned int Size>
+class thread_block_tile<Size, void> : public details::thread_block_tile_impl<Size, void, details::_is_multi_warp<Size>::value>
+{
+    template <unsigned int, typename ParentT>
+    friend class thread_block_tile;
+
+protected:
+    template <unsigned int OtherSize, typename OtherParentT>
+    _CG_QUALIFIER thread_block_tile(const thread_block_tile<OtherSize, OtherParentT>& g) :
+        details::thread_block_tile_impl<Size, void, details::_is_multi_warp<Size>::value>(g) {}
+
+public:
+    template <typename ParentT>
+    _CG_QUALIFIER thread_block_tile(const thread_block_tile<Size, ParentT>& g) :
+        details::thread_block_tile_impl<Size, void, details::_is_multi_warp<Size>::value>(g) {}
+};
+
+namespace details {
+    template <unsigned int Size, typename ParentT>
+    struct tiled_partition_impl;
+
+    template <unsigned int Size>
+    struct tiled_partition_impl<Size, thread_block> : public thread_block_tile<Size, thread_block> {
+        _CG_QUALIFIER tiled_partition_impl(const thread_block& g) :
+            thread_block_tile<Size, thread_block>(g) {}
+    };
+
+    // ParentT = static thread_block_tile<ParentSize, GrandParent> specialization
+    template <unsigned int Size, unsigned int ParentSize, typename GrandParent>
+    struct tiled_partition_impl<Size, thread_block_tile<ParentSize, GrandParent> > :
+        public thread_block_tile<Size, thread_block_tile<ParentSize, GrandParent> > {
+#ifdef _CG_CPP11_FEATURES
+        static_assert(Size < ParentSize, "Tile size bigger or equal to the parent group size");
+#endif
+        _CG_QUALIFIER tiled_partition_impl(const thread_block_tile<ParentSize, GrandParent>& g) :
+            thread_block_tile<Size, thread_block_tile<ParentSize, GrandParent> >(g) {}
+    };
+
+}
+
+template <unsigned int Size, typename ParentT>
+_CG_QUALIFIER thread_block_tile<Size, ParentT> tiled_partition(const ParentT& g)
+{
+    return details::tiled_partition_impl<Size, ParentT>(g);
+}
+
+/**
+ * thread_group this_thread()
+ *
+ * Constructs a generic thread_group containing only the calling thread
+ */
+_CG_QUALIFIER thread_block_tile<1, void> this_thread()
+{
+    // Make thread_block_tile<1, thread_block> parent of the returned group, so it will have its
+    // meta group rank and size set to 0 and 1 respectively.
+    return thread_block_tile<1, thread_block_tile<1, thread_block> >(this_thread_block());
+}
+
+/**
+ * <group_type>.sync()
+ *
+ * Executes a barrier across the group
+ *
+ * Implements both a compiler fence and an architectural fence to prevent,
+ * memory reordering around the barrier.
+ */
+_CG_QUALIFIER void thread_group::sync() const
+{
+    switch (_data.group.type) {
+    case details::coalesced_group_id:
+        cooperative_groups::sync(*static_cast<const coalesced_group*>(this));
+        break;
+    case details::thread_block_id:
+        cooperative_groups::sync(*static_cast<const thread_block*>(this));
+        break;
+    case details::grid_group_id:
+        cooperative_groups::sync(*static_cast<const grid_group*>(this));
+        break;
+#if defined(_CG_HAS_MULTI_GRID_GROUP) && defined(_CG_CPP11_FEATURES) && defined(_CG_ABI_EXPERIMENTAL)
+    case details::multi_grid_group_id:
+        cooperative_groups::sync(*static_cast<const multi_grid_group*>(this));
+        break;
+#endif
+#if defined(_CG_HAS_CLUSTER_GROUP)
+    case details::cluster_group_id:
+        cooperative_groups::sync(*static_cast<const cluster_group*>(this));
+        break;
+#endif
+    default:
+        break;
+    }
+}
+
+/**
+ * <group_type>.size()
+ *
+ * Returns the total number of threads in the group.
+ */
+_CG_QUALIFIER unsigned long long thread_group::size() const
+{
+    unsigned long long size = 0;
+    switch (_data.group.type) {
+    case details::coalesced_group_id:
+        size = cooperative_groups::group_size(*static_cast<const coalesced_group*>(this));
+        break;
+    case details::thread_block_id:
+        size = cooperative_groups::group_size(*static_cast<const thread_block*>(this));
+        break;
+    case details::grid_group_id:
+        size = cooperative_groups::group_size(*static_cast<const grid_group*>(this));
+        break;
+#if defined(_CG_HAS_MULTI_GRID_GROUP) && defined(_CG_CPP11_FEATURES) && defined(_CG_ABI_EXPERIMENTAL)
+    case details::multi_grid_group_id:
+        size = cooperative_groups::group_size(*static_cast<const multi_grid_group*>(this));
+        break;
+#endif
+#if defined(_CG_HAS_CLUSTER_GROUP)
+    case details::cluster_group_id:
+        size = cooperative_groups::group_size(*static_cast<const cluster_group*>(this));
+        break;
+#endif
+    default:
+        break;
+    }
+    return size;
+}
+
+/**
+ * <group_type>.thread_rank()
+ *
+ * Returns the linearized rank of the calling thread along the interval [0, size()).
+ */
+_CG_QUALIFIER unsigned long long thread_group::thread_rank() const
+{
+    unsigned long long rank = 0;
+    switch (_data.group.type) {
+    case details::coalesced_group_id:
+        rank = cooperative_groups::thread_rank(*static_cast<const coalesced_group*>(this));
+        break;
+    case details::thread_block_id:
+        rank = cooperative_groups::thread_rank(*static_cast<const thread_block*>(this));
+        break;
+    case details::grid_group_id:
+        rank = cooperative_groups::thread_rank(*static_cast<const grid_group*>(this));
+        break;
+#if defined(_CG_HAS_MULTI_GRID_GROUP) && defined(_CG_CPP11_FEATURES) && defined(_CG_ABI_EXPERIMENTAL)
+    case details::multi_grid_group_id:
+        rank = cooperative_groups::thread_rank(*static_cast<const multi_grid_group*>(this));
+        break;
+#endif
+#if defined(_CG_HAS_CLUSTER_GROUP)
+    case details::cluster_group_id:
+        rank = cooperative_groups::thread_rank(*static_cast<const cluster_group*>(this));
+        break;
+#endif
+    default:
+        break;
+    }
+    return rank;
+}
+
+_CG_END_NAMESPACE
+
+#include <cooperative_groups/details/partitioning.h>
+#if (!defined(_MSC_VER) || defined(_WIN64))
+# include <cooperative_groups/details/invoke.h>
+#endif
+
+# endif /* ! (__cplusplus, __CUDACC__) */
+
+#endif /* !_COOPERATIVE_GROUPS_H_ */

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/coalesced_scan.h

@@ -0,0 +1,174 @@
+/* Copyright 1993-2016 NVIDIA Corporation.  All rights reserved.
+  *
+  * NOTICE TO LICENSEE:
+  *
+  * The source code and/or documentation ("Licensed Deliverables") are
+  * subject to NVIDIA intellectual property rights under U.S. and
+  * international Copyright laws.
+  *
+  * The Licensed Deliverables contained herein are PROPRIETARY and
+  * CONFIDENTIAL to NVIDIA and are being provided under the terms and
+  * conditions of a form of NVIDIA software license agreement by and
+  * between NVIDIA and Licensee ("License Agreement") or electronically
+  * accepted by Licensee.  Notwithstanding any terms or conditions to
+  * the contrary in the License Agreement, reproduction or disclosure
+  * of the Licensed Deliverables to any third party without the express
+  * written consent of NVIDIA is prohibited.
+  *
+  * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+  * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+  * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  THEY ARE
+  * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+  * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+  * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+  * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+  * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+  * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+  * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+  * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+  * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+  * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+  * OF THESE LICENSED DELIVERABLES.
+  *
+  * U.S. Government End Users.  These Licensed Deliverables are a
+  * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+  * 1995), consisting of "commercial computer software" and "commercial
+  * computer software documentation" as such terms are used in 48
+  * C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
+  * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+  * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+  * U.S. Government End Users acquire the Licensed Deliverables with
+  * only those rights set forth herein.
+  *
+  * Any use of the Licensed Deliverables in individual and commercial
+  * software must include, in the user documentation and internal
+  * comments to the code, the above Disclaimer and U.S. Government End
+  * Users Notice.
+  */
+
+#ifndef _CG_COALESCED_SCAN_H_
+#define _CG_COALESCED_SCAN_H_
+
+#include "info.h"
+#include "helpers.h"
+#include "cooperative_groups.h"
+#include "partitioning.h"
+#include "functional.h"
+
+_CG_BEGIN_NAMESPACE
+
+namespace details {
+
+template <typename TyGroup, typename TyVal, typename TyOp>
+_CG_QUALIFIER auto inclusive_scan_contiguous(const TyGroup& group, TyVal&& val, TyOp&& op) -> decltype(op(val, val)) {
+    auto out = val;
+    for (int mask = 1; mask < group.size(); mask <<= 1) {
+        auto tmp = group.shfl_up(out, mask);
+        if (mask <= group.thread_rank()) {
+            out = op(out, tmp);
+        }
+    }
+
+    return out;
+}
+
+template <typename TyGroup, typename TyVal, typename TyOp>
+_CG_QUALIFIER auto inclusive_scan_non_contiguous(const TyGroup& group, TyVal&& val, TyOp&& op) -> decltype(op(val, val)) {
+    const unsigned int groupSize = group.size();
+    auto out = val;
+
+    const unsigned int mask = details::_coalesced_group_data_access::get_mask(group);
+    unsigned int lanemask = details::lanemask32_lt() & mask;
+    unsigned int srcLane = details::laneid();
+
+    const unsigned int base = __ffs(mask)-1; /* lane with rank == 0 */
+    const unsigned int rank = __popc(lanemask);
+
+    for (unsigned int i = 1, j = 1; i < groupSize; i <<= 1) {
+        if (i <= rank) {
+            srcLane -= j;
+            j = i; /* maximum possible lane */
+
+            unsigned int begLane = base + rank - i; /* minimum possible lane */
+
+            /*  Next source lane is in the range [ begLane .. srcLane ]
+                *  If begLane < srcLane then do a binary search.
+                */
+            while (begLane < srcLane) {
+                const unsigned int halfLane = (begLane + srcLane) >> 1;
+                const unsigned int halfMask = lanemask >> halfLane;
+                const unsigned int d = __popc(halfMask);
+                if (d < i) {
+                    srcLane = halfLane - 1; /* halfLane too large */
+                }
+                else if ((i < d) || !(halfMask & 0x01)) {
+                    begLane = halfLane + 1; /* halfLane too small */
+                }
+                else {
+                    begLane = srcLane = halfLane; /* happen to hit */
+                }
+            }
+        }
+
+        auto tmp = details::tile::shuffle_dispatch<TyVal>::shfl(out, mask, srcLane, 32);
+        if (i <= rank) {
+            out = op(out, tmp);
+        }
+    }
+    return out;
+}
+
+template <unsigned int TySize, typename ParentT, typename TyVal, typename TyOp>
+_CG_QUALIFIER auto coalesced_inclusive_scan(const __single_warp_thread_block_tile<TySize, ParentT>& group,
+                                            TyVal&& val,
+                                            TyOp&& op) -> decltype(op(val, val)) {
+    return inclusive_scan_contiguous(group, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyOp>(op));
+}
+
+template <typename TyVal, typename TyOp>
+_CG_QUALIFIER auto coalesced_inclusive_scan(const coalesced_group& group, TyVal&& val, TyOp&& op) -> decltype(op(val, val)) {
+    if (group.size() == 32) {
+        return inclusive_scan_contiguous(group, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyOp>(op));
+    }
+    else {
+        return inclusive_scan_non_contiguous(group, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyOp>(op));
+    }
+}
+
+template <bool IntegralOptimized>
+struct scan_choose_convertion;
+
+template<>
+struct scan_choose_convertion<true> {
+    template <typename TyGroup, typename TyRes, typename TyVal>
+    _CG_STATIC_QUALIFIER details::remove_qual<TyVal> convert_inclusive_to_exclusive(const TyGroup& group, TyRes& result, TyVal&& val) {
+        return result - val;
+    }
+};
+
+template<>
+struct scan_choose_convertion<false> {
+    template <typename TyGroup, typename TyRes, typename TyVal>
+    _CG_STATIC_QUALIFIER details::remove_qual<TyVal> convert_inclusive_to_exclusive(const TyGroup& group, TyRes& result, TyVal&& val) {
+        auto ret = group.shfl_up(result, 1);
+        if (group.thread_rank() == 0) {
+            return {};
+        }
+        else {
+            return ret;
+        }
+    }
+};
+
+template <typename TyGroup, typename TyRes, typename TyVal, typename TyFn>
+_CG_QUALIFIER auto convert_inclusive_to_exclusive(const TyGroup& group, TyRes& result, TyVal&& val, TyFn&& op) -> decltype(op(val, val)) {
+    using conversion = scan_choose_convertion<_CG_STL_NAMESPACE::is_same<remove_qual<TyFn>, cooperative_groups::plus<remove_qual<TyVal>>>::value
+                                 && _CG_STL_NAMESPACE::is_integral<remove_qual<TyVal>>::value>;
+    return conversion::convert_inclusive_to_exclusive(group, result, _CG_STL_NAMESPACE::forward<TyVal>(val));
+}
+
+} // details
+
+_CG_END_NAMESPACE
+
+#endif // _CG_COALESCED_SCAN_H_

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/invoke.h

@@ -0,0 +1,189 @@
+/*
+ * Copyright 1993-2022 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#ifndef _CG_INVOKE_H
+#define _CG_INVOKE_H
+
+#include "info.h"
+#include "helpers.h"
+
+#if defined(_CG_CPP11_FEATURES)
+
+_CG_BEGIN_NAMESPACE
+
+namespace details {
+
+    template <typename Group>
+    struct _elect_group_supported : _CG_STL_NAMESPACE::false_type {};
+#ifdef _CG_HAS_INSTR_ELECT
+    template<>
+    struct _elect_group_supported<coalesced_group> : _CG_STL_NAMESPACE::true_type {};
+    template<unsigned int Size, typename Parent>
+    struct _elect_group_supported<thread_block_tile<Size, Parent>> :
+        _CG_STL_NAMESPACE::integral_constant<bool, (Size <= 32)> {};
+#endif
+
+    template <typename Group>
+    struct elect_group_supported : public _elect_group_supported<details::remove_qual<Group>> {};
+
+    template<typename Group>
+    _CG_STATIC_QUALIFIER bool elect_one(const Group& group, unsigned int mask, unsigned int& leader_lane) {
+        int is_leader = 0;
+#ifdef _CG_HAS_INSTR_ELECT
+        asm("{\n\t"
+          " .reg .pred p;\n\t"
+          "  elect.sync %0|p, %2;\n\t"
+          " @p mov.s32 %1, 1;\n\t"
+          "}"
+          : "+r"(leader_lane), "+r"(is_leader) : "r" (mask));
+#endif
+        return is_leader;
+    }
+
+    template<bool UseElect>
+    struct invoke_one_impl {};
+
+    template<>
+    struct invoke_one_impl<true> {
+        template<typename Group, typename Fn, typename... Args>
+        _CG_STATIC_QUALIFIER void invoke_one(const Group& group, Fn&& fn, Args&&... args) {
+            auto mask = details::_coalesced_group_data_access::get_mask(group);
+            unsigned int leader_lane = 0;
+
+            if (elect_one(group, mask, leader_lane)) {
+                _CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...);
+            }
+        }
+
+        template<typename Group, typename Fn, typename... Args>
+        _CG_STATIC_QUALIFIER auto invoke_one_broadcast(const Group& group, Fn&& fn, Args&&... args)
+                -> typename _CG_STL_NAMESPACE::remove_reference<
+                    decltype(_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...))>::type {
+
+            using ResultType = decltype(_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...));
+            details::remove_qual<ResultType> result;
+            auto mask = details::_coalesced_group_data_access::get_mask(group);
+            unsigned int leader_lane = 0;
+
+            if (elect_one(group, mask, leader_lane)) {
+                result = _CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...);
+            }
+
+            // Need to use low level api instead of group.shfl, because elect_one returns lane id, not group rank.
+            return tile::shuffle_dispatch<ResultType>::shfl(result, mask, leader_lane, 32);
+        }
+    };
+
+    template<>
+    struct invoke_one_impl<false> {
+        template<typename Group, typename Fn, typename... Args>
+        _CG_STATIC_QUALIFIER void invoke_one(const Group& group, Fn&& fn, Args&&... args) {
+            if (group.thread_rank() == 0) {
+                _CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...);
+            }
+        }
+
+        template<typename Group, typename Fn, typename... Args>
+        _CG_STATIC_QUALIFIER auto invoke_one_broadcast(const Group& group, Fn&& fn, Args&&... args)
+                -> typename _CG_STL_NAMESPACE::remove_reference<
+                    decltype(_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...))>::type {
+
+            using ResultType = decltype(_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...));
+            details::remove_qual<ResultType> result;
+
+            if (group.thread_rank() == 0) {
+                result = _CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...);
+            }
+
+            return group.shfl(result, 0);
+        }
+    };
+
+
+}; // namespace details
+
+template<typename Group, typename Fn, typename... Args>
+_CG_QUALIFIER void invoke_one(const Group& group, Fn&& fn, Args&&... args) {
+    using impl = details::invoke_one_impl<details::elect_group_supported<Group>::value>;
+    impl::invoke_one(group, _CG_STL_NAMESPACE::forward<Fn>(fn), _CG_STL_NAMESPACE::forward<Args>(args)...);
+}
+
+template<typename Fn, typename... Args>
+_CG_QUALIFIER auto invoke_one_broadcast(const coalesced_group& group, Fn&& fn, Args&&... args)
+        -> typename _CG_STL_NAMESPACE::remove_reference<
+            decltype(_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...))>::type {
+
+    using ResultType = decltype(_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...));
+    static_assert(!_CG_STL_NAMESPACE::is_same<ResultType, void>::value,
+                  "For invocables returning void invoke_one should be used instead");
+    using impl = details::invoke_one_impl<details::elect_group_supported<coalesced_group>::value>;
+    return impl::invoke_one_broadcast(group,
+                                      _CG_STL_NAMESPACE::forward<Fn>(fn),
+                                      _CG_STL_NAMESPACE::forward<Args>(args)...);
+}
+
+template<unsigned int Size, typename Parent, typename Fn, typename... Args>
+_CG_QUALIFIER auto invoke_one_broadcast(const thread_block_tile<Size, Parent>& group, Fn&& fn, Args&&... args)
+        -> typename _CG_STL_NAMESPACE::remove_reference<
+            decltype(_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...))>::type {
+
+    using ResultType = decltype(_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...));
+    static_assert(!_CG_STL_NAMESPACE::is_same<ResultType, void>::value,
+                  "For invocables returning void invoke_one should be used instead");
+    using impl = details::invoke_one_impl<details::elect_group_supported<thread_block_tile<Size, Parent>>::value>;
+    return impl::invoke_one_broadcast(group,
+                                      _CG_STL_NAMESPACE::forward<Fn>(fn),
+                                      _CG_STL_NAMESPACE::forward<Args>(args)...);
+}
+
+_CG_END_NAMESPACE
+
+#endif //_CG_CPP11_FEATURES
+
+#endif // _CG_INVOKE_H

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/memcpy_async.h

@@ -0,0 +1,62 @@
+ /* Copyright 1993-2016 NVIDIA Corporation.  All rights reserved.
+  *
+  * NOTICE TO LICENSEE:
+  *
+  * The source code and/or documentation ("Licensed Deliverables") are
+  * subject to NVIDIA intellectual property rights under U.S. and
+  * international Copyright laws.
+  *
+  * The Licensed Deliverables contained herein are PROPRIETARY and
+  * CONFIDENTIAL to NVIDIA and are being provided under the terms and
+  * conditions of a form of NVIDIA software license agreement by and
+  * between NVIDIA and Licensee ("License Agreement") or electronically
+  * accepted by Licensee.  Notwithstanding any terms or conditions to
+  * the contrary in the License Agreement, reproduction or disclosure
+  * of the Licensed Deliverables to any third party without the express
+  * written consent of NVIDIA is prohibited.
+  *
+  * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+  * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+  * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  THEY ARE
+  * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+  * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+  * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+  * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+  * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+  * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+  * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+  * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+  * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+  * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+  * OF THESE LICENSED DELIVERABLES.
+  *
+  * U.S. Government End Users.  These Licensed Deliverables are a
+  * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+  * 1995), consisting of "commercial computer software" and "commercial
+  * computer software documentation" as such terms are used in 48
+  * C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
+  * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+  * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+  * U.S. Government End Users acquire the Licensed Deliverables with
+  * only those rights set forth herein.
+  *
+  * Any use of the Licensed Deliverables in individual and commercial
+  * software must include, in the user documentation and internal
+  * comments to the code, the above Disclaimer and U.S. Government End
+  * Users Notice.
+  */
+
+#ifndef _COOPERATIVE_GROUPS_MEMCPY_ASYNC
+#define _COOPERATIVE_GROUPS_MEMCPY_ASYNC
+
+#include "../cooperative_groups.h"
+#include "details/info.h"
+
+#ifdef _CG_CPP11_FEATURES
+# include "details/async.h"
+#else
+# error This file requires compiler support for the ISO C++ 2011 standard. This support must be enabled with the \
+         -std=c++11 compiler option.
+#endif
+
+#endif // _COOPERATIVE_GROUPS_MEMCPY_ASYNC

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/reduce.h

@@ -0,0 +1,63 @@
+ /* Copyright 1993-2016 NVIDIA Corporation.  All rights reserved.
+  *
+  * NOTICE TO LICENSEE:
+  *
+  * The source code and/or documentation ("Licensed Deliverables") are
+  * subject to NVIDIA intellectual property rights under U.S. and
+  * international Copyright laws.
+  *
+  * The Licensed Deliverables contained herein are PROPRIETARY and
+  * CONFIDENTIAL to NVIDIA and are being provided under the terms and
+  * conditions of a form of NVIDIA software license agreement by and
+  * between NVIDIA and Licensee ("License Agreement") or electronically
+  * accepted by Licensee.  Notwithstanding any terms or conditions to
+  * the contrary in the License Agreement, reproduction or disclosure
+  * of the Licensed Deliverables to any third party without the express
+  * written consent of NVIDIA is prohibited.
+  *
+  * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+  * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+  * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  THEY ARE
+  * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+  * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+  * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+  * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+  * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+  * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+  * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+  * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+  * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+  * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+  * OF THESE LICENSED DELIVERABLES.
+  *
+  * U.S. Government End Users.  These Licensed Deliverables are a
+  * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+  * 1995), consisting of "commercial computer software" and "commercial
+  * computer software documentation" as such terms are used in 48
+  * C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
+  * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+  * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+  * U.S. Government End Users acquire the Licensed Deliverables with
+  * only those rights set forth herein.
+  *
+  * Any use of the Licensed Deliverables in individual and commercial
+  * software must include, in the user documentation and internal
+  * comments to the code, the above Disclaimer and U.S. Government End
+  * Users Notice.
+  */
+
+#ifndef _COOPERATIVE_GROUPS_REDUCE_H
+#define _COOPERATIVE_GROUPS_REDUCE_H
+
+#include "../cooperative_groups.h"
+#include "details/info.h"
+
+#ifdef _CG_CPP11_FEATURES
+# include "details/reduce.h"
+#else
+# error This file requires compiler support for the ISO C++ 2011 standard. This support must be enabled with the \
+         -std=c++11 compiler option.
+#endif
+
+
+#endif //_COOPERATIVE_GROUPS_REDUCE_H

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/scan.h

@@ -0,0 +1,63 @@
+/* Copyright 1993-2016 NVIDIA Corporation.  All rights reserved.
+  *
+  * NOTICE TO LICENSEE:
+  *
+  * The source code and/or documentation ("Licensed Deliverables") are
+  * subject to NVIDIA intellectual property rights under U.S. and
+  * international Copyright laws.
+  *
+  * The Licensed Deliverables contained herein are PROPRIETARY and
+  * CONFIDENTIAL to NVIDIA and are being provided under the terms and
+  * conditions of a form of NVIDIA software license agreement by and
+  * between NVIDIA and Licensee ("License Agreement") or electronically
+  * accepted by Licensee.  Notwithstanding any terms or conditions to
+  * the contrary in the License Agreement, reproduction or disclosure
+  * of the Licensed Deliverables to any third party without the express
+  * written consent of NVIDIA is prohibited.
+  *
+  * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+  * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+  * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  THEY ARE
+  * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+  * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+  * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+  * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+  * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+  * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+  * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+  * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+  * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+  * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+  * OF THESE LICENSED DELIVERABLES.
+  *
+  * U.S. Government End Users.  These Licensed Deliverables are a
+  * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+  * 1995), consisting of "commercial computer software" and "commercial
+  * computer software documentation" as such terms are used in 48
+  * C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
+  * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+  * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+  * U.S. Government End Users acquire the Licensed Deliverables with
+  * only those rights set forth herein.
+  *
+  * Any use of the Licensed Deliverables in individual and commercial
+  * software must include, in the user documentation and internal
+  * comments to the code, the above Disclaimer and U.S. Government End
+  * Users Notice.
+  */
+
+#ifndef _COOPERATIVE_GROUPS_SCAN_H
+#define _COOPERATIVE_GROUPS_SCAN_H
+
+#include "../cooperative_groups.h"
+#include "details/info.h"
+
+#ifdef _CG_CPP11_FEATURES
+# include "details/scan.h"
+#else
+# error This file requires compiler support for the ISO C++ 2011 standard. This support must be enabled with the \
+         -std=c++11 compiler option.
+#endif
+
+
+#endif //_COOPERATIVE_GROUPS_SCAN_H

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cuComplex.h

@@ -0,0 +1,348 @@
+/*
+ * Copyright 1993-2012 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(CU_COMPLEX_H_)
+#define CU_COMPLEX_H_
+
+#if !defined(__CUDACC_RTC__)
+#if defined(__GNUC__)
+#if defined(__clang__) || (!defined(__PGIC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 2)))
+#pragma GCC diagnostic ignored "-Wunused-function"
+#endif
+#endif
+#endif
+
+/* When trying to include C header file in C++ Code extern "C" is required
+ * But the Standard QNX headers already have ifdef extern in them when compiling C++ Code
+ * extern "C" cannot be nested
+ * Hence keep the header out of extern "C" block
+ */
+
+#if !defined(__CUDACC__)
+#include <math.h>       /* import fabsf, sqrt */
+#endif /* !defined(__CUDACC__) */
+
+#if defined(__cplusplus)
+extern "C" {
+#endif /* __cplusplus */
+
+#include "vector_types.h"
+
+typedef float2 cuFloatComplex;
+
+__host__ __device__ static __inline__ float cuCrealf (cuFloatComplex x) 
+{ 
+    return x.x; 
+}
+
+__host__ __device__ static __inline__ float cuCimagf (cuFloatComplex x) 
+{ 
+    return x.y; 
+}
+
+__host__ __device__ static __inline__ cuFloatComplex make_cuFloatComplex 
+                                                             (float r, float i)
+{
+    cuFloatComplex res;
+    res.x = r;
+    res.y = i;
+    return res;
+}
+
+__host__ __device__ static __inline__ cuFloatComplex cuConjf (cuFloatComplex x)
+{
+    return make_cuFloatComplex (cuCrealf(x), -cuCimagf(x));
+}
+__host__ __device__ static __inline__ cuFloatComplex cuCaddf (cuFloatComplex x,
+                                                              cuFloatComplex y)
+{
+    return make_cuFloatComplex (cuCrealf(x) + cuCrealf(y), 
+                                cuCimagf(x) + cuCimagf(y));
+}
+
+__host__ __device__ static __inline__ cuFloatComplex cuCsubf (cuFloatComplex x,
+                                                              cuFloatComplex y)
+{
+        return make_cuFloatComplex (cuCrealf(x) - cuCrealf(y), 
+                                    cuCimagf(x) - cuCimagf(y));
+}
+
+/* This implementation could suffer from intermediate overflow even though
+ * the final result would be in range. However, various implementations do
+ * not guard against this (presumably to avoid losing performance), so we 
+ * don't do it either to stay competitive.
+ */
+__host__ __device__ static __inline__ cuFloatComplex cuCmulf (cuFloatComplex x,
+                                                              cuFloatComplex y)
+{
+    cuFloatComplex prod;
+    prod = make_cuFloatComplex  ((cuCrealf(x) * cuCrealf(y)) - 
+                                 (cuCimagf(x) * cuCimagf(y)),
+                                 (cuCrealf(x) * cuCimagf(y)) + 
+                                 (cuCimagf(x) * cuCrealf(y)));
+    return prod;
+}
+
+/* This implementation guards against intermediate underflow and overflow
+ * by scaling. Such guarded implementations are usually the default for
+ * complex library implementations, with some also offering an unguarded,
+ * faster version.
+ */
+__host__ __device__ static __inline__ cuFloatComplex cuCdivf (cuFloatComplex x,
+                                                              cuFloatComplex y)
+{
+    cuFloatComplex quot;
+    float s = fabsf(cuCrealf(y)) + fabsf(cuCimagf(y));
+    float oos = 1.0f / s;
+    float ars = cuCrealf(x) * oos;
+    float ais = cuCimagf(x) * oos;
+    float brs = cuCrealf(y) * oos;
+    float bis = cuCimagf(y) * oos;
+    s = (brs * brs) + (bis * bis);
+    oos = 1.0f / s;
+    quot = make_cuFloatComplex (((ars * brs) + (ais * bis)) * oos,
+                                ((ais * brs) - (ars * bis)) * oos);
+    return quot;
+}
+
+/* 
+ * We would like to call hypotf(), but it's not available on all platforms.
+ * This discrete implementation guards against intermediate underflow and 
+ * overflow by scaling. Otherwise we would lose half the exponent range. 
+ * There are various ways of doing guarded computation. For now chose the 
+ * simplest and fastest solution, however this may suffer from inaccuracies 
+ * if sqrt and division are not IEEE compliant. 
+ */
+__host__ __device__ static __inline__ float cuCabsf (cuFloatComplex x)
+{
+    float a = cuCrealf(x);
+    float b = cuCimagf(x);
+    float v, w, t;
+    a = fabsf(a);
+    b = fabsf(b);
+    if (a > b) {
+        v = a;
+        w = b; 
+    } else {
+        v = b;
+        w = a;
+    }
+    t = w / v;
+    t = 1.0f + t * t;
+    t = v * sqrtf(t);
+    if ((v == 0.0f) || (v > 3.402823466e38f) || (w > 3.402823466e38f)) {
+        t = v + w;
+    }
+    return t;
+}
+
+/* Double precision */
+typedef double2 cuDoubleComplex;
+
+__host__ __device__ static __inline__ double cuCreal (cuDoubleComplex x) 
+{ 
+    return x.x; 
+}
+
+__host__ __device__ static __inline__ double cuCimag (cuDoubleComplex x) 
+{ 
+    return x.y; 
+}
+
+__host__ __device__ static __inline__ cuDoubleComplex make_cuDoubleComplex 
+                                                           (double r, double i)
+{
+    cuDoubleComplex res;
+    res.x = r;
+    res.y = i;
+    return res;
+}
+
+__host__ __device__ static __inline__ cuDoubleComplex cuConj(cuDoubleComplex x)
+{
+    return make_cuDoubleComplex (cuCreal(x), -cuCimag(x));
+}
+
+__host__ __device__ static __inline__ cuDoubleComplex cuCadd(cuDoubleComplex x,
+                                                             cuDoubleComplex y)
+{
+    return make_cuDoubleComplex (cuCreal(x) + cuCreal(y), 
+                                 cuCimag(x) + cuCimag(y));
+}
+
+__host__ __device__ static __inline__ cuDoubleComplex cuCsub(cuDoubleComplex x,
+                                                             cuDoubleComplex y)
+{
+    return make_cuDoubleComplex (cuCreal(x) - cuCreal(y), 
+                                 cuCimag(x) - cuCimag(y));
+}
+
+/* This implementation could suffer from intermediate overflow even though
+ * the final result would be in range. However, various implementations do
+ * not guard against this (presumably to avoid losing performance), so we 
+ * don't do it either to stay competitive.
+ */
+__host__ __device__ static __inline__ cuDoubleComplex cuCmul(cuDoubleComplex x,
+                                                             cuDoubleComplex y)
+{
+    cuDoubleComplex prod;
+    prod = make_cuDoubleComplex ((cuCreal(x) * cuCreal(y)) - 
+                                 (cuCimag(x) * cuCimag(y)),
+                                 (cuCreal(x) * cuCimag(y)) + 
+                                 (cuCimag(x) * cuCreal(y)));
+    return prod;
+}
+
+/* This implementation guards against intermediate underflow and overflow
+ * by scaling. Such guarded implementations are usually the default for
+ * complex library implementations, with some also offering an unguarded,
+ * faster version.
+ */
+__host__ __device__ static __inline__ cuDoubleComplex cuCdiv(cuDoubleComplex x,
+                                                             cuDoubleComplex y)
+{
+    cuDoubleComplex quot;
+    double s = (fabs(cuCreal(y))) + (fabs(cuCimag(y)));
+    double oos = 1.0 / s;
+    double ars = cuCreal(x) * oos;
+    double ais = cuCimag(x) * oos;
+    double brs = cuCreal(y) * oos;
+    double bis = cuCimag(y) * oos;
+    s = (brs * brs) + (bis * bis);
+    oos = 1.0 / s;
+    quot = make_cuDoubleComplex (((ars * brs) + (ais * bis)) * oos,
+                                 ((ais * brs) - (ars * bis)) * oos);
+    return quot;
+}
+
+/* This implementation guards against intermediate underflow and overflow
+ * by scaling. Otherwise we would lose half the exponent range. There are
+ * various ways of doing guarded computation. For now chose the simplest
+ * and fastest solution, however this may suffer from inaccuracies if sqrt
+ * and division are not IEEE compliant.
+ */
+__host__ __device__ static __inline__ double cuCabs (cuDoubleComplex x)
+{
+    double a = cuCreal(x);
+    double b = cuCimag(x);
+    double v, w, t;
+    a = fabs(a);
+    b = fabs(b);
+    if (a > b) {
+        v = a;
+        w = b; 
+    } else {
+        v = b;
+        w = a;
+    }
+    t = w / v;
+    t = 1.0 + t * t;
+    t = v * sqrt(t);
+    if ((v == 0.0) || 
+        (v > 1.79769313486231570e+308) || (w > 1.79769313486231570e+308)) {
+        t = v + w;
+    }
+    return t;
+}
+
+#if defined(__cplusplus)
+}
+#endif /* __cplusplus */
+
+/* aliases */
+typedef cuFloatComplex cuComplex;
+__host__ __device__ static __inline__ cuComplex make_cuComplex (float x, 
+                                                                float y) 
+{ 
+    return make_cuFloatComplex (x, y); 
+}
+
+/* float-to-double promotion */
+__host__ __device__ static __inline__ cuDoubleComplex cuComplexFloatToDouble
+                                                      (cuFloatComplex c)
+{
+    return make_cuDoubleComplex ((double)cuCrealf(c), (double)cuCimagf(c));
+}
+
+__host__ __device__ static __inline__ cuFloatComplex cuComplexDoubleToFloat
+(cuDoubleComplex c)
+{
+	return make_cuFloatComplex ((float)cuCreal(c), (float)cuCimag(c));
+}
+
+
+__host__ __device__ static __inline__  cuComplex cuCfmaf( cuComplex x, cuComplex y, cuComplex d)
+{
+    float real_res;
+    float imag_res;
+    
+    real_res = (cuCrealf(x) *  cuCrealf(y)) + cuCrealf(d);
+    imag_res = (cuCrealf(x) *  cuCimagf(y)) + cuCimagf(d);
+            
+    real_res = -(cuCimagf(x) * cuCimagf(y))  + real_res;  
+    imag_res =  (cuCimagf(x) *  cuCrealf(y)) + imag_res;          
+     
+    return make_cuComplex(real_res, imag_res);
+}
+
+__host__ __device__ static __inline__  cuDoubleComplex cuCfma( cuDoubleComplex x, cuDoubleComplex y, cuDoubleComplex d)
+{
+    double real_res;
+    double imag_res;
+    
+    real_res = (cuCreal(x) *  cuCreal(y)) + cuCreal(d);
+    imag_res = (cuCreal(x) *  cuCimag(y)) + cuCimag(d);
+            
+    real_res = -(cuCimag(x) * cuCimag(y))  + real_res;  
+    imag_res =  (cuCimag(x) *  cuCreal(y)) + imag_res;     
+     
+    return make_cuDoubleComplex(real_res, imag_res);
+}
+
+#endif /* !defined(CU_COMPLEX_H_) */

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cudaEGLTypedefs.h

@@ -0,0 +1,96 @@
+/*
+ * Copyright 2020-2021 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#ifndef CUDAEGLTYPEDEFS_H
+#define CUDAEGLTYPEDEFS_H
+
+#include <cudaEGL.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif // __cplusplus
+
+/*
+ * Macros for the latest version for each driver function in cudaEGL.h
+ */
+#define PFN_cuGraphicsEGLRegisterImage  PFN_cuGraphicsEGLRegisterImage_v7000
+#define PFN_cuEGLStreamConsumerConnect  PFN_cuEGLStreamConsumerConnect_v7000
+#define PFN_cuEGLStreamConsumerConnectWithFlags  PFN_cuEGLStreamConsumerConnectWithFlags_v8000
+#define PFN_cuEGLStreamConsumerDisconnect  PFN_cuEGLStreamConsumerDisconnect_v7000
+#define PFN_cuEGLStreamConsumerAcquireFrame  PFN_cuEGLStreamConsumerAcquireFrame_v7000
+#define PFN_cuEGLStreamConsumerReleaseFrame  PFN_cuEGLStreamConsumerReleaseFrame_v7000
+#define PFN_cuEGLStreamProducerConnect  PFN_cuEGLStreamProducerConnect_v7000
+#define PFN_cuEGLStreamProducerDisconnect  PFN_cuEGLStreamProducerDisconnect_v7000
+#define PFN_cuEGLStreamProducerPresentFrame  PFN_cuEGLStreamProducerPresentFrame_v7000
+#define PFN_cuEGLStreamProducerReturnFrame  PFN_cuEGLStreamProducerReturnFrame_v7000
+#define PFN_cuGraphicsResourceGetMappedEglFrame  PFN_cuGraphicsResourceGetMappedEglFrame_v7000
+#define PFN_cuEventCreateFromEGLSync  PFN_cuEventCreateFromEGLSync_v9000
+
+
+/**
+ * Type definitions for functions defined in cudaEGL.h
+ */
+typedef CUresult (CUDAAPI *PFN_cuGraphicsEGLRegisterImage_v7000)(CUgraphicsResource CUDAAPI *pCudaResource, EGLImageKHR image, unsigned int flags);
+typedef CUresult (CUDAAPI *PFN_cuEGLStreamConsumerConnect_v7000)(CUeglStreamConnection CUDAAPI *conn, EGLStreamKHR stream);
+typedef CUresult (CUDAAPI *PFN_cuEGLStreamConsumerConnectWithFlags_v8000)(CUeglStreamConnection CUDAAPI *conn, EGLStreamKHR stream, unsigned int flags);
+typedef CUresult (CUDAAPI *PFN_cuEGLStreamConsumerDisconnect_v7000)(CUeglStreamConnection CUDAAPI *conn);
+typedef CUresult (CUDAAPI *PFN_cuEGLStreamConsumerAcquireFrame_v7000)(CUeglStreamConnection CUDAAPI *conn, CUgraphicsResource CUDAAPI *pCudaResource, CUstream CUDAAPI *pStream, unsigned int timeout);
+typedef CUresult (CUDAAPI *PFN_cuEGLStreamConsumerReleaseFrame_v7000)(CUeglStreamConnection CUDAAPI *conn, CUgraphicsResource pCudaResource, CUstream CUDAAPI *pStream);
+typedef CUresult (CUDAAPI *PFN_cuEGLStreamProducerConnect_v7000)(CUeglStreamConnection CUDAAPI *conn, EGLStreamKHR stream, EGLint width, EGLint height);
+typedef CUresult (CUDAAPI *PFN_cuEGLStreamProducerDisconnect_v7000)(CUeglStreamConnection CUDAAPI *conn);
+typedef CUresult (CUDAAPI *PFN_cuEGLStreamProducerPresentFrame_v7000)(CUeglStreamConnection CUDAAPI *conn, CUeglFrame_v1 eglframe, CUstream CUDAAPI *pStream);
+typedef CUresult (CUDAAPI *PFN_cuEGLStreamProducerReturnFrame_v7000)(CUeglStreamConnection CUDAAPI *conn, CUeglFrame_v1 CUDAAPI *eglframe, CUstream CUDAAPI *pStream);
+typedef CUresult (CUDAAPI *PFN_cuGraphicsResourceGetMappedEglFrame_v7000)(CUeglFrame_v1 CUDAAPI *eglFrame, CUgraphicsResource resource, unsigned int index, unsigned int mipLevel);
+typedef CUresult (CUDAAPI *PFN_cuEventCreateFromEGLSync_v9000)(CUevent CUDAAPI *phEvent, EGLSyncKHR eglSync, unsigned int flags);
+
+#ifdef __cplusplus
+}
+#endif // __cplusplus
+
+#endif // file guard

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cudaProfilerTypedefs.h

@@ -0,0 +1,78 @@
+/*
+ * Copyright 2020-2021 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#ifndef CUDAPROFILERTYPEDEFS_H
+#define CUDAPROFILERTYPEDEFS_H
+
+#include <cudaProfiler.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif // __cplusplus
+
+/*
+ * Macros for the latest version for each driver function in cudaProfiler.h
+ */
+#define PFN_cuProfilerInitialize  PFN_cuProfilerInitialize_v4000
+#define PFN_cuProfilerStart  PFN_cuProfilerStart_v4000
+#define PFN_cuProfilerStop  PFN_cuProfilerStop_v4000
+
+
+/**
+ * Type definitions for functions defined in cudaProfiler.h
+ */
+typedef CUresult (CUDAAPI *PFN_cuProfilerInitialize_v4000)(const char *configFile, const char *outputFile, CUoutput_mode outputMode);
+typedef CUresult (CUDAAPI *PFN_cuProfilerStart_v4000)(void);
+typedef CUresult (CUDAAPI *PFN_cuProfilerStop_v4000)(void);
+
+#ifdef __cplusplus
+}
+#endif // __cplusplus
+
+#endif // file guard

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cudaVDPAU.h

@@ -0,0 +1,282 @@
+/*
+ * Copyright 2010-2014 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#ifndef CUDAVDPAU_H
+#define CUDAVDPAU_H
+
+#ifdef CUDA_FORCE_API_VERSION
+#error "CUDA_FORCE_API_VERSION is no longer supported."
+#endif
+
+#define cuVDPAUCtxCreate cuVDPAUCtxCreate_v2
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/**
+ * \defgroup CUDA_VDPAU VDPAU Interoperability
+ * \ingroup CUDA_DRIVER
+ *
+ * ___MANBRIEF___ VDPAU interoperability functions of the low-level CUDA driver
+ * API (___CURRENT_FILE___) ___ENDMANBRIEF___
+ *
+ * This section describes the VDPAU interoperability functions of the
+ * low-level CUDA driver application programming interface.
+ *
+ * @{
+ */
+
+/**
+ * \brief Gets the CUDA device associated with a VDPAU device
+ *
+ * Returns in \p *pDevice the CUDA device associated with a \p vdpDevice, if
+ * applicable.
+ *
+ * \param pDevice           - Device associated with vdpDevice
+ * \param vdpDevice         - A VdpDevice handle
+ * \param vdpGetProcAddress - VDPAU's VdpGetProcAddress function pointer
+ *
+ * \return
+ * ::CUDA_SUCCESS,
+ * ::CUDA_ERROR_DEINITIALIZED,
+ * ::CUDA_ERROR_NOT_INITIALIZED,
+ * ::CUDA_ERROR_INVALID_CONTEXT,
+ * ::CUDA_ERROR_INVALID_VALUE
+ * \notefnerr
+ *
+ * \sa ::cuCtxCreate, ::cuVDPAUCtxCreate, ::cuGraphicsVDPAURegisterVideoSurface,
+ * ::cuGraphicsVDPAURegisterOutputSurface, ::cuGraphicsUnregisterResource,
+ * ::cuGraphicsResourceSetMapFlags, ::cuGraphicsMapResources,
+ * ::cuGraphicsUnmapResources, ::cuGraphicsSubResourceGetMappedArray,
+ * ::cudaVDPAUGetDevice
+ */
+CUresult CUDAAPI cuVDPAUGetDevice(CUdevice *pDevice, VdpDevice vdpDevice, VdpGetProcAddress *vdpGetProcAddress);
+
+/**
+ * \brief Create a CUDA context for interoperability with VDPAU
+ *
+ * Creates a new CUDA context, initializes VDPAU interoperability, and
+ * associates the CUDA context with the calling thread. It must be called
+ * before performing any other VDPAU interoperability operations. It may fail
+ * if the needed VDPAU driver facilities are not available. For usage of the
+ * \p flags parameter, see ::cuCtxCreate().
+ *
+ * \param pCtx              - Returned CUDA context
+ * \param flags             - Options for CUDA context creation
+ * \param device            - Device on which to create the context
+ * \param vdpDevice         - The VdpDevice to interop with
+ * \param vdpGetProcAddress - VDPAU's VdpGetProcAddress function pointer
+ *
+ * \return
+ * ::CUDA_SUCCESS,
+ * ::CUDA_ERROR_DEINITIALIZED,
+ * ::CUDA_ERROR_NOT_INITIALIZED,
+ * ::CUDA_ERROR_INVALID_CONTEXT,
+ * ::CUDA_ERROR_INVALID_VALUE,
+ * ::CUDA_ERROR_OUT_OF_MEMORY
+ * \notefnerr
+ *
+ * \sa ::cuCtxCreate, ::cuGraphicsVDPAURegisterVideoSurface,
+ * ::cuGraphicsVDPAURegisterOutputSurface, ::cuGraphicsUnregisterResource,
+ * ::cuGraphicsResourceSetMapFlags, ::cuGraphicsMapResources,
+ * ::cuGraphicsUnmapResources, ::cuGraphicsSubResourceGetMappedArray,
+ * ::cuVDPAUGetDevice
+ */
+CUresult CUDAAPI cuVDPAUCtxCreate(CUcontext *pCtx, unsigned int flags, CUdevice device, VdpDevice vdpDevice, VdpGetProcAddress *vdpGetProcAddress);
+
+/**
+ * \brief Registers a VDPAU VdpVideoSurface object
+ *
+ * Registers the VdpVideoSurface specified by \p vdpSurface for access by
+ * CUDA. A handle to the registered object is returned as \p pCudaResource.
+ * The surface's intended usage is specified using \p flags, as follows:
+ *
+ * - ::CU_GRAPHICS_MAP_RESOURCE_FLAGS_NONE: Specifies no hints about how this
+ *   resource will be used. It is therefore assumed that this resource will be
+ *   read from and written to by CUDA. This is the default value.
+ * - ::CU_GRAPHICS_MAP_RESOURCE_FLAGS_READ_ONLY: Specifies that CUDA
+ *   will not write to this resource.
+ * - ::CU_GRAPHICS_MAP_RESOURCE_FLAGS_WRITE_DISCARD: Specifies that
+ *   CUDA will not read from this resource and will write over the
+ *   entire contents of the resource, so none of the data previously
+ *   stored in the resource will be preserved.
+ *
+ * The VdpVideoSurface is presented as an array of subresources that may be
+ * accessed using pointers returned by ::cuGraphicsSubResourceGetMappedArray.
+ * The exact number of valid \p arrayIndex values depends on the VDPAU surface
+ * format. The mapping is shown in the table below. \p mipLevel must be 0.
+ *
+ * \htmlonly
+ * <table>
+ * <tr><th>VdpChromaType                               </th><th>arrayIndex</th><th>Size     </th><th>Format</th><th>Content            </th></tr>
+ * <tr><td rowspan="4" valign="top">VDP_CHROMA_TYPE_420</td><td>0         </td><td>w   x h/2</td><td>R8    </td><td>Top-field luma     </td></tr>
+ * <tr>                                                     <td>1         </td><td>w   x h/2</td><td>R8    </td><td>Bottom-field luma  </td></tr>
+ * <tr>                                                     <td>2         </td><td>w/2 x h/4</td><td>R8G8  </td><td>Top-field chroma   </td></tr>
+ * <tr>                                                     <td>3         </td><td>w/2 x h/4</td><td>R8G8  </td><td>Bottom-field chroma</td></tr>
+ * <tr><td rowspan="4" valign="top">VDP_CHROMA_TYPE_422</td><td>0         </td><td>w   x h/2</td><td>R8    </td><td>Top-field luma     </td></tr>
+ * <tr>                                                     <td>1         </td><td>w   x h/2</td><td>R8    </td><td>Bottom-field luma  </td></tr>
+ * <tr>                                                     <td>2         </td><td>w/2 x h/2</td><td>R8G8  </td><td>Top-field chroma   </td></tr>
+ * <tr>                                                     <td>3         </td><td>w/2 x h/2</td><td>R8G8  </td><td>Bottom-field chroma</td></tr>
+ * </table>
+ * \endhtmlonly
+ *
+ * \latexonly
+ * \begin{tabular}{|l|l|l|l|l|}
+ * \hline
+ * VdpChromaType          & arrayIndex & Size      & Format & Content             \\
+ * \hline
+ * VDP\_CHROMA\_TYPE\_420 & 0          & w x h/2   & R8     & Top-field luma      \\
+ *                        & 1          & w x h/2   & R8     & Bottom-field luma   \\
+ *                        & 2          & w/2 x h/4 & R8G8   & Top-field chroma    \\
+ *                        & 3          & w/2 x h/4 & R8G8   & Bottom-field chroma \\
+ * \hline
+ * VDP\_CHROMA\_TYPE\_422 & 0          & w x h/2   & R8     & Top-field luma      \\
+ *                        & 1          & w x h/2   & R8     & Bottom-field luma   \\
+ *                        & 2          & w/2 x h/2 & R8G8   & Top-field chroma    \\
+ *                        & 3          & w/2 x h/2 & R8G8   & Bottom-field chroma \\
+ * \hline
+ * \end{tabular}
+ * \endlatexonly
+ *
+ * \param pCudaResource - Pointer to the returned object handle
+ * \param vdpSurface    - The VdpVideoSurface to be registered
+ * \param flags         - Map flags
+ *
+ * \return
+ * ::CUDA_SUCCESS,
+ * ::CUDA_ERROR_INVALID_HANDLE,
+ * ::CUDA_ERROR_ALREADY_MAPPED,
+ * ::CUDA_ERROR_INVALID_CONTEXT,
+ * \notefnerr
+ *
+ * \sa ::cuCtxCreate, ::cuVDPAUCtxCreate,
+ * ::cuGraphicsVDPAURegisterOutputSurface, ::cuGraphicsUnregisterResource,
+ * ::cuGraphicsResourceSetMapFlags, ::cuGraphicsMapResources,
+ * ::cuGraphicsUnmapResources, ::cuGraphicsSubResourceGetMappedArray,
+ * ::cuVDPAUGetDevice,
+ * ::cudaGraphicsVDPAURegisterVideoSurface
+ */
+CUresult CUDAAPI cuGraphicsVDPAURegisterVideoSurface(CUgraphicsResource *pCudaResource, VdpVideoSurface vdpSurface, unsigned int flags);
+
+/**
+ * \brief Registers a VDPAU VdpOutputSurface object
+ *
+ * Registers the VdpOutputSurface specified by \p vdpSurface for access by
+ * CUDA. A handle to the registered object is returned as \p pCudaResource.
+ * The surface's intended usage is specified using \p flags, as follows:
+ *
+ * - ::CU_GRAPHICS_MAP_RESOURCE_FLAGS_NONE: Specifies no hints about how this
+ *   resource will be used. It is therefore assumed that this resource will be
+ *   read from and written to by CUDA. This is the default value.
+ * - ::CU_GRAPHICS_MAP_RESOURCE_FLAGS_READ_ONLY: Specifies that CUDA
+ *   will not write to this resource.
+ * - ::CU_GRAPHICS_MAP_RESOURCE_FLAGS_WRITE_DISCARD: Specifies that
+ *   CUDA will not read from this resource and will write over the
+ *   entire contents of the resource, so none of the data previously
+ *   stored in the resource will be preserved.
+ *
+ * The VdpOutputSurface is presented as an array of subresources that may be
+ * accessed using pointers returned by ::cuGraphicsSubResourceGetMappedArray.
+ * The exact number of valid \p arrayIndex values depends on the VDPAU surface
+ * format. The mapping is shown in the table below. \p mipLevel must be 0.
+ *
+ * \htmlonly
+ * <table>
+ * <tr><th>VdpRGBAFormat              </th><th>arrayIndex</th><th>Size </th><th>Format </th><th>Content       </th></tr>
+ * <tr><td>VDP_RGBA_FORMAT_B8G8R8A8   </td><td>0         </td><td>w x h</td><td>ARGB8  </td><td>Entire surface</td></tr>
+ * <tr><td>VDP_RGBA_FORMAT_R10G10B10A2</td><td>0         </td><td>w x h</td><td>A2BGR10</td><td>Entire surface</td></tr>
+ * </table>
+ * \endhtmlonly
+ *
+ * \latexonly
+ * \begin{tabular}{|l|l|l|l|l|}
+ * \hline
+ * VdpRGBAFormat                  & arrayIndex & Size  & Format  & Content        \\
+ * \hline
+ * VDP\_RGBA\_FORMAT\_B8G8R8A8    & 0          & w x h & ARGB8   & Entire surface \\
+ * VDP\_RGBA\_FORMAT\_R10G10B10A2 & 0          & w x h & A2BGR10 & Entire surface \\
+ * \hline
+ * \end{tabular}
+ * \endlatexonly
+ *
+ * \param pCudaResource - Pointer to the returned object handle
+ * \param vdpSurface    - The VdpOutputSurface to be registered
+ * \param flags         - Map flags
+ *
+ * \return
+ * ::CUDA_SUCCESS,
+ * ::CUDA_ERROR_INVALID_HANDLE,
+ * ::CUDA_ERROR_ALREADY_MAPPED,
+ * ::CUDA_ERROR_INVALID_CONTEXT,
+ * \notefnerr
+ *
+ * \sa ::cuCtxCreate, ::cuVDPAUCtxCreate,
+ * ::cuGraphicsVDPAURegisterVideoSurface, ::cuGraphicsUnregisterResource,
+ * ::cuGraphicsResourceSetMapFlags, ::cuGraphicsMapResources,
+ * ::cuGraphicsUnmapResources, ::cuGraphicsSubResourceGetMappedArray,
+ * ::cuVDPAUGetDevice,
+ * ::cudaGraphicsVDPAURegisterOutputSurface
+ */
+CUresult CUDAAPI cuGraphicsVDPAURegisterOutputSurface(CUgraphicsResource *pCudaResource, VdpOutputSurface vdpSurface, unsigned int flags);
+
+/** @} */ /* END CUDA_VDPAU */
+
+
+#if defined(__CUDA_API_VERSION_INTERNAL)
+    #undef cuVDPAUCtxCreate
+
+    CUresult CUDAAPI cuVDPAUCtxCreate(CUcontext *pCtx, unsigned int flags, CUdevice device, VdpDevice vdpDevice, VdpGetProcAddress *vdpGetProcAddress);
+#endif /* __CUDA_API_VERSION_INTERNAL */
+
+#ifdef __cplusplus
+};
+#endif
+
+#endif

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cudaVDPAUTypedefs.h

@@ -0,0 +1,90 @@
+/*
+ * Copyright 2020-2021 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#ifndef CUDAVDPAUTYPEDEFS_H
+#define CUDAVDPAUTYPEDEFS_H
+
+// Dependent includes for cudavdpau.h
+#include <vdpau/vdpau.h>
+
+#include <cudaVDPAU.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif // __cplusplus
+
+/*
+ * Macros for the latest version for each driver function in cudaVDPAU.h
+ */
+#define PFN_cuVDPAUGetDevice  PFN_cuVDPAUGetDevice_v3010
+#define PFN_cuVDPAUCtxCreate  PFN_cuVDPAUCtxCreate_v3020
+#define PFN_cuGraphicsVDPAURegisterVideoSurface  PFN_cuGraphicsVDPAURegisterVideoSurface_v3010
+#define PFN_cuGraphicsVDPAURegisterOutputSurface  PFN_cuGraphicsVDPAURegisterOutputSurface_v3010
+
+
+/**
+ * Type definitions for functions defined in cudaVDPAU.h
+ */
+typedef CUresult (CUDAAPI *PFN_cuVDPAUGetDevice_v3010)(CUdevice_v1 *pDevice, VdpDevice vdpDevice, VdpGetProcAddress *vdpGetProcAddress);
+typedef CUresult (CUDAAPI *PFN_cuVDPAUCtxCreate_v3020)(CUcontext *pCtx, unsigned int flags, CUdevice_v1 device, VdpDevice vdpDevice, VdpGetProcAddress *vdpGetProcAddress);
+typedef CUresult (CUDAAPI *PFN_cuGraphicsVDPAURegisterVideoSurface_v3010)(CUgraphicsResource *pCudaResource, VdpVideoSurface vdpSurface, unsigned int flags);
+typedef CUresult (CUDAAPI *PFN_cuGraphicsVDPAURegisterOutputSurface_v3010)(CUgraphicsResource *pCudaResource, VdpOutputSurface vdpSurface, unsigned int flags);
+
+/*
+ * Type definitions for older versioned functions in cudaVDPAU.h
+ */
+#if defined(__CUDA_API_VERSION_INTERNAL)
+typedef CUresult (CUDAAPI *PFN_cuVDPAUCtxCreate_v3010)(CUcontext *pCtx, unsigned int flags, CUdevice_v1 device, VdpDevice vdpDevice, VdpGetProcAddress *vdpGetProcAddress);
+#endif
+
+#ifdef __cplusplus
+}
+#endif // __cplusplus
+
+#endif // file guard

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cuda_awbarrier_primitives.h

@@ -0,0 +1,109 @@
+/*
+ * Copyright 1993-2019 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#ifndef _CUDA_AWBARRIER_PRIMITIVES_H_
+#define _CUDA_AWBARRIER_PRIMITIVES_H_
+
+#include "cuda_awbarrier_helpers.h"
+
+#if !defined(_CUDA_AWBARRIER_SM_TARGET)
+# error This file requires compute capability 7.0 or greater.
+#endif
+
+_CUDA_AWBARRIER_STATIC_QUALIFIER __host__
+uint32_t __mbarrier_maximum_count() {
+    return _CUDA_AWBARRIER_MAX_COUNT;
+}
+
+_CUDA_AWBARRIER_STATIC_QUALIFIER
+void __mbarrier_init(__mbarrier_t* barrier, uint32_t expected_count) {
+    _CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_init(barrier, expected_count);
+}
+
+_CUDA_AWBARRIER_STATIC_QUALIFIER
+void __mbarrier_inval(__mbarrier_t* barrier) {
+    _CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_inval(barrier);
+}
+
+_CUDA_AWBARRIER_STATIC_QUALIFIER
+__mbarrier_token_t __mbarrier_arrive(__mbarrier_t* barrier) {
+    return _CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_arrive_drop<false>(barrier);
+}
+
+_CUDA_AWBARRIER_STATIC_QUALIFIER
+__mbarrier_token_t __mbarrier_arrive_and_drop(__mbarrier_t* barrier) {
+    return _CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_arrive_drop<true>(barrier);
+}
+
+_CUDA_AWBARRIER_STATIC_QUALIFIER
+bool __mbarrier_test_wait(__mbarrier_t* barrier, __mbarrier_token_t token) {
+    return _CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_test_wait(barrier, token);
+}
+
+_CUDA_AWBARRIER_STATIC_QUALIFIER
+uint32_t __mbarrier_token_pending_count(__mbarrier_token_t token) {
+    return _CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_token_pending_count(token);
+}
+
+_CUDA_AWBARRIER_STATIC_QUALIFIER
+bool __mbarrier_test_wait_parity(__mbarrier_t* barrier, bool phase_parity) {
+   return _CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_test_wait_parity(barrier, phase_parity);
+}
+
+_CUDA_AWBARRIER_STATIC_QUALIFIER
+bool __mbarrier_try_wait(__mbarrier_t* barrier, __mbarrier_token_t token, uint32_t max_sleep_nanosec) {
+   return _CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_try_wait(barrier, token, max_sleep_nanosec);
+}
+
+_CUDA_AWBARRIER_STATIC_QUALIFIER
+bool __mbarrier_try_wait_parity(__mbarrier_t* barrier, bool phase_parity, uint32_t max_sleep_nanosec) {
+   return _CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_try_wait_parity(barrier, phase_parity, max_sleep_nanosec);
+}
+
+#endif /* !_CUDA_AWBARRIER_PRIMITIVES_H_ */

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cuda_egl_interop.h

@@ -0,0 +1,642 @@
+/*
+ * Copyright 1993-2019 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__CUDA_EGL_INTEROP_H__)
+#define __CUDA_EGL_INTEROP_H__
+
+#include "cuda_runtime_api.h"
+#include "cuda_runtime.h"
+#include "cudart_platform.h"
+#include "EGL/egl.h"
+#include "EGL/eglext.h"
+
+#if defined(__cplusplus)
+extern "C" {
+#endif /* __cplusplus */
+
+/**
+ * \addtogroup CUDART_TYPES
+ * @{
+ */
+
+ /**
+ * Maximum number of planes per frame
+ */
+#define CUDA_EGL_MAX_PLANES 3
+
+/**
+ * CUDA EglFrame type - array or pointer
+ */
+typedef enum cudaEglFrameType_enum
+{
+    cudaEglFrameTypeArray = 0,  /**< Frame type CUDA array */
+    cudaEglFrameTypePitch = 1,  /**< Frame type CUDA pointer */
+} cudaEglFrameType;
+
+/**
+ * Resource location flags- sysmem or vidmem
+ *
+ * For CUDA context on iGPU, since video and system memory are equivalent -
+ * these flags will not have an effect on the execution.
+ *
+ * For CUDA context on dGPU, applications can use the flag ::cudaEglResourceLocationFlags
+ * to give a hint about the desired location.
+ *
+ * ::cudaEglResourceLocationSysmem - the frame data is made resident on the system memory
+ * to be accessed by CUDA.
+ *
+ * ::cudaEglResourceLocationVidmem - the frame data is made resident on the dedicated
+ * video memory to be accessed by CUDA.
+ *
+ * There may be an additional latency due to new allocation and data migration,
+ * if the frame is produced on a different memory.
+ */
+typedef enum cudaEglResourceLocationFlags_enum {
+    cudaEglResourceLocationSysmem   = 0x00,       /**< Resource location sysmem */
+    cudaEglResourceLocationVidmem   = 0x01,       /**< Resource location vidmem */
+} cudaEglResourceLocationFlags;
+
+/**
+ * CUDA EGL Color Format - The different planar and multiplanar formats currently supported for CUDA_EGL interops.
+ */
+typedef enum cudaEglColorFormat_enum {
+    cudaEglColorFormatYUV420Planar            = 0,  /**< Y, U, V in three surfaces, each in a separate surface, U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatYUV420SemiPlanar        = 1,  /**< Y, UV in two surfaces (UV as one surface) with VU byte ordering, width, height ratio same as YUV420Planar. */
+    cudaEglColorFormatYUV422Planar            = 2,  /**< Y, U, V  each in a separate  surface, U/V width = 1/2 Y width, U/V height = Y height. */
+    cudaEglColorFormatYUV422SemiPlanar        = 3,  /**< Y, UV in two surfaces with VU byte ordering, width, height ratio same as YUV422Planar. */
+    cudaEglColorFormatARGB                    = 6,  /**< R/G/B/A four channels in one surface with BGRA byte ordering. */
+    cudaEglColorFormatRGBA                    = 7,  /**< R/G/B/A four channels in one surface with ABGR byte ordering. */
+    cudaEglColorFormatL                       = 8,  /**< single luminance channel in one surface. */
+    cudaEglColorFormatR                       = 9,  /**< single color channel in one surface. */
+    cudaEglColorFormatYUV444Planar            = 10, /**< Y, U, V in three surfaces, each in a separate surface, U/V width = Y width, U/V height = Y height. */
+    cudaEglColorFormatYUV444SemiPlanar        = 11, /**< Y, UV in two surfaces (UV as one surface) with VU byte ordering, width, height ratio same as YUV444Planar. */
+    cudaEglColorFormatYUYV422                 = 12, /**< Y, U, V in one surface, interleaved as UYVY in one channel. */
+    cudaEglColorFormatUYVY422                 = 13, /**< Y, U, V in one surface, interleaved as YUYV in one channel. */
+    cudaEglColorFormatABGR                    = 14, /**< R/G/B/A four channels in one surface with RGBA byte ordering. */
+    cudaEglColorFormatBGRA                    = 15, /**< R/G/B/A four channels in one surface with ARGB byte ordering. */
+    cudaEglColorFormatA                       = 16, /**< Alpha color format - one channel in one surface. */
+    cudaEglColorFormatRG                      = 17, /**< R/G color format - two channels in one surface with GR byte ordering */
+    cudaEglColorFormatAYUV                    = 18, /**< Y, U, V, A four channels in one surface, interleaved as VUYA. */
+    cudaEglColorFormatYVU444SemiPlanar        = 19, /**< Y, VU in two surfaces (VU as one surface) with UV byte ordering, U/V width = Y width, U/V height = Y height. */
+    cudaEglColorFormatYVU422SemiPlanar        = 20, /**< Y, VU in two surfaces (VU as one surface) with UV byte ordering, U/V width = 1/2 Y width, U/V height = Y height. */
+    cudaEglColorFormatYVU420SemiPlanar        = 21, /**< Y, VU in two surfaces (VU as one surface) with UV byte ordering, U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatY10V10U10_444SemiPlanar = 22, /**< Y10, V10U10 in two surfaces (VU as one surface) with UV byte ordering, U/V width = Y width, U/V height = Y height. */
+    cudaEglColorFormatY10V10U10_420SemiPlanar = 23, /**< Y10, V10U10 in two surfaces (VU as one surface) with UV byte ordering, U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatY12V12U12_444SemiPlanar = 24, /**< Y12, V12U12 in two surfaces (VU as one surface) with UV byte ordering, U/V width = Y width, U/V height = Y height. */
+    cudaEglColorFormatY12V12U12_420SemiPlanar = 25, /**< Y12, V12U12 in two surfaces (VU as one surface) with UV byte ordering, U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatVYUY_ER                 = 26, /**< Extended Range Y, U, V in one surface, interleaved as YVYU in one channel. */
+    cudaEglColorFormatUYVY_ER                 = 27, /**< Extended Range Y, U, V in one surface, interleaved as YUYV in one channel. */
+    cudaEglColorFormatYUYV_ER                 = 28, /**< Extended Range Y, U, V in one surface, interleaved as UYVY in one channel. */
+    cudaEglColorFormatYVYU_ER                 = 29, /**< Extended Range Y, U, V in one surface, interleaved as VYUY in one channel. */
+    cudaEglColorFormatYUVA_ER                 = 31, /**< Extended Range Y, U, V, A four channels in one surface, interleaved as AVUY. */
+    cudaEglColorFormatAYUV_ER                 = 32, /**< Extended Range Y, U, V, A four channels in one surface, interleaved as VUYA. */
+    cudaEglColorFormatYUV444Planar_ER         = 33, /**< Extended Range Y, U, V in three surfaces, U/V width = Y width, U/V height = Y height. */
+    cudaEglColorFormatYUV422Planar_ER         = 34, /**< Extended Range Y, U, V in three surfaces, U/V width = 1/2 Y width, U/V height = Y height. */
+    cudaEglColorFormatYUV420Planar_ER         = 35, /**< Extended Range Y, U, V in three surfaces, U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatYUV444SemiPlanar_ER     = 36, /**< Extended Range Y, UV in two surfaces (UV as one surface) with VU byte ordering, U/V width = Y width, U/V height = Y height. */
+    cudaEglColorFormatYUV422SemiPlanar_ER     = 37, /**< Extended Range Y, UV in two surfaces (UV as one surface) with VU byte ordering, U/V width = 1/2 Y width, U/V height = Y height. */
+    cudaEglColorFormatYUV420SemiPlanar_ER     = 38, /**< Extended Range Y, UV in two surfaces (UV as one surface) with VU byte ordering, U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatYVU444Planar_ER         = 39, /**< Extended Range Y, V, U in three surfaces, U/V width = Y width, U/V height = Y height. */
+    cudaEglColorFormatYVU422Planar_ER         = 40, /**< Extended Range Y, V, U in three surfaces, U/V width = 1/2 Y width, U/V height = Y height. */
+    cudaEglColorFormatYVU420Planar_ER         = 41, /**< Extended Range Y, V, U in three surfaces, U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatYVU444SemiPlanar_ER     = 42, /**< Extended Range Y, VU in two surfaces (VU as one surface) with UV byte ordering, U/V width = Y width, U/V height = Y height. */
+    cudaEglColorFormatYVU422SemiPlanar_ER     = 43, /**< Extended Range Y, VU in two surfaces (VU as one surface) with UV byte ordering, U/V width = 1/2 Y width, U/V height = Y height. */
+    cudaEglColorFormatYVU420SemiPlanar_ER     = 44, /**< Extended Range Y, VU in two surfaces (VU as one surface) with UV byte ordering, U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatBayerRGGB               = 45, /**< Bayer format - one channel in one surface with interleaved RGGB ordering. */
+    cudaEglColorFormatBayerBGGR               = 46, /**< Bayer format - one channel in one surface with interleaved BGGR ordering. */
+    cudaEglColorFormatBayerGRBG               = 47, /**< Bayer format - one channel in one surface with interleaved GRBG ordering. */
+    cudaEglColorFormatBayerGBRG               = 48, /**< Bayer format - one channel in one surface with interleaved GBRG ordering. */
+    cudaEglColorFormatBayer10RGGB             = 49, /**< Bayer10 format - one channel in one surface with interleaved RGGB ordering. Out of 16 bits, 10 bits used 6 bits No-op. */
+    cudaEglColorFormatBayer10BGGR             = 50, /**< Bayer10 format - one channel in one surface with interleaved BGGR ordering. Out of 16 bits, 10 bits used 6 bits No-op. */
+    cudaEglColorFormatBayer10GRBG             = 51, /**< Bayer10 format - one channel in one surface with interleaved GRBG ordering. Out of 16 bits, 10 bits used 6 bits No-op. */
+    cudaEglColorFormatBayer10GBRG             = 52, /**< Bayer10 format - one channel in one surface with interleaved GBRG ordering. Out of 16 bits, 10 bits used 6 bits No-op. */
+    cudaEglColorFormatBayer12RGGB             = 53, /**< Bayer12 format - one channel in one surface with interleaved RGGB ordering. Out of 16 bits, 12 bits used 4 bits No-op. */
+    cudaEglColorFormatBayer12BGGR             = 54, /**< Bayer12 format - one channel in one surface with interleaved BGGR ordering. Out of 16 bits, 12 bits used 4 bits No-op. */
+    cudaEglColorFormatBayer12GRBG             = 55, /**< Bayer12 format - one channel in one surface with interleaved GRBG ordering. Out of 16 bits, 12 bits used 4 bits No-op. */
+    cudaEglColorFormatBayer12GBRG             = 56, /**< Bayer12 format - one channel in one surface with interleaved GBRG ordering. Out of 16 bits, 12 bits used 4 bits No-op. */
+    cudaEglColorFormatBayer14RGGB             = 57, /**< Bayer14 format - one channel in one surface with interleaved RGGB ordering. Out of 16 bits, 14 bits used 2 bits No-op. */
+    cudaEglColorFormatBayer14BGGR             = 58, /**< Bayer14 format - one channel in one surface with interleaved BGGR ordering. Out of 16 bits, 14 bits used 2 bits No-op. */
+    cudaEglColorFormatBayer14GRBG             = 59, /**< Bayer14 format - one channel in one surface with interleaved GRBG ordering. Out of 16 bits, 14 bits used 2 bits No-op. */
+    cudaEglColorFormatBayer14GBRG             = 60, /**< Bayer14 format - one channel in one surface with interleaved GBRG ordering. Out of 16 bits, 14 bits used 2 bits No-op. */
+    cudaEglColorFormatBayer20RGGB             = 61, /**< Bayer20 format - one channel in one surface with interleaved RGGB ordering. Out of 32 bits, 20 bits used 12 bits No-op. */
+    cudaEglColorFormatBayer20BGGR             = 62, /**< Bayer20 format - one channel in one surface with interleaved BGGR ordering. Out of 32 bits, 20 bits used 12 bits No-op. */
+    cudaEglColorFormatBayer20GRBG             = 63, /**< Bayer20 format - one channel in one surface with interleaved GRBG ordering. Out of 32 bits, 20 bits used 12 bits No-op. */
+    cudaEglColorFormatBayer20GBRG             = 64, /**< Bayer20 format - one channel in one surface with interleaved GBRG ordering. Out of 32 bits, 20 bits used 12 bits No-op. */
+    cudaEglColorFormatYVU444Planar            = 65, /**< Y, V, U in three surfaces, each in a separate surface, U/V width = Y width, U/V height = Y height. */
+    cudaEglColorFormatYVU422Planar            = 66, /**< Y, V, U in three surfaces, each in a separate surface, U/V width = 1/2 Y width, U/V height = Y height. */
+    cudaEglColorFormatYVU420Planar            = 67, /**< Y, V, U in three surfaces, each in a separate surface, U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatBayerIspRGGB            = 68, /**< Nvidia proprietary Bayer ISP format - one channel in one surface with interleaved RGGB ordering and mapped to opaque integer datatype. */
+    cudaEglColorFormatBayerIspBGGR            = 69, /**< Nvidia proprietary Bayer ISP format - one channel in one surface with interleaved BGGR ordering and mapped to opaque integer datatype. */
+    cudaEglColorFormatBayerIspGRBG            = 70, /**< Nvidia proprietary Bayer ISP format - one channel in one surface with interleaved GRBG ordering and mapped to opaque integer datatype. */
+    cudaEglColorFormatBayerIspGBRG            = 71, /**< Nvidia proprietary Bayer ISP format - one channel in one surface with interleaved GBRG ordering and mapped to opaque integer datatype. */
+    cudaEglColorFormatBayerBCCR               = 72, /**< Bayer format - one channel in one surface with interleaved BCCR ordering. */
+    cudaEglColorFormatBayerRCCB               = 73, /**< Bayer format - one channel in one surface with interleaved RCCB ordering. */
+    cudaEglColorFormatBayerCRBC               = 74, /**< Bayer format - one channel in one surface with interleaved CRBC ordering. */
+    cudaEglColorFormatBayerCBRC               = 75, /**< Bayer format - one channel in one surface with interleaved CBRC ordering. */
+    cudaEglColorFormatBayer10CCCC             = 76, /**< Bayer10 format - one channel in one surface with interleaved CCCC ordering. Out of 16 bits, 10 bits used 6 bits No-op. */
+    cudaEglColorFormatBayer12BCCR             = 77, /**< Bayer12 format - one channel in one surface with interleaved BCCR ordering. Out of 16 bits, 12 bits used 4 bits No-op. */
+    cudaEglColorFormatBayer12RCCB             = 78, /**< Bayer12 format - one channel in one surface with interleaved RCCB ordering. Out of 16 bits, 12 bits used 4 bits No-op. */
+    cudaEglColorFormatBayer12CRBC             = 79, /**< Bayer12 format - one channel in one surface with interleaved CRBC ordering. Out of 16 bits, 12 bits used 4 bits No-op. */
+    cudaEglColorFormatBayer12CBRC             = 80, /**< Bayer12 format - one channel in one surface with interleaved CBRC ordering. Out of 16 bits, 12 bits used 4 bits No-op. */
+    cudaEglColorFormatBayer12CCCC             = 81, /**< Bayer12 format - one channel in one surface with interleaved CCCC ordering. Out of 16 bits, 12 bits used 4 bits No-op. */
+    cudaEglColorFormatY                       = 82, /**< Color format for single Y plane. */
+    cudaEglColorFormatYUV420SemiPlanar_2020   = 83, /**< Y, UV in two surfaces (UV as one surface) U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatYVU420SemiPlanar_2020   = 84, /**< Y, VU in two surfaces (VU as one surface) U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatYUV420Planar_2020       = 85, /**< Y, U, V in three surfaces, each in a separate surface, U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatYVU420Planar_2020       = 86, /**< Y, V, U in three surfaces, each in a separate surface, U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatYUV420SemiPlanar_709    = 87, /**< Y, UV in two surfaces (UV as one surface) U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatYVU420SemiPlanar_709    = 88, /**< Y, VU in two surfaces (VU as one surface) U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatYUV420Planar_709        = 89, /**< Y, U, V in three surfaces, each in a separate surface, U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatYVU420Planar_709        = 90, /**< Y, V, U in three surfaces, each in a separate surface, U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatY10V10U10_420SemiPlanar_709  = 91, /**< Y10, V10U10 in two surfaces (VU as one surface) U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatY10V10U10_420SemiPlanar_2020 = 92, /**< Y10, V10U10 in two surfaces (VU as one surface) U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatY10V10U10_422SemiPlanar_2020 = 93, /**< Y10, V10U10  in two surfaces (VU as one surface) U/V width = 1/2 Y width, U/V height =  Y height. */
+    cudaEglColorFormatY10V10U10_422SemiPlanar      = 94, /**< Y10, V10U10  in two surfaces (VU as one surface) U/V width = 1/2 Y width, U/V height =  Y height. */
+    cudaEglColorFormatY10V10U10_422SemiPlanar_709  = 95, /**< Y10, V10U10  in two surfaces (VU as one surface) U/V width = 1/2 Y width, U/V height =  Y height. */
+    cudaEglColorFormatY_ER                         = 96, /**< Extended Range Color format for single Y plane. */
+    cudaEglColorFormatY_709_ER                     = 97, /**< Extended Range Color format for single Y plane. */
+    cudaEglColorFormatY10_ER                       = 98, /**< Extended Range Color format for single Y10 plane. */
+    cudaEglColorFormatY10_709_ER                   = 99, /**< Extended Range Color format for single Y10 plane. */
+    cudaEglColorFormatY12_ER                       = 100, /**< Extended Range Color format for single Y12 plane. */
+    cudaEglColorFormatY12_709_ER                   = 101, /**< Extended Range Color format for single Y12 plane. */
+    cudaEglColorFormatYUVA                         = 102, /**< Y, U, V, A four channels in one surface, interleaved as AVUY. */
+    cudaEglColorFormatYVYU                         = 104, /**< Y, U, V in one surface, interleaved as YVYU in one channel. */
+    cudaEglColorFormatVYUY                         = 105, /**< Y, U, V in one surface, interleaved as VYUY in one channel. */
+    cudaEglColorFormatY10V10U10_420SemiPlanar_ER     = 106, /**< Extended Range Y10, V10U10 in two surfaces (VU as one surface) U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatY10V10U10_420SemiPlanar_709_ER = 107, /**< Extended Range Y10, V10U10 in two surfaces (VU as one surface) U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatY10V10U10_444SemiPlanar_ER     = 108, /**< Extended Range Y10, V10U10 in two surfaces (VU as one surface) U/V width = Y width, U/V height = Y height. */ 
+    cudaEglColorFormatY10V10U10_444SemiPlanar_709_ER = 109, /**< Extended Range Y10, V10U10 in two surfaces (VU as one surface) U/V width = Y width, U/V height = Y height. */
+    cudaEglColorFormatY12V12U12_420SemiPlanar_ER     = 110, /**< Extended Range Y12, V12U12 in two surfaces (VU as one surface) U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatY12V12U12_420SemiPlanar_709_ER = 111, /**< Extended Range Y12, V12U12 in two surfaces (VU as one surface) U/V width = 1/2 Y width, U/V height = 1/2 Y height. */
+    cudaEglColorFormatY12V12U12_444SemiPlanar_ER     = 112, /**< Extended Range Y12, V12U12 in two surfaces (VU as one surface) U/V width = Y width, U/V height = Y height. */
+    cudaEglColorFormatY12V12U12_444SemiPlanar_709_ER = 113, /**< Extended Range Y12, V12U12 in two surfaces (VU as one surface) U/V width = Y width, U/V height = Y height. */
+} cudaEglColorFormat;
+
+/**
+ * CUDA EGL Plane Descriptor - structure defining each plane of a CUDA EGLFrame
+ */
+typedef struct cudaEglPlaneDesc_st {
+    unsigned int width;                         /**< Width of plane */
+    unsigned int height;                        /**< Height of plane */
+    unsigned int depth;                         /**< Depth of plane */
+    unsigned int pitch;                         /**< Pitch of plane */
+    unsigned int numChannels;                   /**< Number of channels for the plane */
+    struct cudaChannelFormatDesc channelDesc;   /**< Channel Format Descriptor */
+    unsigned int reserved[4];                   /**< Reserved for future use */
+} cudaEglPlaneDesc;
+
+/**
+ * CUDA EGLFrame Descriptor - structure defining one frame of EGL.
+ *
+ * Each frame may contain one or more planes depending on whether the surface is Multiplanar or not.
+ * Each plane of EGLFrame is represented by ::cudaEglPlaneDesc which is defined as:
+ * \code
+ * typedef struct cudaEglPlaneDesc_st {
+ *     unsigned int width;
+ *     unsigned int height;
+ *     unsigned int depth;
+ *     unsigned int pitch;
+ *     unsigned int numChannels;
+ *     struct cudaChannelFormatDesc channelDesc;
+ *     unsigned int reserved[4];
+ * } cudaEglPlaneDesc;
+ * \endcode
+
+*/
+typedef struct cudaEglFrame_st {
+   union {
+       cudaArray_t            pArray[CUDA_EGL_MAX_PLANES];     /**< Array of CUDA arrays corresponding to each plane*/
+       struct cudaPitchedPtr  pPitch[CUDA_EGL_MAX_PLANES];     /**< Array of Pointers corresponding to each plane*/
+   } frame;
+   cudaEglPlaneDesc planeDesc[CUDA_EGL_MAX_PLANES];     /**< CUDA EGL Plane Descriptor ::cudaEglPlaneDesc*/
+   unsigned int planeCount;                             /**< Number of planes */
+   cudaEglFrameType frameType;                          /**< Array or Pitch */
+   cudaEglColorFormat eglColorFormat;                   /**< CUDA EGL Color Format*/
+} cudaEglFrame;
+
+/**
+ * CUDA EGLSream Connection
+ */
+typedef struct  CUeglStreamConnection_st *cudaEglStreamConnection;
+
+/** @} */ /* END CUDART_TYPES */
+
+/**
+ * \addtogroup CUDART_EGL EGL Interoperability
+ * This section describes the EGL interoperability functions of the CUDA
+ * runtime application programming interface.
+ *
+ * @{
+ */
+
+/**
+ * \brief Registers an EGL image
+ *
+ * Registers the EGLImageKHR specified by \p image for access by
+ * CUDA. A handle to the registered object is returned as \p pCudaResource.
+ * Additional Mapping/Unmapping is not required for the registered resource and
+ * ::cudaGraphicsResourceGetMappedEglFrame can be directly called on the \p pCudaResource.
+ *
+ * The application will be responsible for synchronizing access to shared objects.
+ * The application must ensure that any pending operation which access the objects have completed
+ * before passing control to CUDA. This may be accomplished by issuing and waiting for
+ * glFinish command on all GLcontexts (for OpenGL and likewise for other APIs).
+ * The application will be also responsible for ensuring that any pending operation on the
+ * registered CUDA resource has completed prior to executing subsequent commands in other APIs
+ * accesing the same memory objects.
+ * This can be accomplished by calling cuCtxSynchronize or cuEventSynchronize (preferably).
+ *
+ * The surface's intended usage is specified using \p flags, as follows:
+ *
+ * - ::cudaGraphicsRegisterFlagsNone: Specifies no hints about how this
+ *   resource will be used. It is therefore assumed that this resource will be
+ *   read from and written to by CUDA. This is the default value.
+ * - ::cudaGraphicsRegisterFlagsReadOnly: Specifies that CUDA
+ *   will not write to this resource.
+ * - ::cudaGraphicsRegisterFlagsWriteDiscard: Specifies that
+ *   CUDA will not read from this resource and will write over the
+ *   entire contents of the resource, so none of the data previously
+ *   stored in the resource will be preserved.
+ *
+ * The EGLImageKHR is an object which can be used to create EGLImage target resource. It is defined as a void pointer.
+ * typedef void* EGLImageKHR
+ *
+ * \param pCudaResource   - Pointer to the returned object handle
+ * \param image           - An EGLImageKHR image which can be used to create target resource.
+ * \param flags           - Map flags
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidResourceHandle,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorUnknown
+ *
+ * \sa
+ * ::cudaGraphicsUnregisterResource,
+ * ::cudaGraphicsResourceGetMappedEglFrame,
+ * ::cuGraphicsEGLRegisterImage
+ */
+extern __host__ cudaError_t CUDARTAPI cudaGraphicsEGLRegisterImage(struct cudaGraphicsResource **pCudaResource, EGLImageKHR image, unsigned int flags);
+
+/**
+ * \brief Connect CUDA to EGLStream as a consumer.
+ *
+ * Connect CUDA as a consumer to EGLStreamKHR specified by \p eglStream.
+ *
+ * The EGLStreamKHR is an EGL object that transfers a sequence of image frames from one
+ * API to another.
+ *
+ * \param conn              - Pointer to the returned connection handle
+ * \param eglStream         - EGLStreamKHR handle
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorUnknown
+ *
+ * \sa
+ * ::cudaEGLStreamConsumerDisconnect,
+ * ::cudaEGLStreamConsumerAcquireFrame,
+ * ::cudaEGLStreamConsumerReleaseFrame,
+ * ::cuEGLStreamConsumerConnect
+ */
+extern __host__ cudaError_t CUDARTAPI cudaEGLStreamConsumerConnect(cudaEglStreamConnection *conn, EGLStreamKHR eglStream);
+
+/**
+ * \brief Connect CUDA to EGLStream as a consumer with given flags.
+ *
+ * Connect CUDA as a consumer to EGLStreamKHR specified by \p stream with specified \p flags defined by
+ * ::cudaEglResourceLocationFlags.
+ *
+ * The flags specify whether the consumer wants to access frames from system memory or video memory.
+ * Default is ::cudaEglResourceLocationVidmem.
+ *
+ * \param conn              - Pointer to the returned connection handle
+ * \param eglStream         - EGLStreamKHR handle
+ * \param flags             - Flags denote intended location - system or video.
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorUnknown
+ *
+ * \sa
+ * ::cudaEGLStreamConsumerDisconnect,
+ * ::cudaEGLStreamConsumerAcquireFrame,
+ * ::cudaEGLStreamConsumerReleaseFrame,
+ * ::cuEGLStreamConsumerConnectWithFlags
+ */
+extern __host__ cudaError_t CUDARTAPI cudaEGLStreamConsumerConnectWithFlags(cudaEglStreamConnection *conn, EGLStreamKHR eglStream, unsigned int flags);
+
+/**
+ * \brief Disconnect CUDA as a consumer to EGLStream .
+ *
+ * Disconnect CUDA as a consumer to EGLStreamKHR.
+ *
+ * \param conn            - Conection to disconnect.
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorUnknown
+ *
+ * \sa
+ * ::cudaEGLStreamConsumerConnect,
+ * ::cudaEGLStreamConsumerAcquireFrame,
+ * ::cudaEGLStreamConsumerReleaseFrame,
+ * ::cuEGLStreamConsumerDisconnect
+ */
+extern __host__ cudaError_t CUDARTAPI cudaEGLStreamConsumerDisconnect(cudaEglStreamConnection *conn);
+
+/**
+ * \brief Acquire an image frame from the EGLStream with CUDA as a consumer.
+ *
+ * Acquire an image frame from EGLStreamKHR.
+ * ::cudaGraphicsResourceGetMappedEglFrame can be called on \p pCudaResource to get
+ * ::cudaEglFrame.
+ *
+ * \param conn            - Connection on which to acquire
+ * \param pCudaResource   - CUDA resource on which the EGLStream frame will be mapped for use.
+ * \param pStream         - CUDA stream for synchronization and any data migrations
+ * implied by ::cudaEglResourceLocationFlags.
+ * \param timeout         - Desired timeout in usec.
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorUnknown,
+ * ::cudaErrorLaunchTimeout
+ *
+ * \sa
+ * ::cudaEGLStreamConsumerConnect,
+ * ::cudaEGLStreamConsumerDisconnect,
+ * ::cudaEGLStreamConsumerReleaseFrame,
+ * ::cuEGLStreamConsumerAcquireFrame
+ */
+
+extern __host__ cudaError_t CUDARTAPI cudaEGLStreamConsumerAcquireFrame(cudaEglStreamConnection *conn,
+        cudaGraphicsResource_t *pCudaResource, cudaStream_t *pStream, unsigned int timeout);
+/**
+ * \brief Releases the last frame acquired from the EGLStream.
+ *
+ * Release the acquired image frame specified by \p pCudaResource to EGLStreamKHR.
+ *
+ * \param conn            - Connection on which to release
+ * \param pCudaResource   - CUDA resource whose corresponding frame is to be released
+ * \param pStream         - CUDA stream on which release will be done.
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorUnknown
+ *
+ * \sa
+ * ::cudaEGLStreamConsumerConnect,
+ * ::cudaEGLStreamConsumerDisconnect,
+ * ::cudaEGLStreamConsumerAcquireFrame,
+ * ::cuEGLStreamConsumerReleaseFrame
+ */
+extern __host__ cudaError_t CUDARTAPI cudaEGLStreamConsumerReleaseFrame(cudaEglStreamConnection *conn,
+                                                  cudaGraphicsResource_t pCudaResource, cudaStream_t *pStream);
+
+/**
+ * \brief Connect CUDA to EGLStream as a producer.
+ *
+ * Connect CUDA as a producer to EGLStreamKHR specified by \p stream.
+ *
+ * The EGLStreamKHR is an EGL object that transfers a sequence of image frames from one
+ * API to another.
+ *
+ * \param conn   - Pointer to the returned connection handle
+ * \param eglStream - EGLStreamKHR handle
+ * \param width  - width of the image to be submitted to the stream
+ * \param height - height of the image to be submitted to the stream
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorUnknown
+ *
+ * \sa
+ * ::cudaEGLStreamProducerDisconnect,
+ * ::cudaEGLStreamProducerPresentFrame,
+ * ::cudaEGLStreamProducerReturnFrame,
+ * ::cuEGLStreamProducerConnect
+ */
+extern __host__ cudaError_t CUDARTAPI cudaEGLStreamProducerConnect(cudaEglStreamConnection *conn,
+                                                EGLStreamKHR eglStream, EGLint width, EGLint height);
+
+/**
+ * \brief Disconnect CUDA as a producer  to EGLStream .
+ *
+ * Disconnect CUDA as a producer to EGLStreamKHR.
+ *
+ * \param conn            - Conection to disconnect.
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorUnknown
+ *
+ * \sa
+ * ::cudaEGLStreamProducerConnect,
+ * ::cudaEGLStreamProducerPresentFrame,
+ * ::cudaEGLStreamProducerReturnFrame,
+ * ::cuEGLStreamProducerDisconnect
+ */
+extern __host__ cudaError_t CUDARTAPI cudaEGLStreamProducerDisconnect(cudaEglStreamConnection *conn);
+
+/**
+ * \brief Present a CUDA eglFrame to the EGLStream with CUDA as a producer.
+ *
+ * The ::cudaEglFrame is defined as:
+ * \code
+ * typedef struct cudaEglFrame_st {
+ *     union {
+ *         cudaArray_t            pArray[CUDA_EGL_MAX_PLANES];
+ *         struct cudaPitchedPtr  pPitch[CUDA_EGL_MAX_PLANES];
+ *     } frame;
+ *     cudaEglPlaneDesc planeDesc[CUDA_EGL_MAX_PLANES];
+ *     unsigned int planeCount;
+ *     cudaEglFrameType frameType;
+ *     cudaEglColorFormat eglColorFormat;
+ * } cudaEglFrame;
+ * \endcode
+ *
+ * For ::cudaEglFrame of type ::cudaEglFrameTypePitch, the application may present sub-region of a memory
+ * allocation. In that case, ::cudaPitchedPtr::ptr will specify the start address of the sub-region in
+ * the allocation and ::cudaEglPlaneDesc will specify the dimensions of the sub-region.
+ *
+ * \param conn            - Connection on which to present the CUDA array
+ * \param eglframe        - CUDA Eglstream Proucer Frame handle to be sent to the consumer over EglStream.
+ * \param pStream         - CUDA stream on which to present the frame.
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorUnknown
+ *
+ * \sa
+ * ::cudaEGLStreamProducerConnect,
+ * ::cudaEGLStreamProducerDisconnect,
+ * ::cudaEGLStreamProducerReturnFrame,
+ * ::cuEGLStreamProducerPresentFrame
+ */
+extern __host__ cudaError_t CUDARTAPI cudaEGLStreamProducerPresentFrame(cudaEglStreamConnection *conn,
+                                                 cudaEglFrame eglframe, cudaStream_t *pStream);
+
+/**
+ * \brief Return the CUDA eglFrame to the EGLStream last released by the consumer.
+ * 
+ * This API can potentially return cudaErrorLaunchTimeout if the consumer has not 
+ * returned a frame to EGL stream. If timeout is returned the application can retry.
+ *
+ * \param conn            - Connection on which to present the CUDA array
+ * \param eglframe        - CUDA Eglstream Proucer Frame handle returned from the consumer over EglStream.
+ * \param pStream         - CUDA stream on which to return the frame.
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorLaunchTimeout,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorUnknown
+ *
+ * \sa
+ * ::cudaEGLStreamProducerConnect,
+ * ::cudaEGLStreamProducerDisconnect,
+ * ::cudaEGLStreamProducerPresentFrame,
+ * ::cuEGLStreamProducerReturnFrame
+ */
+extern __host__ cudaError_t CUDARTAPI cudaEGLStreamProducerReturnFrame(cudaEglStreamConnection *conn,
+                                                cudaEglFrame *eglframe, cudaStream_t *pStream);
+
+/**
+ * \brief Get an eglFrame through which to access a registered EGL graphics resource.
+ *
+ * Returns in \p *eglFrame an eglFrame pointer through which the registered graphics resource
+ * \p resource may be accessed.
+ * This API can only be called for EGL graphics resources.
+ *
+ * The ::cudaEglFrame is defined as
+ * \code
+ * typedef struct cudaEglFrame_st {
+ *     union {
+ *         cudaArray_t             pArray[CUDA_EGL_MAX_PLANES];
+ *         struct cudaPitchedPtr   pPitch[CUDA_EGL_MAX_PLANES];
+ *     } frame;
+ *     cudaEglPlaneDesc planeDesc[CUDA_EGL_MAX_PLANES];
+ *     unsigned int planeCount;
+ *     cudaEglFrameType frameType;
+ *     cudaEglColorFormat eglColorFormat;
+ * } cudaEglFrame;
+ * \endcode
+ *
+ *
+ * \param eglFrame   - Returned eglFrame.
+ * \param resource   - Registered resource to access.
+ * \param index      - Index for cubemap surfaces.
+ * \param mipLevel   - Mipmap level for the subresource to access.
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorUnknown
+ *
+ * \note Note that in case of multiplanar \p *eglFrame, pitch of only first plane (unsigned int cudaEglPlaneDesc::pitch) is to be considered by the application.
+ *
+ * \sa
+ * ::cudaGraphicsSubResourceGetMappedArray,
+ * ::cudaGraphicsResourceGetMappedPointer,
+ * ::cuGraphicsResourceGetMappedEglFrame
+ */
+extern __host__ cudaError_t CUDARTAPI cudaGraphicsResourceGetMappedEglFrame(cudaEglFrame* eglFrame,
+                                        cudaGraphicsResource_t resource, unsigned int index, unsigned int mipLevel);
+
+/**
+ * \brief Creates an event from EGLSync object
+ *
+ * Creates an event *phEvent from an EGLSyncKHR eglSync with the flages specified
+ * via \p flags. Valid flags include:
+ * - ::cudaEventDefault: Default event creation flag.
+ * - ::cudaEventBlockingSync: Specifies that the created event should use blocking
+ * synchronization.  A CPU thread that uses ::cudaEventSynchronize() to wait on
+ * an event created with this flag will block until the event has actually
+ * been completed.
+ *
+ * ::cudaEventRecord and TimingData are not supported for events created from EGLSync.
+ *
+ * The EGLSyncKHR is an opaque handle to an EGL sync object.
+ * typedef void* EGLSyncKHR
+ *
+ * \param phEvent - Returns newly created event
+ * \param eglSync - Opaque handle to EGLSync object
+ * \param flags   - Event creation flags
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInitializationError,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorLaunchFailure,
+ * ::cudaErrorMemoryAllocation
+ *
+ * \sa
+ * ::cudaEventQuery,
+ * ::cudaEventSynchronize,
+ * ::cudaEventDestroy
+ */
+extern __host__ cudaError_t CUDARTAPI cudaEventCreateFromEGLSync(cudaEvent_t *phEvent, EGLSyncKHR eglSync, unsigned int flags);
+
+/** @} */ /* END CUDART_EGL */
+
+#if defined(__cplusplus)
+}
+#endif /* __cplusplus */
+
+#endif /* __CUDA_EGL_INTEROP_H__ */
+

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cuda_fp8.hpp

@@ -0,0 +1,1546 @@
+/*
+ * Copyright 2022 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__CUDA_FP8_HPP__)
+#define __CUDA_FP8_HPP__
+
+#if !defined(__CUDA_FP8_H__)
+#error "Do not include this file directly. Instead, include cuda_fp8.h."
+#endif
+
+/* C++ header for std::memcpy (used for type punning in host-side
+ * implementations). When compiling as a CUDA source file memcpy is provided
+ * implicitly. !defined(__CUDACC__) implies !defined(__CUDACC_RTC__).
+ */
+#if defined(__cplusplus) && !defined(__CUDACC__)
+#include <cstring>
+#elif !defined(__cplusplus) && !defined(__CUDACC__)
+#include <string.h>
+#endif /* defined(__cplusplus) && !defined(__CUDACC__) */
+
+/* Set up structure-alignment attribute */
+#if !(defined __CUDA_ALIGN__)
+#if defined(__CUDACC__)
+#define __CUDA_ALIGN__(align) __align__(align)
+#else
+/* Define alignment macro based on compiler type (cannot assume C11 "_Alignas"
+ * is available) */
+#if __cplusplus >= 201103L
+#define __CUDA_ALIGN__(n)                                                      \
+    alignas(n) /* C++11 kindly gives us a keyword for this */
+#else          /* !defined(__CPP_VERSION_AT_LEAST_11_FP8)*/
+#if defined(__GNUC__)
+#define __CUDA_ALIGN__(n) __attribute__((aligned(n)))
+#elif defined(_MSC_VER)
+#define __CUDA_ALIGN__(n) __declspec(align(n))
+#else
+#define __CUDA_ALIGN__(n)
+#endif /* defined(__GNUC__) */
+#endif /* defined(__CPP_VERSION_AT_LEAST_11_FP8) */
+#endif /* defined(__CUDACC__) */
+#endif /* !(defined __CUDA_ALIGN__) */
+
+#if !(defined __CPP_VERSION_AT_LEAST_11_FP8)
+/* need c++11 for explicit operators */
+#define __CUDA_NO_FP8_CONVERSION_OPERATORS__
+#endif
+
+__CUDA_HOSTDEVICE_FP8_DECL__ __nv_fp8_storage_t
+__nv_cvt_double_to_fp8(const double x, const __nv_saturation_t saturate,
+                       const __nv_fp8_interpretation_t fp8_interpretation) {
+    unsigned char res;
+    unsigned long long int xbits;
+
+#if defined(__CUDACC__) || (!defined __cplusplus)
+    (void)memcpy(&xbits, &x, sizeof(x));
+#else
+    (void)std::memcpy(&xbits, &x, sizeof(x));
+#endif
+    unsigned char FP8_MAXNORM;
+    unsigned char FP8_MANTISSA_MASK;
+    unsigned short int FP8_EXP_BIAS;
+    unsigned long long int FP8_SIGNIFICAND_BITS;
+    const unsigned long long int DP_INF_BITS = 0x7FF0000000000000ULL;
+    unsigned long long int FP8_MINDENORM_O2;
+    unsigned long long int FP8_OVERFLOW_THRESHOLD;
+    unsigned long long int FP8_MINNORM;
+
+    if (fp8_interpretation == __NV_E4M3) {
+        FP8_EXP_BIAS = 7U;
+        FP8_SIGNIFICAND_BITS = 4ULL;
+        FP8_MANTISSA_MASK = 0x7U;
+        FP8_MINDENORM_O2 = 0x3F50000000000000ULL; // mindenorm/2 = 2^-10
+        FP8_OVERFLOW_THRESHOLD =
+            0x407D000000000000ULL; // maxnorm + 1/2ulp = 0x1.Cp+8 + 0x1p+4
+        FP8_MAXNORM = 0x7EU;
+        FP8_MINNORM = 0x3F90000000000000ULL; // minnorm = 2^-6
+    } else {                                 //__NV_E5M2
+        FP8_EXP_BIAS = 15U;
+        FP8_SIGNIFICAND_BITS = 3ULL;
+        FP8_MANTISSA_MASK = 0x3U;
+        FP8_MINDENORM_O2 = 0x3EE0000000000000ULL; // mindenorm/2 = 2^-17
+        FP8_OVERFLOW_THRESHOLD =
+            0x40EE000000000000ULL -
+            1ULL; // maxnorm + 1/2ulp = 0x1.Ep+15, and -1 to have common code
+        FP8_MAXNORM = 0x7BU;
+        FP8_MINNORM = 0x3F10000000000000ULL; // minnorm = 2^-14
+    }
+
+    // 1/2 LSB of the target format, positioned in double precision mantissa
+    // helpful in midpoints detection during round-to-nearest-even step
+    const unsigned long long int FP8_DP_HALF_ULP =
+        (unsigned long long int)1ULL << (53ULL - FP8_SIGNIFICAND_BITS - 1ULL);
+    // prepare sign bit in target format
+    unsigned char sign = (unsigned char)((xbits >> 63ULL) << 7U);
+    // prepare exponent field in target format
+    unsigned char exp =
+        (unsigned char)((((unsigned short int)(xbits >> 52ULL)) & 0x7FFU) -
+                        1023U + FP8_EXP_BIAS);
+    // round mantissa to target format width, rounding towards zero
+    unsigned char mantissa =
+        (unsigned char)(xbits >> (53ULL - FP8_SIGNIFICAND_BITS)) &
+        FP8_MANTISSA_MASK;
+    unsigned long long int absx = xbits & 0x7FFFFFFFFFFFFFFFULL;
+
+    if (absx <= FP8_MINDENORM_O2) {
+        // zero or underflow
+        res = 0U;
+    } else if (absx > DP_INF_BITS) {
+        // NaN
+        if (fp8_interpretation == __NV_E4M3) {
+            res = 0x7FU;
+        } else {
+            // NaN --> QNaN
+            res = 0x7EU | mantissa;
+        }
+    } else if (absx > FP8_OVERFLOW_THRESHOLD) {
+        if (saturate == __NV_SATFINITE) {
+            res = FP8_MAXNORM;
+        } else {
+            // __NV_NOSAT
+            if (fp8_interpretation == __NV_E4M3) {
+                // no Inf in E4M3
+                res = 0x7FU; // NaN
+            } else {
+                res = 0x7CU; // Inf in E5M2
+            }
+        }
+    } else if (absx >= FP8_MINNORM) {
+        res = (unsigned char)((exp << (FP8_SIGNIFICAND_BITS - 1U)) | mantissa);
+        // rounded-off bits
+        unsigned long long int round =
+            xbits & ((FP8_DP_HALF_ULP << 1ULL) - 1ULL);
+        // round-to-nearest-even adjustment
+        if ((round > FP8_DP_HALF_ULP) ||
+            ((round == FP8_DP_HALF_ULP) && (mantissa & 1U))) {
+            res = (unsigned char)(res + 1U);
+        }
+    } else // Denormal range
+    {
+        unsigned char shift = (unsigned char)(1U - exp);
+        // add implicit leading bit
+        mantissa |= (unsigned char)(1U << (FP8_SIGNIFICAND_BITS - 1U));
+        // additional round-off due to denormalization
+        res = (unsigned char)(mantissa >> shift);
+
+        // rounded-off bits, including implicit leading bit
+        unsigned long long int round =
+            (xbits | ((unsigned long long int)1ULL << (53ULL - 1ULL))) &
+            ((FP8_DP_HALF_ULP << (shift + 1ULL)) - 1ULL);
+        // round-to-nearest-even adjustment
+        if ((round > (FP8_DP_HALF_ULP << shift)) ||
+            ((round == (FP8_DP_HALF_ULP << shift)) && (res & 1U))) {
+            res = (unsigned char)(res + 1U);
+        }
+    }
+
+    res |= sign;
+
+    return (__nv_fp8_storage_t)res;
+}
+
+__CUDA_HOSTDEVICE_FP8_DECL__ __nv_fp8x2_storage_t
+__nv_cvt_double2_to_fp8x2(const double2 x, const __nv_saturation_t saturate,
+                          const __nv_fp8_interpretation_t fp8_interpretation) {
+    __nv_fp8x2_storage_t storage = (__nv_fp8x2_storage_t)__nv_cvt_double_to_fp8(
+        x.y, saturate, fp8_interpretation);
+    storage = (__nv_fp8x2_storage_t)(storage << 8U);
+    storage = (__nv_fp8x2_storage_t)(storage |
+                                     __nv_cvt_double_to_fp8(
+                                         x.x, saturate, fp8_interpretation));
+    return storage;
+}
+
+__CUDA_HOSTDEVICE_FP8_DECL__ __nv_fp8_storage_t
+__nv_cvt_float_to_fp8(const float x, const __nv_saturation_t saturate,
+                      const __nv_fp8_interpretation_t fp8_interpretation) {
+    __nv_fp8_storage_t res = 0U;
+#if (defined __CUDA_ARCH__) && (__CUDA_ARCH__ >= 890)
+    if (saturate == __NV_SATFINITE) {
+        __nv_fp8x2_storage_t storage;
+        if (fp8_interpretation == __NV_E5M2) {
+            asm("{cvt.rn.satfinite.e5m2x2.f32 %0, %2, %1;}\n"
+                : "=h"(storage)
+                : "f"(x), "f"(0.0f));
+        } else {
+            asm("{cvt.rn.satfinite.e4m3x2.f32 %0, %2, %1;}\n"
+                : "=h"(storage)
+                : "f"(x), "f"(0.0f));
+        }
+        res = (__nv_fp8_storage_t)storage;
+    } else
+#endif
+    {
+        unsigned int xbits;
+#if defined(__CUDACC__) || (!defined __cplusplus)
+        (void)memcpy(&xbits, &x, sizeof(x));
+#else
+        (void)std::memcpy(&xbits, &x, sizeof(x));
+#endif
+
+        // isnan
+        if ((xbits & 0x7FFFFFFFU) > 0x7F800000U) {
+            // Canonical NaN
+            xbits = 0x7FFFFFFFU;
+        }
+
+        float fx;
+#if defined(__CUDACC__) || (!defined __cplusplus)
+        (void)memcpy(&fx, &xbits, sizeof(xbits));
+#else
+        (void)std::memcpy(&fx, &xbits, sizeof(xbits));
+#endif
+
+        const double dx = (double)fx;
+        res = __nv_cvt_double_to_fp8(dx, saturate, fp8_interpretation);
+    }
+    return res;
+}
+
+__CUDA_HOSTDEVICE_FP8_DECL__ __nv_fp8x2_storage_t
+__nv_cvt_float2_to_fp8x2(const float2 x, const __nv_saturation_t saturate,
+                         const __nv_fp8_interpretation_t fp8_interpretation) {
+    __nv_fp8x2_storage_t storage;
+#if (defined __CUDA_ARCH__) && (__CUDA_ARCH__ >= 890)
+    if (saturate == __NV_SATFINITE) {
+        if (fp8_interpretation == __NV_E5M2) {
+            asm("{cvt.rn.satfinite.e5m2x2.f32 %0, %2, %1;}\n"
+                : "=h"(storage)
+                : "f"(x.x), "f"(x.y));
+        } else {
+            asm("{cvt.rn.satfinite.e4m3x2.f32 %0, %2, %1;}\n"
+                : "=h"(storage)
+                : "f"(x.x), "f"(x.y));
+        }
+    } else
+#endif
+    {
+        storage = (__nv_fp8x2_storage_t)__nv_cvt_float_to_fp8(
+            x.y, saturate, fp8_interpretation);
+        storage = (__nv_fp8x2_storage_t)(storage << 8U);
+        storage = (__nv_fp8x2_storage_t)(storage | __nv_cvt_float_to_fp8(
+                                                       x.x, saturate,
+                                                       fp8_interpretation));
+    }
+    return storage;
+}
+
+__CUDA_HOSTDEVICE_FP8_DECL__ float
+__internal_halfraw_to_float(const __half_raw x) {
+    float f;
+#if (defined __CUDA_ARCH__) && (__CUDA_ARCH__ >= 530)
+    asm("{cvt.f32.f16 %0, %1;}\n" : "=f"(f) : "h"(x.x));
+#else
+    const unsigned int ux = (unsigned int)x.x;
+    unsigned int sign = (ux >> 15U) & 1U;
+    unsigned int exponent = (ux >> 10U) & 0x1fU;
+    unsigned int mantissa = (ux & 0x3ffU) << 13U;
+    if (exponent == 0x1fU) { /* NaN or Inf */
+        /* discard sign of a NaN */
+        sign = ((mantissa != 0U) ? (sign >> 1U) : sign);
+        mantissa = ((mantissa != 0U) ? 0x7fffffU : 0U);
+        exponent = 0xffU;
+    } else if (exponent == 0U) { /* Denorm or Zero */
+        if (mantissa != 0U) {
+            unsigned int msb;
+            exponent = 0x71U;
+            do {
+                msb = (mantissa & 0x400000U);
+                mantissa <<= 1U; /* normalize */
+                --exponent;
+            } while (msb == 0U);
+            mantissa &= 0x7fffffU; /* 1.mantissa is implicit */
+        }
+    } else {
+        exponent += 0x70U;
+    }
+    const unsigned int u = ((sign << 31U) | (exponent << 23U) | mantissa);
+#if defined(__CUDACC__) || (!defined __cplusplus)
+    (void)memcpy(&f, &u, sizeof(u));
+#else
+    (void)std::memcpy(&f, &u, sizeof(u));
+#endif
+#endif /* (defined __CUDA_ARCH__) && (__CUDA_ARCH__ >= 530) */
+    return f;
+}
+
+__CUDA_HOSTDEVICE_FP8_DECL__ float2
+__internal_halfraw2_to_float2(const __half2_raw x) {
+    __half_raw raw;
+    float2 res;
+    raw.x = x.x;
+    res.x = __internal_halfraw_to_float(raw);
+    raw.x = x.y;
+    res.y = __internal_halfraw_to_float(raw);
+    return res;
+}
+
+__CUDA_HOSTDEVICE_FP8_DECL__ __nv_fp8_storage_t
+__nv_cvt_halfraw_to_fp8(const __half_raw x, const __nv_saturation_t saturate,
+                        const __nv_fp8_interpretation_t fp8_interpretation) {
+    __nv_fp8_storage_t res = 0U;
+#if (defined __CUDA_ARCH__) && (__CUDA_ARCH__ >= 890)
+    if (saturate == __NV_SATFINITE) {
+        unsigned int half2_storage = (unsigned int)(x.x);
+        __nv_fp8x2_storage_t tmp;
+        if (fp8_interpretation == __NV_E5M2) {
+            asm("{cvt.rn.satfinite.e5m2x2.f16x2 %0, %1;}\n"
+                : "=h"(tmp)
+                : "r"(half2_storage));
+        } else {
+            asm("{cvt.rn.satfinite.e4m3x2.f16x2 %0, %1;}\n"
+                : "=h"(tmp)
+                : "r"(half2_storage));
+        }
+        res = (__nv_fp8_storage_t)tmp;
+    } else
+#endif
+    {
+        float fx = __internal_halfraw_to_float(x);
+        res = __nv_cvt_float_to_fp8(fx, saturate, fp8_interpretation);
+    }
+    return res;
+}
+
+__CUDA_HOSTDEVICE_FP8_DECL__ __nv_fp8x2_storage_t __nv_cvt_halfraw2_to_fp8x2(
+    const __half2_raw x, const __nv_saturation_t saturate,
+    const __nv_fp8_interpretation_t fp8_interpretation) {
+    __nv_fp8x2_storage_t tmp;
+#if (defined __CUDA_ARCH__) && (__CUDA_ARCH__ >= 890)
+    if (saturate == __NV_SATFINITE) {
+        unsigned int half2_storage;
+        (void)memcpy(&half2_storage, &x, sizeof(x));
+
+        if (fp8_interpretation == __NV_E5M2) {
+            asm("{cvt.rn.satfinite.e5m2x2.f16x2 %0, %1;}\n"
+                : "=h"(tmp)
+                : "r"(half2_storage));
+        } else {
+            asm("{cvt.rn.satfinite.e4m3x2.f16x2 %0, %1;}\n"
+                : "=h"(tmp)
+                : "r"(half2_storage));
+        }
+    } else
+#endif
+    {
+        __half_raw raw;
+        raw.x = x.x;
+        __nv_fp8_storage_t lo =
+            __nv_cvt_halfraw_to_fp8(raw, saturate, fp8_interpretation);
+        raw.x = x.y;
+        __nv_fp8_storage_t hi =
+            __nv_cvt_halfraw_to_fp8(raw, saturate, fp8_interpretation);
+        tmp = hi;
+        tmp = (__nv_fp8x2_storage_t)(tmp << 8U);
+        tmp = (__nv_fp8x2_storage_t)(tmp | lo);
+    }
+    return tmp;
+}
+
+__CUDA_HOSTDEVICE_FP8_DECL__ float
+__internal_bf16raw_to_float(const __nv_bfloat16_raw x) {
+    const unsigned int ux = ((unsigned int)x.x) << 16U;
+    float fx;
+#if defined(__CUDACC__) || (!defined __cplusplus)
+    (void)memcpy(&fx, &ux, sizeof(ux));
+#else
+    (void)std::memcpy(&fx, &ux, sizeof(ux));
+#endif
+    return fx;
+}
+
+__CUDA_HOSTDEVICE_FP8_DECL__ __nv_bfloat16_raw
+__internal_float_to_bf16raw_rz(const float x) {
+    unsigned int ux;
+    __nv_bfloat16_raw r;
+#if defined(__CUDACC__) || (!defined __cplusplus)
+    (void)memcpy(&ux, &x, sizeof(x));
+#else
+    (void)std::memcpy(&ux, &x, sizeof(x));
+#endif
+    r.x = (unsigned short int)(ux >> 16U);
+    return r;
+}
+
+__CUDA_HOSTDEVICE_FP8_DECL__ __nv_fp8_storage_t __nv_cvt_bfloat16raw_to_fp8(
+    const __nv_bfloat16_raw x, const __nv_saturation_t saturate,
+    const __nv_fp8_interpretation_t fp8_interpretation) {
+    const float fx = __internal_bf16raw_to_float(x);
+    const __nv_fp8_storage_t res =
+        __nv_cvt_float_to_fp8(fx, saturate, fp8_interpretation);
+    return res;
+}
+
+__CUDA_HOSTDEVICE_FP8_DECL__ __nv_fp8x2_storage_t
+__nv_cvt_bfloat16raw2_to_fp8x2(
+    const __nv_bfloat162_raw x, const __nv_saturation_t saturate,
+    const __nv_fp8_interpretation_t fp8_interpretation) {
+    __nv_bfloat16_raw raw;
+    raw.x = x.y;
+    __nv_fp8x2_storage_t storage =
+        (__nv_fp8x2_storage_t)__nv_cvt_bfloat16raw_to_fp8(raw, saturate,
+                                                          fp8_interpretation);
+    storage = (__nv_fp8x2_storage_t)(storage << 8U);
+    raw.x = x.x;
+    storage = (__nv_fp8x2_storage_t)(storage |
+                                     __nv_cvt_bfloat16raw_to_fp8(
+                                         raw, saturate, fp8_interpretation));
+    return storage;
+}
+
+__CUDA_HOSTDEVICE_FP8_DECL__ __half2_raw
+__nv_cvt_fp8x2_to_halfraw2(const __nv_fp8x2_storage_t x,
+                           const __nv_fp8_interpretation_t fp8_interpretation);
+__CUDA_HOSTDEVICE_FP8_DECL__ __half_raw
+__nv_cvt_fp8_to_halfraw(const __nv_fp8_storage_t x,
+                        const __nv_fp8_interpretation_t fp8_interpretation) {
+    __half_raw res;
+    res.x = 0U;
+#if (defined __CUDA_ARCH__) && (__CUDA_ARCH__ >= 890)
+    res.x =
+        __nv_cvt_fp8x2_to_halfraw2((__nv_fp8x2_storage_t)x, fp8_interpretation)
+            .x;
+#else
+    unsigned short int ur = (unsigned short int)x;
+    ur = (unsigned short int)(ur << 8U);
+
+    if (fp8_interpretation == __NV_E5M2) {
+        if ((ur & 0x7FFFU) > 0x7C00U) {
+            /* If NaN, return canonical NaN */
+            ur = 0x7FFFU;
+        }
+    } else { // __NV_E4M3
+        unsigned short int sign = ur & 0x8000U;
+        unsigned short int exponent =
+            (unsigned short int)(((ur & 0x7800U) >> 1U) + 0x2000U);
+        unsigned short int mantissa = (ur & 0x0700U) >> 1U;
+        unsigned char absx = 0x7FU & (unsigned char)x;
+
+        if (absx == 0x7FU) // NaN
+        {
+            ur = 0x7FFFU; // fp16 canonical NaN, discard sign
+        } else if (exponent == 0x2000U) {
+            // zero or denormal
+            if (mantissa != 0U) {
+                // normalize
+                mantissa = (unsigned short int)(mantissa << 1U);
+                while ((mantissa & 0x0400U) == 0U) {
+                    mantissa = (unsigned short int)(mantissa << 1U);
+                    exponent = (unsigned short int)(exponent - 0x0400U);
+                }
+                // discard implicit leading bit
+                mantissa &= 0x03FFU;
+            } else { // Zero
+                exponent = 0U;
+            }
+
+            ur = (sign | exponent) | mantissa;
+        } else {
+            ur = (sign | exponent) | mantissa;
+        }
+    }
+    res.x = ur;
+#endif
+    return res;
+}
+
+__CUDA_HOSTDEVICE_FP8_DECL__ __half2_raw
+__nv_cvt_fp8x2_to_halfraw2(const __nv_fp8x2_storage_t x,
+                           const __nv_fp8_interpretation_t fp8_interpretation) {
+    __half2_raw res;
+#if (defined __CUDA_ARCH__) && (__CUDA_ARCH__ >= 890)
+    unsigned int half2_storage;
+    if (fp8_interpretation == __NV_E5M2) {
+        asm("{cvt.rn.f16x2.e5m2x2 %0, %1;}\n" : "=r"(half2_storage) : "h"(x));
+    } else {
+        asm("{cvt.rn.f16x2.e4m3x2 %0, %1;}\n" : "=r"(half2_storage) : "h"(x));
+    }
+    (void)memcpy(&res, &half2_storage, sizeof(half2_storage));
+#else
+    res.x =
+        __nv_cvt_fp8_to_halfraw((__nv_fp8_storage_t)x, fp8_interpretation).x;
+    res.y = __nv_cvt_fp8_to_halfraw((__nv_fp8_storage_t)(x >> 8U),
+                                    fp8_interpretation)
+                .x;
+#endif
+    return res;
+}
+
+/* All other definitions in this file are only visible to C++ compilers */
+#if defined(__cplusplus)
+
+/**
+ * \defgroup CUDA_MATH_FP8_E5M2_STRUCT C++ struct for handling fp8 data type of e5m2 kind.
+ * \ingroup CUDA_MATH_INTRINSIC_FP8
+ */
+
+/**
+ * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+ * \brief __nv_fp8_e5m2 datatype
+ *
+ * \details This structure implements the datatype for handling
+ * \p fp8 floating-point numbers of \p e5m2 kind:
+ * with 1 sign, 5 exponent, 1 implicit and 2 explicit mantissa bits.
+ *
+ * The structure implements converting constructors and operators.
+ */
+struct __CUDA_ALIGN__(1) __nv_fp8_e5m2 {
+  public:
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Storage variable contains the \p fp8 floating-point data.
+     */
+    __nv_fp8_storage_t __x;
+
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Constructor by default.
+     */
+#if defined(__CPP_VERSION_AT_LEAST_11_FP8)
+    __nv_fp8_e5m2() = default;
+#else
+    __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2() {}
+#endif /* defined(__CPP_VERSION_AT_LEAST_11_FP8) */
+
+#if !defined(__CUDA_NO_FP8_CONVERSIONS__)
+
+    /* Construct from wider FP types */
+    /* Note we do avoid constructor init-list because of special host/device
+     * compilation rules */
+
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Constructor from \p __half data type, relies on \p __NV_SATFINITE
+     * behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2(const __half f) {
+        __x = __nv_cvt_halfraw_to_fp8(static_cast<__half_raw>(f),
+                                      __NV_SATFINITE, __NV_E5M2);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Constructor from \p __nv_bfloat16 data type, relies on \p __NV_SATFINITE
+     * behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2(const __nv_bfloat16 f) {
+        __x = __nv_cvt_bfloat16raw_to_fp8(static_cast<__nv_bfloat16_raw>(f),
+                                          __NV_SATFINITE, __NV_E5M2);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Constructor from \p float data type, relies on \p __NV_SATFINITE behavior
+     * for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2(const float f) {
+        __x = __nv_cvt_float_to_fp8(f, __NV_SATFINITE, __NV_E5M2);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Constructor from \p double data type, relies on \p __NV_SATFINITE
+     * behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2(const double f) {
+        __x = __nv_cvt_double_to_fp8(f, __NV_SATFINITE, __NV_E5M2);
+    }
+
+    /* Converts from integral */
+
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Constructor from \p unsigned \p short \p int data type, relies on \p
+     * __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__
+    __nv_fp8_e5m2(const unsigned short int val) {
+        __x = static_cast<__nv_fp8_e5m2>(static_cast<float>(val)).__x;
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Constructor from \p unsigned \p int data type, relies on \p
+     * __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2(const unsigned int val) {
+        __x = static_cast<__nv_fp8_e5m2>(static_cast<float>(val)).__x;
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Constructor from \p unsigned \p long \p long \p int data type, relies on
+     * \p __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__
+    __nv_fp8_e5m2(const unsigned long long int val) {
+        __x = static_cast<__nv_fp8_e5m2>(static_cast<float>(val)).__x;
+    }
+
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Constructor from \p short \p int data type.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2(const short int val) {
+        __x = static_cast<__nv_fp8_e5m2>(static_cast<float>(val)).__x;
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Constructor from \p int data type, relies on \p __NV_SATFINITE behavior
+     * for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2(const int val) {
+        __x = static_cast<__nv_fp8_e5m2>(static_cast<float>(val)).__x;
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Constructor from \p long \p long \p int data type, relies on \p
+     * __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2(const long long int val) {
+        __x = static_cast<__nv_fp8_e5m2>(static_cast<float>(val)).__x;
+    }
+
+#if !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__)
+    /* Widening FP converts */
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Conversion operator to \p __half data type.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator __half() const {
+        return static_cast<__half>(__nv_cvt_fp8_to_halfraw(__x, __NV_E5M2));
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Conversion operator to \p float data type.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator float() const {
+        return __internal_halfraw_to_float(
+            __nv_cvt_fp8_to_halfraw(__x, __NV_E5M2));
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Conversion operator to \p __nv_bfloat16 data type.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator __nv_bfloat16() const {
+        return static_cast<__nv_bfloat16>(
+            __internal_float_to_bf16raw_rz(float(*this)));
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Conversion operator to \p double data type.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator double() const {
+        return static_cast<double>(float(*this));
+    }
+
+    /* Convert to integral */
+
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Conversion operator to \p unsigned \p char data type.
+     * Clamps negative and too large inputs to the output range.
+     * \p NaN inputs convert to \p zero.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator unsigned char() const {
+        unsigned char i;
+        const float f = float(*this);
+        const unsigned char max_val = 0xFFU;
+        const unsigned char min_val = 0U;
+        const unsigned char bits = (*this).__x;
+        // saturation fixup
+        if ((bits & 0x7FU) > 0x7CU) {
+            // NaN
+            i = 0;
+        } else if (f > static_cast<float>(max_val)) {
+            // saturate maximum
+            i = max_val;
+        } else if (f < static_cast<float>(min_val)) {
+            // saturate minimum
+            i = min_val;
+        } else {
+            // normal value
+            i = static_cast<unsigned char>(f);
+        }
+        return i;
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Conversion operator to \p unsigned \p short \p int data type.
+     * Clamps negative and too large inputs to the output range.
+     * \p NaN inputs convert to \p zero.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator unsigned short int() const {
+        return __half2ushort_rz(__half(*this));
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Conversion operator to \p unsigned \p int data type.
+     * Clamps negative and too large inputs to the output range.
+     * \p NaN inputs convert to \p zero.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator unsigned int() const {
+        return __half2uint_rz(__half(*this));
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Conversion operator to \p unsigned \p long \p long \p int data type.
+     * Clamps negative and too large inputs to the output range.
+     * \p NaN inputs convert to \p 0x8000000000000000ULL.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator unsigned long long int() const {
+        return __half2ull_rz(__half(*this));
+    }
+
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Conversion operator to \p signed \p char data type.
+     * Clamps too large inputs to the output range.
+     * \p NaN inputs convert to \p zero.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator signed char() const {
+        signed char i;
+        const float f = float(*this);
+        const signed char max_val = (signed char)0x7FU;
+        const signed char min_val = (signed char)0x80U;
+        const unsigned char bits = (*this).__x;
+        // saturation fixup
+        if ((bits & 0x7FU) > 0x7CU) {
+            // NaN
+            i = 0;
+        } else if (f > static_cast<float>(max_val)) {
+            // saturate maximum
+            i = max_val;
+        } else if (f < static_cast<float>(min_val)) {
+            // saturate minimum
+            i = min_val;
+        } else {
+            // normal value
+            i = static_cast<signed char>(f);
+        }
+        return i;
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Conversion operator to \p short \p int data type.
+     * Clamps too large inputs to the output range.
+     * \p NaN inputs convert to \p zero.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator short int() const {
+        return __half2short_rz(__half(*this));
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Conversion operator to \p int data type.
+     * Clamps too large inputs to the output range.
+     * \p NaN inputs convert to \p zero.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator int() const {
+        return __half2int_rz(__half(*this));
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Conversion operator to \p long \p long \p int data type.
+     * Clamps too large inputs to the output range.
+     * \p NaN inputs convert to \p 0x8000000000000000LL.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator long long int() const {
+        return __half2ll_rz(__half(*this));
+    }
+
+    /**
+     * \ingroup CUDA_MATH_FP8_E5M2_STRUCT
+     * Conversion operator to \p bool data type.
+     * +0 and -0 inputs convert to \p false.
+     * Non-zero inputs convert to \p true.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator bool() const {
+        return (__x & 0x7FU) != 0U;
+    }
+#endif /* !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__) */
+#endif /* !defined(__CUDA_NO_FP8_CONVERSIONS__) */
+};
+
+/**
+ * \defgroup CUDA_MATH_FP8X2_E5M2_STRUCT C++ struct for handling vector type of two fp8 values of e5m2 kind.
+ * \ingroup CUDA_MATH_INTRINSIC_FP8
+ */
+
+/**
+ * \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
+ * \brief __nv_fp8x2_e5m2 datatype
+ *
+ * \details This structure implements the datatype for handling two
+ * \p fp8 floating-point numbers of \p e5m2 kind each:
+ * with 1 sign, 5 exponent, 1 implicit and 2 explicit mantissa bits.
+ *
+ * The structure implements converting constructors and operators.
+ */
+struct __CUDA_ALIGN__(2) __nv_fp8x2_e5m2 {
+  public:
+    /**
+     * \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
+     * Storage variable contains the vector of two \p fp8 floating-point data
+     * values.
+     */
+    __nv_fp8x2_storage_t __x;
+
+    /**
+     * \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
+     * Constructor by default.
+     */
+#if defined(__CPP_VERSION_AT_LEAST_11_FP8)
+    __nv_fp8x2_e5m2() = default;
+#else
+    __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e5m2() {}
+#endif /* defined(__CPP_VERSION_AT_LEAST_11_FP8) */
+
+#if !defined(__CUDA_NO_FP8_CONVERSIONS__)
+
+    /* Construct from wider types */
+
+    /**
+     * \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
+     * Constructor from \p __half2 data type, relies on \p __NV_SATFINITE
+     * behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e5m2(const __half2 f) {
+        __x = __nv_cvt_halfraw2_to_fp8x2(static_cast<__half2_raw>(f),
+                                         __NV_SATFINITE, __NV_E5M2);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
+     * Constructor from \p __nv_bfloat162 data type, relies on \p __NV_SATFINITE
+     * behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e5m2(const __nv_bfloat162 f) {
+        __x = __nv_cvt_bfloat16raw2_to_fp8x2(static_cast<__nv_bfloat162_raw>(f),
+                                             __NV_SATFINITE, __NV_E5M2);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
+     * Constructor from \p float2 data type, relies on \p __NV_SATFINITE
+     * behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e5m2(const float2 f) {
+        __x = __nv_cvt_float2_to_fp8x2(f, __NV_SATFINITE, __NV_E5M2);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
+     * Constructor from \p double2 data type, relies on \p __NV_SATFINITE
+     * behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e5m2(const double2 f) {
+        __x = __nv_cvt_double2_to_fp8x2(f, __NV_SATFINITE, __NV_E5M2);
+    }
+
+#if !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__)
+    /* Widening converts */
+    /**
+     * \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
+     * Conversion operator to \p __half2 data type.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator __half2() const {
+        return static_cast<__half2>(__nv_cvt_fp8x2_to_halfraw2(__x, __NV_E5M2));
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
+     * Conversion operator to \p float2 data type.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator float2() const {
+        return __internal_halfraw2_to_float2(
+            __nv_cvt_fp8x2_to_halfraw2(__x, __NV_E5M2));
+    }
+#endif /* !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__) */
+#endif /* !defined(__CUDA_NO_FP8_CONVERSIONS__) */
+};
+
+__CUDA_HOSTDEVICE_FP8_DECL__ unsigned int
+__internal_pack_u16x2_to_u32(const unsigned short int src_lo,
+                             const unsigned short int src_hi) {
+    unsigned int dst;
+#if (defined __CUDACC__) && (defined __CUDA_ARCH__)
+    asm("{  mov.b32 %0, {%1,%2};}\n" : "=r"(dst) : "h"(src_lo), "h"(src_hi));
+#else
+    dst = (static_cast<unsigned int>(src_hi) << 16U) |
+          static_cast<unsigned int>(src_lo);
+#endif
+    return dst;
+}
+
+/**
+ * \defgroup CUDA_MATH_FP8X4_E5M2_STRUCT C++ struct for handling vector type of four fp8 values of e5m2 kind.
+ * \ingroup CUDA_MATH_INTRINSIC_FP8
+ */
+
+/**
+ * \ingroup CUDA_MATH_FP8X4_E5M2_STRUCT
+ * \brief __nv_fp8x4_e5m2 datatype
+ *
+ * \details This structure implements the datatype for handling four
+ * \p fp8 floating-point numbers of \p e5m2 kind each:
+ * with 1 sign, 5 exponent, 1 implicit and 2 explicit mantissa bits.
+ *
+ * The structure implements converting constructors and operators.
+ */
+struct __CUDA_ALIGN__(4) __nv_fp8x4_e5m2 {
+  public:
+    /**
+     * \ingroup CUDA_MATH_FP8X4_E5M2_STRUCT
+     * Storage variable contains the vector of four \p fp8 floating-point data
+     * values.
+     */
+    __nv_fp8x4_storage_t __x;
+
+    /**
+     * \ingroup CUDA_MATH_FP8X4_E5M2_STRUCT
+     * Constructor by default.
+     */
+#if defined(__CPP_VERSION_AT_LEAST_11_FP8)
+    __nv_fp8x4_e5m2() = default;
+#else
+    __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e5m2() {}
+#endif /* defined(__CPP_VERSION_AT_LEAST_11_FP8) */
+
+#if !defined(__CUDA_NO_FP8_CONVERSIONS__)
+
+    /* Construct from wider types */
+
+    /**
+     * \ingroup CUDA_MATH_FP8X4_E5M2_STRUCT
+     * Constructor from a pair of \p __half2 data type values,
+     * relies on \p __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e5m2(const __half2 flo,
+                                                     const __half2 fhi) {
+        const __nv_fp8x2_storage_t rlo = __nv_cvt_halfraw2_to_fp8x2(
+            static_cast<__half2_raw>(flo), __NV_SATFINITE, __NV_E5M2);
+        const __nv_fp8x2_storage_t rhi = __nv_cvt_halfraw2_to_fp8x2(
+            static_cast<__half2_raw>(fhi), __NV_SATFINITE, __NV_E5M2);
+        __x = __internal_pack_u16x2_to_u32(rlo, rhi);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8X4_E5M2_STRUCT
+     * Constructor from a pair of \p __nv_bfloat162 data type values,
+     * relies on \p __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e5m2(const __nv_bfloat162 flo,
+                                                     const __nv_bfloat162 fhi) {
+        const __nv_fp8x2_storage_t rlo = __nv_cvt_bfloat16raw2_to_fp8x2(
+            static_cast<__nv_bfloat162_raw>(flo), __NV_SATFINITE, __NV_E5M2);
+        const __nv_fp8x2_storage_t rhi = __nv_cvt_bfloat16raw2_to_fp8x2(
+            static_cast<__nv_bfloat162_raw>(fhi), __NV_SATFINITE, __NV_E5M2);
+        __x = __internal_pack_u16x2_to_u32(rlo, rhi);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8X4_E5M2_STRUCT
+     * Constructor from \p float4 vector data type,
+     * relies on \p __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e5m2(const float4 f) {
+        const float2 flo = {f.x, f.y};
+        const float2 fhi = {f.z, f.w};
+        const __nv_fp8x2_storage_t rlo =
+            __nv_cvt_float2_to_fp8x2(flo, __NV_SATFINITE, __NV_E5M2);
+        const __nv_fp8x2_storage_t rhi =
+            __nv_cvt_float2_to_fp8x2(fhi, __NV_SATFINITE, __NV_E5M2);
+        __x = __internal_pack_u16x2_to_u32(rlo, rhi);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8X4_E5M2_STRUCT
+     * Constructor from \p double4 vector data type,
+     * relies on \p __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e5m2(const double4 f) {
+        const double2 flo = {f.x, f.y};
+        const double2 fhi = {f.z, f.w};
+        const __nv_fp8x2_storage_t rlo =
+            __nv_cvt_double2_to_fp8x2(flo, __NV_SATFINITE, __NV_E5M2);
+        const __nv_fp8x2_storage_t rhi =
+            __nv_cvt_double2_to_fp8x2(fhi, __NV_SATFINITE, __NV_E5M2);
+        __x = __internal_pack_u16x2_to_u32(rlo, rhi);
+    }
+
+#if !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__)
+    /* Widening converts */
+
+    /**
+     * \ingroup CUDA_MATH_FP8X4_E5M2_STRUCT
+     * Conversion operator to \p float4 vector data type.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator float4() const {
+        const __nv_fp8x2_storage_t slo = static_cast<__nv_fp8x2_storage_t>(__x);
+        const __nv_fp8x2_storage_t shi =
+            static_cast<__nv_fp8x2_storage_t>(__x >> 16U);
+        float2 rlo = __internal_halfraw2_to_float2(
+            __nv_cvt_fp8x2_to_halfraw2(slo, __NV_E5M2));
+        float2 rhi = __internal_halfraw2_to_float2(
+            __nv_cvt_fp8x2_to_halfraw2(shi, __NV_E5M2));
+        float4 res = {rlo.x, rlo.y, rhi.x, rhi.y};
+        return res;
+    }
+#endif /* !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__) */
+#endif /* !defined(__CUDA_NO_FP8_CONVERSIONS__) */
+};
+
+/**
+ * \defgroup CUDA_MATH_FP8_E4M3_STRUCT C++ struct for handling fp8 data type of e4m3 kind.
+ * \ingroup CUDA_MATH_INTRINSIC_FP8
+ */
+
+/**
+ * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+ * \brief __nv_fp8_e4m3 datatype
+ *
+ * \details This structure implements the datatype for storing
+ * \p fp8 floating-point numbers of \p e4m3 kind:
+ * with 1 sign, 4 exponent, 1 implicit and 3 explicit mantissa bits.
+ * The encoding doesn't support Infinity.
+ * NaNs are limited to 0x7F and 0xFF values.
+ *
+ * The structure implements converting constructors and operators.
+ */
+struct __CUDA_ALIGN__(1) __nv_fp8_e4m3 {
+  public:
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Storage variable contains the \p fp8 floating-point data.
+     */
+    __nv_fp8_storage_t __x;
+
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Constructor by default.
+     */
+#if defined(__CPP_VERSION_AT_LEAST_11_FP8)
+    __nv_fp8_e4m3() = default;
+#else
+    __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3() {}
+#endif /* defined(__CPP_VERSION_AT_LEAST_11_FP8) */
+
+#if !defined(__CUDA_NO_FP8_CONVERSIONS__)
+
+    /* Construct from wider FP types */
+    /* Note we do avoid constructor init-list because of special host/device
+     * compilation rules */
+
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Constructor from \p __half data type, relies on \p __NV_SATFINITE
+     * behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3(const __half f) {
+        __x = __nv_cvt_halfraw_to_fp8(static_cast<__half_raw>(f),
+                                      __NV_SATFINITE, __NV_E4M3);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Constructor from \p __nv_bfloat16 data type, relies on \p __NV_SATFINITE
+     * behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3(const __nv_bfloat16 f) {
+        __x = __nv_cvt_bfloat16raw_to_fp8(static_cast<__nv_bfloat16_raw>(f),
+                                          __NV_SATFINITE, __NV_E4M3);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Constructor from \p float data type, relies on \p __NV_SATFINITE behavior
+     * for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3(const float f) {
+        __x = __nv_cvt_float_to_fp8(f, __NV_SATFINITE, __NV_E4M3);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Constructor from \p double data type, relies on \p __NV_SATFINITE
+     * behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3(const double f) {
+        __x = __nv_cvt_double_to_fp8(f, __NV_SATFINITE, __NV_E4M3);
+    }
+
+    /* Converts from integral */
+
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Constructor from \p unsigned \p short \p int data type, relies on \p
+     * __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__
+    __nv_fp8_e4m3(const unsigned short int val) {
+        __x = static_cast<__nv_fp8_e4m3>(static_cast<float>(val)).__x;
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Constructor from \p unsigned \p int data type, relies on \p
+     * __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3(const unsigned int val) {
+        __x = static_cast<__nv_fp8_e4m3>(static_cast<float>(val)).__x;
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Constructor from \p unsigned \p long \p long \p int data type, relies on
+     * \p __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__
+    __nv_fp8_e4m3(const unsigned long long int val) {
+        __x = static_cast<__nv_fp8_e4m3>(static_cast<float>(val)).__x;
+    }
+
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Constructor from \p short \p int data type, relies on \p
+     * __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3(const short int val) {
+        __x = static_cast<__nv_fp8_e4m3>(static_cast<float>(val)).__x;
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Constructor from \p int data type, relies on \p __NV_SATFINITE behavior
+     * for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3(const int val) {
+        __x = static_cast<__nv_fp8_e4m3>(static_cast<float>(val)).__x;
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Constructor from \p long \p long \p int data type, relies on \p
+     * __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3(const long long int val) {
+        __x = static_cast<__nv_fp8_e4m3>(static_cast<float>(val)).__x;
+    }
+
+#if !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__)
+    /* Widening FP converts */
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Conversion operator to \p __half data type.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator __half() const {
+        return static_cast<__half>(__nv_cvt_fp8_to_halfraw(__x, __NV_E4M3));
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Conversion operator to \p float data type.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator float() const {
+        return __internal_halfraw_to_float(
+            __nv_cvt_fp8_to_halfraw(__x, __NV_E4M3));
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Conversion operator to \p __nv_bfloat16 data type.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator __nv_bfloat16() const {
+        return static_cast<__nv_bfloat16>(
+            __internal_float_to_bf16raw_rz(float(*this)));
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Conversion operator to \p double data type.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator double() const {
+        return static_cast<double>(float(*this));
+    }
+
+    /* Convert to integral */
+
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Conversion operator to \p unsigned \p char data type.
+     * Clamps negative and too large inputs to the output range.
+     * \p NaN inputs convert to \p zero.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator unsigned char() const {
+        unsigned char i;
+        const float f = float(*this);
+        const unsigned char max_val = 0xFFU;
+        const unsigned char min_val = 0U;
+        const unsigned char bits = (*this).__x;
+        // saturation fixup
+        if ((bits & 0x7FU) == 0x7FU) {
+            // NaN
+            i = 0;
+        } else if (f > static_cast<float>(max_val)) {
+            // saturate maximum
+            i = max_val;
+        } else if (f < static_cast<float>(min_val)) {
+            // saturate minimum
+            i = min_val;
+        } else {
+            // normal value
+            i = static_cast<unsigned char>(f);
+        }
+        return i;
+    }
+
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Conversion operator to \p unsigned \p short \p int data type.
+     * Clamps negative inputs to zero.
+     * \p NaN inputs convert to \p zero.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator unsigned short int() const {
+        return __half2ushort_rz(__half(*this));
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Conversion operator to \p unsigned \p int data type.
+     * Clamps negative inputs to zero.
+     * \p NaN inputs convert to \p zero.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator unsigned int() const {
+        return __half2uint_rz(__half(*this));
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Conversion operator to \p unsigned \p long \p long \p int data type.
+     * Clamps negative inputs to zero.
+     * \p NaN inputs convert to \p 0x8000000000000000ULL.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator unsigned long long int() const {
+        return __half2ull_rz(__half(*this));
+    }
+
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Conversion operator to \p signed \p char data type.
+     * Clamps too large inputs to the output range.
+     * \p NaN inputs convert to \p zero.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator signed char() const {
+        signed char i;
+        const float f = float(*this);
+        const signed char max_val = (signed char)0x7FU;
+        const signed char min_val = (signed char)0x80U;
+        const unsigned char bits = (*this).__x;
+        // saturation fixup
+        if ((bits & 0x7FU) == 0x7FU) {
+            // NaN
+            i = 0;
+        } else if (f > static_cast<float>(max_val)) {
+            // saturate maximum
+            i = max_val;
+        } else if (f < static_cast<float>(min_val)) {
+            // saturate minimum
+            i = min_val;
+        } else {
+            // normal value
+            i = static_cast<signed char>(f);
+        }
+        return i;
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Conversion operator to \p short \p int data type.
+     * \p NaN inputs convert to \p zero.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator short int() const {
+        return __half2short_rz(__half(*this));
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Conversion operator to \p int data type.
+     * \p NaN inputs convert to \p zero.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator int() const {
+        return __half2int_rz(__half(*this));
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Conversion operator to \p long \p long \p int data type.
+     * \p NaN inputs convert to \p 0x8000000000000000LL.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator long long int() const {
+        return __half2ll_rz(__half(*this));
+    }
+
+    /**
+     * \ingroup CUDA_MATH_FP8_E4M3_STRUCT
+     * Conversion operator to \p bool data type.
+     * +0 and -0 inputs convert to \p false.
+     * Non-zero inputs convert to \p true.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator bool() const {
+        return (__x & 0x7FU) != 0U;
+    }
+#endif /* !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__) */
+#endif /* !defined(__CUDA_NO_FP8_CONVERSIONS__) */
+};
+
+/**
+ * \defgroup CUDA_MATH_FP8X2_E4M3_STRUCT C++ struct for handling vector type of two fp8 values of e4m3 kind.
+ * \ingroup CUDA_MATH_INTRINSIC_FP8
+ */
+
+/**
+ * \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
+ * \brief __nv_fp8x2_e4m3 datatype
+ *
+ * \details This structure implements the datatype for storage
+ * and operations on the vector of two \p fp8 values of \p e4m3 kind each:
+ * with 1 sign, 4 exponent, 1 implicit and 3 explicit mantissa bits.
+ * The encoding doesn't support Infinity.
+ * NaNs are limited to 0x7F and 0xFF values.
+ */
+struct __CUDA_ALIGN__(2) __nv_fp8x2_e4m3 {
+  public:
+    /**
+     * \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
+     * Storage variable contains the vector of two \p fp8 floating-point data
+     * values.
+     */
+    __nv_fp8x2_storage_t __x;
+
+    /**
+     * \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
+     * Constructor by default.
+     */
+#if defined(__CPP_VERSION_AT_LEAST_11_FP8)
+    __nv_fp8x2_e4m3() = default;
+#else
+    __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e4m3() {}
+#endif /* defined(__CPP_VERSION_AT_LEAST_11_FP8) */
+
+#if !defined(__CUDA_NO_FP8_CONVERSIONS__)
+
+    /* Construct from wider types */
+
+    /**
+     * \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
+     * Constructor from \p __half2 data type, relies on \p __NV_SATFINITE
+     * behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e4m3(const __half2 f) {
+        __x = __nv_cvt_halfraw2_to_fp8x2(static_cast<__half2_raw>(f),
+                                         __NV_SATFINITE, __NV_E4M3);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
+     * Constructor from \p __nv_bfloat162 data type, relies on \p __NV_SATFINITE
+     * behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e4m3(const __nv_bfloat162 f) {
+        __x = __nv_cvt_bfloat16raw2_to_fp8x2(static_cast<__nv_bfloat162_raw>(f),
+                                             __NV_SATFINITE, __NV_E4M3);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
+     * Constructor from \p float2 data type, relies on \p __NV_SATFINITE
+     * behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e4m3(const float2 f) {
+        __x = __nv_cvt_float2_to_fp8x2(f, __NV_SATFINITE, __NV_E4M3);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
+     * Constructor from \p double2 data type, relies on \p __NV_SATFINITE
+     * behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e4m3(const double2 f) {
+        __x = __nv_cvt_double2_to_fp8x2(f, __NV_SATFINITE, __NV_E4M3);
+    }
+
+#if !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__)
+    /* Widening converts */
+    /**
+     * \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
+     * Conversion operator to \p __half2 data type.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator __half2() const {
+        return static_cast<__half2>(__nv_cvt_fp8x2_to_halfraw2(__x, __NV_E4M3));
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
+     * Conversion operator to \p float2 data type.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator float2() const {
+        return __internal_halfraw2_to_float2(
+            __nv_cvt_fp8x2_to_halfraw2(__x, __NV_E4M3));
+    }
+#endif /* !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__) */
+#endif /* !defined(__CUDA_NO_FP8_CONVERSIONS__) */
+};
+
+/**
+ * \defgroup CUDA_MATH_FP8X4_E4M3_STRUCT C++ struct for handling vector type of four fp8 values of e4m3 kind.
+ * \ingroup CUDA_MATH_INTRINSIC_FP8
+ */
+
+/**
+ * \ingroup CUDA_MATH_FP8X4_E4M3_STRUCT
+ * \brief __nv_fp8x4_e4m3 datatype
+ *
+ * \details This structure implements the datatype for storage
+ * and operations on the vector of four \p fp8 values of \p e4m3 kind each:
+ * with 1 sign, 4 exponent, 1 implicit and 3 explicit mantissa bits.
+ * The encoding doesn't support Infinity.
+ * NaNs are limited to 0x7F and 0xFF values.
+ */
+struct __CUDA_ALIGN__(4) __nv_fp8x4_e4m3 {
+  public:
+    /**
+     * \ingroup CUDA_MATH_FP8X4_E4M3_STRUCT
+     * Storage variable contains the vector of four \p fp8 floating-point data
+     * values.
+     */
+    __nv_fp8x4_storage_t __x;
+
+    /**
+     * \ingroup CUDA_MATH_FP8X4_E4M3_STRUCT
+     * Constructor by default.
+     */
+#if defined(__CPP_VERSION_AT_LEAST_11_FP8)
+    __nv_fp8x4_e4m3() = default;
+#else
+    __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e4m3() {}
+#endif /* defined(__CPP_VERSION_AT_LEAST_11_FP8) */
+
+#if !defined(__CUDA_NO_FP8_CONVERSIONS__)
+
+    /* Construct from wider types */
+
+    /**
+     * \ingroup CUDA_MATH_FP8X4_E4M3_STRUCT
+     * Constructor from a pair of \p __half2 data type values,
+     * relies on \p __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e4m3(const __half2 flo,
+                                                     const __half2 fhi) {
+        const __nv_fp8x2_storage_t rlo = __nv_cvt_halfraw2_to_fp8x2(
+            static_cast<__half2_raw>(flo), __NV_SATFINITE, __NV_E4M3);
+        const __nv_fp8x2_storage_t rhi = __nv_cvt_halfraw2_to_fp8x2(
+            static_cast<__half2_raw>(fhi), __NV_SATFINITE, __NV_E4M3);
+        __x = __internal_pack_u16x2_to_u32(rlo, rhi);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8X4_E4M3_STRUCT
+     * Constructor from a pair of \p __nv_bfloat162 data type values,
+     * relies on \p __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e4m3(const __nv_bfloat162 flo,
+                                                     const __nv_bfloat162 fhi) {
+        const __nv_fp8x2_storage_t rlo = __nv_cvt_bfloat16raw2_to_fp8x2(
+            static_cast<__nv_bfloat162_raw>(flo), __NV_SATFINITE, __NV_E4M3);
+        const __nv_fp8x2_storage_t rhi = __nv_cvt_bfloat16raw2_to_fp8x2(
+            static_cast<__nv_bfloat162_raw>(fhi), __NV_SATFINITE, __NV_E4M3);
+        __x = __internal_pack_u16x2_to_u32(rlo, rhi);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8X4_E4M3_STRUCT
+     * Constructor from \p float4 vector data type,
+     * relies on \p __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e4m3(const float4 f) {
+        const float2 flo = {f.x, f.y};
+        const float2 fhi = {f.z, f.w};
+        const __nv_fp8x2_storage_t rlo =
+            __nv_cvt_float2_to_fp8x2(flo, __NV_SATFINITE, __NV_E4M3);
+        const __nv_fp8x2_storage_t rhi =
+            __nv_cvt_float2_to_fp8x2(fhi, __NV_SATFINITE, __NV_E4M3);
+        __x = __internal_pack_u16x2_to_u32(rlo, rhi);
+    }
+    /**
+     * \ingroup CUDA_MATH_FP8X4_E4M3_STRUCT
+     * Constructor from \p double4 vector data type,
+     * relies on \p __NV_SATFINITE behavior for out-of-range values.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e4m3(const double4 f) {
+        const double2 flo = {f.x, f.y};
+        const double2 fhi = {f.z, f.w};
+        const __nv_fp8x2_storage_t rlo =
+            __nv_cvt_double2_to_fp8x2(flo, __NV_SATFINITE, __NV_E4M3);
+        const __nv_fp8x2_storage_t rhi =
+            __nv_cvt_double2_to_fp8x2(fhi, __NV_SATFINITE, __NV_E4M3);
+        __x = __internal_pack_u16x2_to_u32(rlo, rhi);
+    }
+
+#if !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__)
+    /* Widening converts */
+
+    /**
+     * \ingroup CUDA_MATH_FP8X4_E4M3_STRUCT
+     * Conversion operator to \p float4 vector data type.
+     */
+    explicit __CUDA_HOSTDEVICE_FP8__ operator float4() const {
+        const __nv_fp8x2_storage_t slo = static_cast<__nv_fp8x2_storage_t>(__x);
+        const __nv_fp8x2_storage_t shi =
+            static_cast<__nv_fp8x2_storage_t>(__x >> 16U);
+        float2 rlo = __internal_halfraw2_to_float2(
+            __nv_cvt_fp8x2_to_halfraw2(slo, __NV_E4M3));
+        float2 rhi = __internal_halfraw2_to_float2(
+            __nv_cvt_fp8x2_to_halfraw2(shi, __NV_E4M3));
+        float4 res = {rlo.x, rlo.y, rhi.x, rhi.y};
+        return res;
+    }
+#endif /* !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__) */
+#endif /* !defined(__CUDA_NO_FP8_CONVERSIONS__) */
+};
+
+#endif /* defined(__cplusplus) */
+
+#endif /* end of include guard: __CUDA_FP8_HPP__ */

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cuda_gl_interop.h

@@ -0,0 +1,514 @@
+/*
+ * Copyright 1993-2012 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__CUDA_GL_INTEROP_H__)
+#define __CUDA_GL_INTEROP_H__
+
+#include "cuda_runtime_api.h"
+
+#if defined(__APPLE__)
+
+#include <OpenGL/gl.h>
+
+#else /* __APPLE__ */
+
+#if defined(__arm__) || defined(__aarch64__)
+#ifndef GL_VERSION
+#error Please include the appropriate gl headers before including cuda_gl_interop.h
+#endif
+#else
+#include <GL/gl.h>
+#endif
+
+#endif /* __APPLE__ */
+
+/** \cond impl_private */
+#if defined(__DOXYGEN_ONLY__) || defined(CUDA_ENABLE_DEPRECATED)
+#define __CUDA_DEPRECATED
+#elif defined(_MSC_VER)
+#define __CUDA_DEPRECATED __declspec(deprecated)
+#elif defined(__GNUC__)
+#define __CUDA_DEPRECATED __attribute__((deprecated))
+#else
+#define __CUDA_DEPRECATED
+#endif
+/** \endcond impl_private */
+
+#if defined(__cplusplus)
+extern "C" {
+#endif /* __cplusplus */
+
+/**
+ * \addtogroup CUDART_OPENGL OpenGL Interoperability
+ * This section describes the OpenGL interoperability functions of the CUDA
+ * runtime application programming interface. Note that mapping of OpenGL
+ * resources is performed with the graphics API agnostic, resource mapping 
+ * interface described in \ref CUDART_INTEROP "Graphics Interopability".
+ *
+ * @{
+ */
+
+/**
+ * CUDA devices corresponding to the current OpenGL context
+ */
+enum cudaGLDeviceList
+{
+  cudaGLDeviceListAll           = 1, /**< The CUDA devices for all GPUs used by the current OpenGL context */
+  cudaGLDeviceListCurrentFrame  = 2, /**< The CUDA devices for the GPUs used by the current OpenGL context in its currently rendering frame */
+  cudaGLDeviceListNextFrame     = 3  /**< The CUDA devices for the GPUs to be used by the current OpenGL context in the next frame  */
+};
+
+/**
+ * \brief Gets the CUDA devices associated with the current OpenGL context
+ *
+ * Returns in \p *pCudaDeviceCount the number of CUDA-compatible devices 
+ * corresponding to the current OpenGL context. Also returns in \p *pCudaDevices 
+ * at most \p cudaDeviceCount of the CUDA-compatible devices corresponding to 
+ * the current OpenGL context. If any of the GPUs being used by the current OpenGL
+ * context are not CUDA capable then the call will return ::cudaErrorNoDevice.
+ *
+ * \param pCudaDeviceCount - Returned number of CUDA devices corresponding to the 
+ *                           current OpenGL context
+ * \param pCudaDevices     - Returned CUDA devices corresponding to the current 
+ *                           OpenGL context
+ * \param cudaDeviceCount  - The size of the output device array \p pCudaDevices
+ * \param deviceList       - The set of devices to return.  This set may be
+ *                           ::cudaGLDeviceListAll for all devices, 
+ *                           ::cudaGLDeviceListCurrentFrame for the devices used to
+ *                           render the current frame (in SLI), or
+ *                           ::cudaGLDeviceListNextFrame for the devices used to
+ *                           render the next frame (in SLI).
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorNoDevice,
+ * ::cudaErrorInvalidGraphicsContext,
+ * ::cudaErrorOperatingSystem,
+ * ::cudaErrorUnknown
+ *
+ * \note This function is not supported on Mac OS X.
+ * \notefnerr
+ *
+ * \sa 
+ * ::cudaGraphicsUnregisterResource,
+ * ::cudaGraphicsMapResources, 
+ * ::cudaGraphicsSubResourceGetMappedArray, 
+ * ::cudaGraphicsResourceGetMappedPointer,
+ * ::cuGLGetDevices 
+ */
+extern __host__ cudaError_t CUDARTAPI cudaGLGetDevices(unsigned int *pCudaDeviceCount, int *pCudaDevices, unsigned int cudaDeviceCount, enum cudaGLDeviceList deviceList);
+
+/**
+ * \brief Register an OpenGL texture or renderbuffer object
+ *
+ * Registers the texture or renderbuffer object specified by \p image for access by CUDA.
+ * A handle to the registered object is returned as \p resource.
+ *
+ * \p target must match the type of the object, and must be one of ::GL_TEXTURE_2D, 
+ * ::GL_TEXTURE_RECTANGLE, ::GL_TEXTURE_CUBE_MAP, ::GL_TEXTURE_3D, ::GL_TEXTURE_2D_ARRAY, 
+ * or ::GL_RENDERBUFFER.
+ *
+ * The register flags \p flags specify the intended usage, as follows: 
+ * - ::cudaGraphicsRegisterFlagsNone: Specifies no hints about how this
+ *   resource will be used. It is therefore assumed that this resource will be
+ *   read from and written to by CUDA. This is the default value.
+ * - ::cudaGraphicsRegisterFlagsReadOnly: Specifies that CUDA
+ *   will not write to this resource.
+ * - ::cudaGraphicsRegisterFlagsWriteDiscard: Specifies that
+ *   CUDA will not read from this resource and will write over the
+ *   entire contents of the resource, so none of the data previously
+ *   stored in the resource will be preserved.
+ * - ::cudaGraphicsRegisterFlagsSurfaceLoadStore: Specifies that CUDA will
+ *   bind this resource to a surface reference.
+ * - ::cudaGraphicsRegisterFlagsTextureGather: Specifies that CUDA will perform
+ *   texture gather operations on this resource.
+ *
+ * The following image formats are supported. For brevity's sake, the list is abbreviated.
+ * For ex., {GL_R, GL_RG} X {8, 16} would expand to the following 4 formats 
+ * {GL_R8, GL_R16, GL_RG8, GL_RG16} :
+ * - GL_RED, GL_RG, GL_RGBA, GL_LUMINANCE, GL_ALPHA, GL_LUMINANCE_ALPHA, GL_INTENSITY
+ * - {GL_R, GL_RG, GL_RGBA} X {8, 16, 16F, 32F, 8UI, 16UI, 32UI, 8I, 16I, 32I}
+ * - {GL_LUMINANCE, GL_ALPHA, GL_LUMINANCE_ALPHA, GL_INTENSITY} X
+ * {8, 16, 16F_ARB, 32F_ARB, 8UI_EXT, 16UI_EXT, 32UI_EXT, 8I_EXT, 16I_EXT, 32I_EXT}
+ *
+ * The following image classes are currently disallowed:
+ * - Textures with borders
+ * - Multisampled renderbuffers
+ *
+ * \param resource - Pointer to the returned object handle
+ * \param image    - name of texture or renderbuffer object to be registered
+ * \param target   - Identifies the type of object specified by \p image 
+ * \param flags    - Register flags
+ * 
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidDevice,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorInvalidResourceHandle,
+ * ::cudaErrorOperatingSystem,
+ * ::cudaErrorUnknown
+ * \notefnerr
+ *
+ * \sa 
+ * ::cudaGraphicsUnregisterResource,
+ * ::cudaGraphicsMapResources, 
+ * ::cudaGraphicsSubResourceGetMappedArray,
+ * ::cuGraphicsGLRegisterImage
+ */
+extern __host__ cudaError_t CUDARTAPI cudaGraphicsGLRegisterImage(struct cudaGraphicsResource **resource, GLuint image, GLenum target, unsigned int flags);
+
+/**
+ * \brief Registers an OpenGL buffer object
+ *
+ * Registers the buffer object specified by \p buffer for access by
+ * CUDA.  A handle to the registered object is returned as \p
+ * resource.  The register flags \p flags specify the intended usage,
+ * as follows:
+ *
+ * - ::cudaGraphicsRegisterFlagsNone: Specifies no hints about how this
+ *   resource will be used. It is therefore assumed that this resource will be
+ *   read from and written to by CUDA. This is the default value.
+ * - ::cudaGraphicsRegisterFlagsReadOnly: Specifies that CUDA
+ *   will not write to this resource.
+ * - ::cudaGraphicsRegisterFlagsWriteDiscard: Specifies that
+ *   CUDA will not read from this resource and will write over the
+ *   entire contents of the resource, so none of the data previously
+ *   stored in the resource will be preserved.
+ *
+ * \param resource - Pointer to the returned object handle
+ * \param buffer   - name of buffer object to be registered
+ * \param flags    - Register flags
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidDevice,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorInvalidResourceHandle,
+ * ::cudaErrorOperatingSystem,
+ * ::cudaErrorUnknown
+ * \notefnerr
+ *
+ * \sa 
+ * ::cudaGraphicsUnregisterResource,
+ * ::cudaGraphicsMapResources,
+ * ::cudaGraphicsResourceGetMappedPointer,
+ * ::cuGraphicsGLRegisterBuffer
+ */
+extern __host__ cudaError_t CUDARTAPI cudaGraphicsGLRegisterBuffer(struct cudaGraphicsResource **resource, GLuint buffer, unsigned int flags);
+
+#ifdef _WIN32
+#ifndef WGL_NV_gpu_affinity
+typedef void* HGPUNV;
+#endif
+
+/**
+ * \brief Gets the CUDA device associated with hGpu
+ *
+ * Returns the CUDA device associated with a hGpu, if applicable.
+ *
+ * \param device - Returns the device associated with hGpu, or -1 if hGpu is
+ * not a compute device.
+ * \param hGpu   - Handle to a GPU, as queried via WGL_NV_gpu_affinity
+ *
+ * \return
+ * ::cudaSuccess
+ * \notefnerr
+ *
+ * \sa
+ * ::WGL_NV_gpu_affinity,
+ * ::cuWGLGetDevice
+ */
+extern __host__ cudaError_t CUDARTAPI cudaWGLGetDevice(int *device, HGPUNV hGpu);
+#endif
+
+/** @} */ /* END CUDART_OPENGL */
+
+/**
+ * \addtogroup CUDART_OPENGL_DEPRECATED OpenGL Interoperability [DEPRECATED]
+ * This section describes deprecated OpenGL interoperability functionality.
+ *
+ * @{
+ */
+
+/**
+ * CUDA GL Map Flags
+ */
+enum cudaGLMapFlags
+{
+  cudaGLMapFlagsNone         = 0,  /**< Default; Assume resource can be read/written */
+  cudaGLMapFlagsReadOnly     = 1,  /**< CUDA kernels will not write to this resource */
+  cudaGLMapFlagsWriteDiscard = 2   /**< CUDA kernels will only write to and will not read from this resource */
+};
+
+/**
+ * \brief Sets a CUDA device to use OpenGL interoperability
+ *
+ * \deprecated This function is deprecated as of CUDA 5.0. 
+ *
+ * This function is deprecated and should no longer be used.  It is
+ * no longer necessary to associate a CUDA device with an OpenGL
+ * context in order to achieve maximum interoperability performance.
+ *
+ * This function will immediately initialize the primary context on 
+ * \p device if needed.
+ *
+ * \param device - Device to use for OpenGL interoperability
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidDevice,
+ * ::cudaErrorSetOnActiveProcess
+ * \notefnerr
+ *
+ * \sa ::cudaGraphicsGLRegisterBuffer, ::cudaGraphicsGLRegisterImage
+ */
+extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLSetGLDevice(int device);
+
+/**
+ * \brief Registers a buffer object for access by CUDA
+ *
+ * \deprecated This function is deprecated as of CUDA 3.0. 
+ *
+ * Registers the buffer object of ID \p bufObj for access by
+ * CUDA. This function must be called before CUDA can map the buffer
+ * object.  The OpenGL context used to create the buffer, or another
+ * context from the same share group, must be bound to the current
+ * thread when this is called.
+ *
+ * \param bufObj - Buffer object ID to register
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInitializationError
+ * \notefnerr
+ *
+ * \sa ::cudaGraphicsGLRegisterBuffer
+ */
+extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLRegisterBufferObject(GLuint bufObj);
+
+/**
+ * \brief Maps a buffer object for access by CUDA
+ *
+ * \deprecated This function is deprecated as of CUDA 3.0. 
+ *
+ * Maps the buffer object of ID \p bufObj into the address space of
+ * CUDA and returns in \p *devPtr the base pointer of the resulting
+ * mapping.  The buffer must have previously been registered by
+ * calling ::cudaGLRegisterBufferObject().  While a buffer is mapped
+ * by CUDA, any OpenGL operation which references the buffer will
+ * result in undefined behavior.  The OpenGL context used to create
+ * the buffer, or another context from the same share group, must be
+ * bound to the current thread when this is called.
+ *
+ * All streams in the current thread are synchronized with the current
+ * GL context.
+ *
+ * \param devPtr - Returned device pointer to CUDA object
+ * \param bufObj - Buffer object ID to map
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorMapBufferObjectFailed
+ * \notefnerr
+ *
+ * \sa ::cudaGraphicsMapResources
+ */
+extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLMapBufferObject(void **devPtr, GLuint bufObj);
+
+/**
+ * \brief Unmaps a buffer object for access by CUDA
+ *
+ * \deprecated This function is deprecated as of CUDA 3.0. 
+ *
+ * Unmaps the buffer object of ID \p bufObj for access by CUDA.  When
+ * a buffer is unmapped, the base address returned by
+ * ::cudaGLMapBufferObject() is invalid and subsequent references to
+ * the address result in undefined behavior.  The OpenGL context used
+ * to create the buffer, or another context from the same share group,
+ * must be bound to the current thread when this is called.
+ *
+ * All streams in the current thread are synchronized with the current
+ * GL context.
+ *
+ * \param bufObj - Buffer object to unmap
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorUnmapBufferObjectFailed
+ * \notefnerr
+ *
+ * \sa ::cudaGraphicsUnmapResources
+ */
+extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLUnmapBufferObject(GLuint bufObj);
+
+/**
+ * \brief Unregisters a buffer object for access by CUDA
+ *
+ * \deprecated This function is deprecated as of CUDA 3.0. 
+ *
+ * Unregisters the buffer object of ID \p bufObj for access by CUDA
+ * and releases any CUDA resources associated with the buffer.  Once a
+ * buffer is unregistered, it may no longer be mapped by CUDA.  The GL
+ * context used to create the buffer, or another context from the
+ * same share group, must be bound to the current thread when this is
+ * called.
+ *
+ * \param bufObj - Buffer object to unregister
+ *
+ * \return
+ * ::cudaSuccess
+ * \notefnerr
+ *
+ * \sa ::cudaGraphicsUnregisterResource
+ */
+extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLUnregisterBufferObject(GLuint bufObj);
+
+/**
+ * \brief Set usage flags for mapping an OpenGL buffer
+ *
+ * \deprecated This function is deprecated as of CUDA 3.0. 
+ *
+ * Set flags for mapping the OpenGL buffer \p bufObj
+ *
+ * Changes to flags will take effect the next time \p bufObj is mapped.
+ * The \p flags argument may be any of the following:
+ *
+ * - ::cudaGLMapFlagsNone: Specifies no hints about how this buffer will
+ * be used. It is therefore assumed that this buffer will be read from and
+ * written to by CUDA kernels. This is the default value.
+ * - ::cudaGLMapFlagsReadOnly: Specifies that CUDA kernels which access this
+ * buffer will not write to the buffer.
+ * - ::cudaGLMapFlagsWriteDiscard: Specifies that CUDA kernels which access
+ * this buffer will not read from the buffer and will write over the
+ * entire contents of the buffer, so none of the data previously stored in
+ * the buffer will be preserved.
+ *
+ * If \p bufObj has not been registered for use with CUDA, then
+ * ::cudaErrorInvalidResourceHandle is returned. If \p bufObj is presently
+ * mapped for access by CUDA, then ::cudaErrorUnknown is returned.
+ *
+ * \param bufObj    - Registered buffer object to set flags for
+ * \param flags     - Parameters for buffer mapping
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorInvalidResourceHandle,
+ * ::cudaErrorUnknown
+ * \notefnerr
+ *
+ * \sa ::cudaGraphicsResourceSetMapFlags
+ */
+extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLSetBufferObjectMapFlags(GLuint bufObj, unsigned int flags); 
+
+/**
+ * \brief Maps a buffer object for access by CUDA
+ *
+ * \deprecated This function is deprecated as of CUDA 3.0. 
+ *
+ * Maps the buffer object of ID \p bufObj into the address space of
+ * CUDA and returns in \p *devPtr the base pointer of the resulting
+ * mapping.  The buffer must have previously been registered by
+ * calling ::cudaGLRegisterBufferObject().  While a buffer is mapped
+ * by CUDA, any OpenGL operation which references the buffer will
+ * result in undefined behavior.  The OpenGL context used to create
+ * the buffer, or another context from the same share group, must be
+ * bound to the current thread when this is called.
+ *
+ * Stream /p stream is synchronized with the current GL context.
+ *
+ * \param devPtr - Returned device pointer to CUDA object
+ * \param bufObj - Buffer object ID to map
+ * \param stream - Stream to synchronize
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorMapBufferObjectFailed
+ * \notefnerr
+ *
+ * \sa ::cudaGraphicsMapResources
+ */
+extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLMapBufferObjectAsync(void **devPtr, GLuint bufObj, cudaStream_t stream);
+
+/**
+ * \brief Unmaps a buffer object for access by CUDA
+ *
+ * \deprecated This function is deprecated as of CUDA 3.0. 
+ *
+ * Unmaps the buffer object of ID \p bufObj for access by CUDA.  When
+ * a buffer is unmapped, the base address returned by
+ * ::cudaGLMapBufferObject() is invalid and subsequent references to
+ * the address result in undefined behavior.  The OpenGL context used
+ * to create the buffer, or another context from the same share group,
+ * must be bound to the current thread when this is called.
+ *
+ * Stream /p stream is synchronized with the current GL context.
+ *
+ * \param bufObj - Buffer object to unmap
+ * \param stream - Stream to synchronize
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorUnmapBufferObjectFailed
+ * \notefnerr
+ *
+ * \sa ::cudaGraphicsUnmapResources
+ */
+extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLUnmapBufferObjectAsync(GLuint bufObj, cudaStream_t stream);
+
+/** @} */ /* END CUDART_OPENGL_DEPRECATED */
+
+#if defined(__cplusplus)
+}
+#endif /* __cplusplus */
+
+#undef __CUDA_DEPRECATED
+
+#endif /* __CUDA_GL_INTEROP_H__ */
+

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cuda_occupancy.h

@@ -0,0 +1,1958 @@
+/*
+ * Copyright 1993-2017 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+/**
+ * CUDA Occupancy Calculator
+ *
+ * NAME
+ *
+ *   cudaOccMaxActiveBlocksPerMultiprocessor,
+ *   cudaOccMaxPotentialOccupancyBlockSize,
+ *   cudaOccMaxPotentialOccupancyBlockSizeVariableSMem
+ *   cudaOccAvailableDynamicSMemPerBlock
+ *
+ * DESCRIPTION
+ *
+ *   The CUDA occupancy calculator provides a standalone, programmatical
+ *   interface to compute the occupancy of a function on a device. It can also
+ *   provide occupancy-oriented launch configuration suggestions.
+ *
+ *   The function and device are defined by the user through
+ *   cudaOccFuncAttributes, cudaOccDeviceProp, and cudaOccDeviceState
+ *   structures. All APIs require all 3 of them.
+ *
+ *   See the structure definition for more details about the device / function
+ *   descriptors.
+ *
+ *   See each API's prototype for API usage.
+ *
+ * COMPATIBILITY
+ *
+ *   The occupancy calculator will be updated on each major CUDA toolkit
+ *   release. It does not provide forward compatibility, i.e. new hardwares
+ *   released after this implementation's release will not be supported.
+ *
+ * NOTE
+ *
+ *   If there is access to CUDA runtime, and the sole intent is to calculate
+ *   occupancy related values on one of the accessible CUDA devices, using CUDA
+ *   runtime's occupancy calculation APIs is recommended.
+ *
+ */
+
+#ifndef __cuda_occupancy_h__
+#define __cuda_occupancy_h__
+
+#include <stddef.h>
+#include <limits.h>
+#include <string.h>
+
+
+// __OCC_INLINE will be undefined at the end of this header
+//
+#ifdef __CUDACC__
+#define __OCC_INLINE inline __host__ __device__
+#elif defined _MSC_VER
+#define __OCC_INLINE __inline
+#else // GNUCC assumed
+#define __OCC_INLINE inline
+#endif
+
+enum cudaOccError_enum {
+    CUDA_OCC_SUCCESS              = 0,  // no error encountered
+    CUDA_OCC_ERROR_INVALID_INPUT  = 1,  // input parameter is invalid
+    CUDA_OCC_ERROR_UNKNOWN_DEVICE = 2,  // requested device is not supported in
+                                        // current implementation or device is
+                                        // invalid
+};
+typedef enum cudaOccError_enum       cudaOccError;
+
+typedef struct cudaOccResult         cudaOccResult;
+typedef struct cudaOccDeviceProp     cudaOccDeviceProp;
+typedef struct cudaOccFuncAttributes cudaOccFuncAttributes;
+typedef struct cudaOccDeviceState    cudaOccDeviceState;
+
+/**
+ * The CUDA occupancy calculator computes the occupancy of the function
+ * described by attributes with the given block size (blockSize), static device
+ * properties (properties), dynamic device states (states) and per-block dynamic
+ * shared memory allocation (dynamicSMemSize) in bytes, and output it through
+ * result along with other useful information. The occupancy is computed in
+ * terms of the maximum number of active blocks per multiprocessor. The user can
+ * then convert it to other metrics, such as number of active warps.
+ *
+ * RETURN VALUE
+ *
+ * The occupancy and related information is returned through result.
+ *
+ * If result->activeBlocksPerMultiprocessor is 0, then the given parameter
+ * combination cannot run on the device.
+ *
+ * ERRORS
+ *
+ *     CUDA_OCC_ERROR_INVALID_INPUT   input parameter is invalid.
+ *     CUDA_OCC_ERROR_UNKNOWN_DEVICE  requested device is not supported in
+ *     current implementation or device is invalid
+ */
+static __OCC_INLINE
+cudaOccError cudaOccMaxActiveBlocksPerMultiprocessor(
+    cudaOccResult               *result,           // out
+    const cudaOccDeviceProp     *properties,       // in
+    const cudaOccFuncAttributes *attributes,       // in
+    const cudaOccDeviceState    *state,            // in
+    int                          blockSize,        // in
+    size_t                       dynamicSmemSize); // in
+
+/**
+ * The CUDA launch configurator C API suggests a grid / block size pair (in
+ * minGridSize and blockSize) that achieves the best potential occupancy
+ * (i.e. maximum number of active warps with the smallest number of blocks) for
+ * the given function described by attributes, on a device described by
+ * properties with settings in state.
+ *
+ * If per-block dynamic shared memory allocation is not needed, the user should
+ * leave both blockSizeToDynamicSMemSize and dynamicSMemSize as 0.
+ *
+ * If per-block dynamic shared memory allocation is needed, then if the dynamic
+ * shared memory size is constant regardless of block size, the size should be
+ * passed through dynamicSMemSize, and blockSizeToDynamicSMemSize should be
+ * NULL.
+ *
+ * Otherwise, if the per-block dynamic shared memory size varies with different
+ * block sizes, the user needs to provide a pointer to an unary function through
+ * blockSizeToDynamicSMemSize that computes the dynamic shared memory needed by
+ * a block of the function for any given block size. dynamicSMemSize is
+ * ignored. An example signature is:
+ *
+ *    // Take block size, returns dynamic shared memory needed
+ *    size_t blockToSmem(int blockSize);
+ *
+ * RETURN VALUE
+ *
+ * The suggested block size and the minimum number of blocks needed to achieve
+ * the maximum occupancy are returned through blockSize and minGridSize.
+ *
+ * If *blockSize is 0, then the given combination cannot run on the device.
+ *
+ * ERRORS
+ *
+ *     CUDA_OCC_ERROR_INVALID_INPUT   input parameter is invalid.
+ *     CUDA_OCC_ERROR_UNKNOWN_DEVICE  requested device is not supported in
+ *     current implementation or device is invalid
+ *
+ */
+static __OCC_INLINE
+cudaOccError cudaOccMaxPotentialOccupancyBlockSize(
+    int                         *minGridSize,      // out
+    int                         *blockSize,        // out
+    const cudaOccDeviceProp     *properties,       // in
+    const cudaOccFuncAttributes *attributes,       // in
+    const cudaOccDeviceState    *state,            // in
+    size_t                     (*blockSizeToDynamicSMemSize)(int), // in
+    size_t                       dynamicSMemSize); // in
+
+/**
+ * The CUDA launch configurator C++ API suggests a grid / block size pair (in
+ * minGridSize and blockSize) that achieves the best potential occupancy
+ * (i.e. the maximum number of active warps with the smallest number of blocks)
+ * for the given function described by attributes, on a device described by
+ * properties with settings in state.
+ *
+ * If per-block dynamic shared memory allocation is 0 or constant regardless of
+ * block size, the user can use cudaOccMaxPotentialOccupancyBlockSize to
+ * configure the launch. A constant dynamic shared memory allocation size in
+ * bytes can be passed through dynamicSMemSize.
+ *
+ * Otherwise, if the per-block dynamic shared memory size varies with different
+ * block sizes, the user needs to use
+ * cudaOccMaxPotentialOccupancyBlockSizeVariableSmem instead, and provide a
+ * functor / pointer to an unary function (blockSizeToDynamicSMemSize) that
+ * computes the dynamic shared memory needed by func for any given block
+ * size. An example signature is:
+ *
+ *  // Take block size, returns per-block dynamic shared memory needed
+ *  size_t blockToSmem(int blockSize);
+ *
+ * RETURN VALUE
+ *
+ * The suggested block size and the minimum number of blocks needed to achieve
+ * the maximum occupancy are returned through blockSize and minGridSize.
+ *
+ * If *blockSize is 0, then the given combination cannot run on the device.
+ *
+ * ERRORS
+ *
+ *     CUDA_OCC_ERROR_INVALID_INPUT   input parameter is invalid.
+ *     CUDA_OCC_ERROR_UNKNOWN_DEVICE  requested device is not supported in
+ *     current implementation or device is invalid
+ *
+ */
+
+#if defined(__cplusplus)
+namespace {
+
+__OCC_INLINE
+cudaOccError cudaOccMaxPotentialOccupancyBlockSize(
+    int                         *minGridSize,          // out
+    int                         *blockSize,            // out
+    const cudaOccDeviceProp     *properties,           // in
+    const cudaOccFuncAttributes *attributes,           // in
+    const cudaOccDeviceState    *state,                // in
+    size_t                       dynamicSMemSize = 0); // in
+
+template <typename UnaryFunction>
+__OCC_INLINE
+cudaOccError cudaOccMaxPotentialOccupancyBlockSizeVariableSMem(
+    int                         *minGridSize,          // out
+    int                         *blockSize,            // out
+    const cudaOccDeviceProp     *properties,           // in
+    const cudaOccFuncAttributes *attributes,           // in
+    const cudaOccDeviceState    *state,                // in
+    UnaryFunction                blockSizeToDynamicSMemSize); // in
+
+} // namespace anonymous
+#endif // defined(__cplusplus)
+
+/**
+ *
+ * The CUDA dynamic shared memory calculator computes the maximum size of 
+ * per-block dynamic shared memory if we want to place numBlocks blocks
+ * on an SM.
+ *
+ * RETURN VALUE
+ *
+ * Returns in *dynamicSmemSize the maximum size of dynamic shared memory to allow 
+ * numBlocks blocks per SM.
+ *
+ * ERRORS
+ *
+ *     CUDA_OCC_ERROR_INVALID_INPUT   input parameter is invalid.
+ *     CUDA_OCC_ERROR_UNKNOWN_DEVICE  requested device is not supported in
+ *     current implementation or device is invalid
+ *
+ */
+static __OCC_INLINE
+cudaOccError cudaOccAvailableDynamicSMemPerBlock(
+    size_t                      *dynamicSmemSize,
+    const cudaOccDeviceProp     *properties,
+    const cudaOccFuncAttributes *attributes,
+    const cudaOccDeviceState    *state,
+    int                         numBlocks,
+    int                         blockSize);
+
+/**
+ * Data structures
+ *
+ * These structures are subject to change for future architecture and CUDA
+ * releases. C users should initialize the structure as {0}.
+ *
+ */
+
+/**
+ * Device descriptor
+ *
+ * This structure describes a device.
+ */
+struct cudaOccDeviceProp {
+    int    computeMajor;                // Compute capability major version
+    int    computeMinor;                // Compute capability minor
+                                        // version. None supported minor version
+                                        // may cause error
+    int    maxThreadsPerBlock;          // Maximum number of threads per block
+    int    maxThreadsPerMultiprocessor; // Maximum number of threads per SM
+                                        // i.e. (Max. number of warps) x (warp
+                                        // size)
+    int    regsPerBlock;                // Maximum number of registers per block
+    int    regsPerMultiprocessor;       // Maximum number of registers per SM
+    int    warpSize;                    // Warp size
+    size_t sharedMemPerBlock;           // Maximum shared memory size per block
+    size_t sharedMemPerMultiprocessor;  // Maximum shared memory size per SM
+    int    numSms;                      // Number of SMs available
+    size_t sharedMemPerBlockOptin;      // Maximum optin shared memory size per block
+    size_t reservedSharedMemPerBlock;   // Shared memory per block reserved by driver
+
+#ifdef __cplusplus
+    // This structure can be converted from a cudaDeviceProp structure for users
+    // that use this header in their CUDA applications.
+    //
+    // If the application have access to the CUDA Runtime API, the application
+    // can obtain the device properties of a CUDA device through
+    // cudaGetDeviceProperties, and initialize a cudaOccDeviceProp with the
+    // cudaDeviceProp structure.
+    //
+    // Example:
+    /*
+     {
+         cudaDeviceProp prop;
+
+         cudaGetDeviceProperties(&prop, ...);
+
+         cudaOccDeviceProp occProp = prop;
+
+         ...
+
+         cudaOccMaxPotentialOccupancyBlockSize(..., &occProp, ...);
+     }
+     */
+    //
+    template<typename DeviceProp>
+    __OCC_INLINE
+    cudaOccDeviceProp(const DeviceProp &props)
+    :   computeMajor                (props.major),
+        computeMinor                (props.minor),
+        maxThreadsPerBlock          (props.maxThreadsPerBlock),
+        maxThreadsPerMultiprocessor (props.maxThreadsPerMultiProcessor),
+        regsPerBlock                (props.regsPerBlock),
+        regsPerMultiprocessor       (props.regsPerMultiprocessor),
+        warpSize                    (props.warpSize),
+        sharedMemPerBlock           (props.sharedMemPerBlock),
+        sharedMemPerMultiprocessor  (props.sharedMemPerMultiprocessor),
+        numSms                      (props.multiProcessorCount),
+        sharedMemPerBlockOptin      (props.sharedMemPerBlockOptin),
+        reservedSharedMemPerBlock   (props.reservedSharedMemPerBlock)
+    {}
+
+    __OCC_INLINE
+    cudaOccDeviceProp()
+    :   computeMajor                (0),
+        computeMinor                (0),
+        maxThreadsPerBlock          (0),
+        maxThreadsPerMultiprocessor (0),
+        regsPerBlock                (0),
+        regsPerMultiprocessor       (0),
+        warpSize                    (0),
+        sharedMemPerBlock           (0),
+        sharedMemPerMultiprocessor  (0),
+        numSms                      (0),
+        sharedMemPerBlockOptin      (0),
+        reservedSharedMemPerBlock   (0)
+    {}
+#endif // __cplusplus
+};
+
+/**
+ * Partitioned global caching option
+ */
+typedef enum cudaOccPartitionedGCConfig_enum {
+    PARTITIONED_GC_OFF,        // Disable partitioned global caching
+    PARTITIONED_GC_ON,         // Prefer partitioned global caching
+    PARTITIONED_GC_ON_STRICT   // Force partitioned global caching
+} cudaOccPartitionedGCConfig;
+
+/**
+ * Per function opt in maximum dynamic shared memory limit
+ */
+typedef enum cudaOccFuncShmemConfig_enum {
+    FUNC_SHMEM_LIMIT_DEFAULT,   // Default shmem limit
+    FUNC_SHMEM_LIMIT_OPTIN,     // Use the optin shmem limit
+} cudaOccFuncShmemConfig;
+
+/**
+ * Function descriptor
+ *
+ * This structure describes a CUDA function.
+ */
+struct cudaOccFuncAttributes {
+    int maxThreadsPerBlock; // Maximum block size the function can work with. If
+                            // unlimited, use INT_MAX or any value greater than
+                            // or equal to maxThreadsPerBlock of the device
+    int numRegs;            // Number of registers used. When the function is
+                            // launched on device, the register count may change
+                            // due to internal tools requirements.
+    size_t sharedSizeBytes; // Number of static shared memory used
+
+    cudaOccPartitionedGCConfig partitionedGCConfig; 
+                            // Partitioned global caching is required to enable
+                            // caching on certain chips, such as sm_52
+                            // devices. Partitioned global caching can be
+                            // automatically disabled if the occupancy
+                            // requirement of the launch cannot support caching.
+                            //
+                            // To override this behavior with caching on and
+                            // calculate occupancy strictly according to the
+                            // preference, set partitionedGCConfig to
+                            // PARTITIONED_GC_ON_STRICT. This is especially
+                            // useful for experimenting and finding launch
+                            // configurations (MaxPotentialOccupancyBlockSize)
+                            // that allow global caching to take effect.
+                            //
+                            // This flag only affects the occupancy calculation.
+
+    cudaOccFuncShmemConfig shmemLimitConfig;
+                            // Certain chips like sm_70 allow a user to opt into
+                            // a higher per block limit of dynamic shared memory
+                            // This optin is performed on a per function basis
+                            // using the cuFuncSetAttribute function
+
+    size_t maxDynamicSharedSizeBytes;
+                            // User set limit on maximum dynamic shared memory
+                            // usable by the kernel
+                            // This limit is set using the cuFuncSetAttribute
+                            // function.
+
+    int numBlockBarriers;   // Number of block barriers used (default to 1)
+#ifdef __cplusplus
+    // This structure can be converted from a cudaFuncAttributes structure for
+    // users that use this header in their CUDA applications.
+    //
+    // If the application have access to the CUDA Runtime API, the application
+    // can obtain the function attributes of a CUDA kernel function through
+    // cudaFuncGetAttributes, and initialize a cudaOccFuncAttributes with the
+    // cudaFuncAttributes structure.
+    //
+    // Example:
+    /*
+      __global__ void foo() {...}
+
+      ...
+
+      {
+          cudaFuncAttributes attr;
+
+          cudaFuncGetAttributes(&attr, foo);
+
+          cudaOccFuncAttributes occAttr = attr;
+
+          ...
+
+          cudaOccMaxPotentialOccupancyBlockSize(..., &occAttr, ...);
+      }
+     */
+    //
+    template<typename FuncAttributes>
+    __OCC_INLINE
+    cudaOccFuncAttributes(const FuncAttributes &attr)
+    :   maxThreadsPerBlock  (attr.maxThreadsPerBlock),
+        numRegs             (attr.numRegs),
+        sharedSizeBytes     (attr.sharedSizeBytes),
+        partitionedGCConfig (PARTITIONED_GC_OFF),
+        shmemLimitConfig    (FUNC_SHMEM_LIMIT_OPTIN),
+        maxDynamicSharedSizeBytes (attr.maxDynamicSharedSizeBytes),
+        numBlockBarriers    (1)
+    {}
+
+    __OCC_INLINE
+    cudaOccFuncAttributes()
+    :   maxThreadsPerBlock  (0),
+        numRegs             (0),
+        sharedSizeBytes     (0),
+        partitionedGCConfig (PARTITIONED_GC_OFF),
+        shmemLimitConfig    (FUNC_SHMEM_LIMIT_DEFAULT),
+        maxDynamicSharedSizeBytes (0),
+        numBlockBarriers    (0)
+    {}
+#endif
+};
+
+typedef enum cudaOccCacheConfig_enum {
+    CACHE_PREFER_NONE   = 0x00, // no preference for shared memory or L1 (default)
+    CACHE_PREFER_SHARED = 0x01, // prefer larger shared memory and smaller L1 cache
+    CACHE_PREFER_L1     = 0x02, // prefer larger L1 cache and smaller shared memory
+    CACHE_PREFER_EQUAL  = 0x03  // prefer equal sized L1 cache and shared memory
+} cudaOccCacheConfig;
+
+typedef enum cudaOccCarveoutConfig_enum {
+    SHAREDMEM_CARVEOUT_DEFAULT       = -1,  // no preference for shared memory or L1 (default)
+    SHAREDMEM_CARVEOUT_MAX_SHARED    = 100, // prefer maximum available shared memory, minimum L1 cache
+    SHAREDMEM_CARVEOUT_MAX_L1        = 0,    // prefer maximum available L1 cache, minimum shared memory
+    SHAREDMEM_CARVEOUT_HALF          = 50   // prefer half of maximum available shared memory, with the rest as L1 cache
+} cudaOccCarveoutConfig;
+
+/**
+ * Device state descriptor
+ *
+ * This structure describes device settings that affect occupancy calculation.
+ */
+struct cudaOccDeviceState
+{
+    // Cache / shared memory split preference. Deprecated on Volta 
+    cudaOccCacheConfig cacheConfig; 
+    // Shared memory / L1 split preference. Supported on only Volta
+    int carveoutConfig;
+
+#ifdef __cplusplus
+    __OCC_INLINE
+    cudaOccDeviceState()
+    :   cacheConfig     (CACHE_PREFER_NONE),
+        carveoutConfig  (SHAREDMEM_CARVEOUT_DEFAULT)
+    {}
+#endif
+};
+
+typedef enum cudaOccLimitingFactor_enum {
+                                    // Occupancy limited due to:
+    OCC_LIMIT_WARPS         = 0x01, // - warps available
+    OCC_LIMIT_REGISTERS     = 0x02, // - registers available
+    OCC_LIMIT_SHARED_MEMORY = 0x04, // - shared memory available
+    OCC_LIMIT_BLOCKS        = 0x08, // - blocks available
+    OCC_LIMIT_BARRIERS      = 0x10  // - barrier available
+} cudaOccLimitingFactor;
+
+/**
+ * Occupancy output
+ *
+ * This structure contains occupancy calculator's output.
+ */
+struct cudaOccResult {
+    int activeBlocksPerMultiprocessor; // Occupancy
+    unsigned int limitingFactors;      // Factors that limited occupancy. A bit
+                                       // field that counts the limiting
+                                       // factors, see cudaOccLimitingFactor
+    int blockLimitRegs;                // Occupancy due to register
+                                       // usage, INT_MAX if the kernel does not
+                                       // use any register.
+    int blockLimitSharedMem;           // Occupancy due to shared memory
+                                       // usage, INT_MAX if the kernel does not
+                                       // use shared memory.
+    int blockLimitWarps;               // Occupancy due to block size limit
+    int blockLimitBlocks;              // Occupancy due to maximum number of blocks
+                                       // managable per SM
+    int blockLimitBarriers;            // Occupancy due to block barrier usage
+    int allocatedRegistersPerBlock;    // Actual number of registers allocated per
+                                       // block
+    size_t allocatedSharedMemPerBlock; // Actual size of shared memory allocated
+                                       // per block
+    cudaOccPartitionedGCConfig partitionedGCConfig;
+                                       // Report if partitioned global caching
+                                       // is actually enabled.
+};
+
+/**
+ * Partitioned global caching support
+ *
+ * See cudaOccPartitionedGlobalCachingModeSupport
+ */
+typedef enum cudaOccPartitionedGCSupport_enum {
+    PARTITIONED_GC_NOT_SUPPORTED,  // Partitioned global caching is not supported
+    PARTITIONED_GC_SUPPORTED,      // Partitioned global caching is supported
+} cudaOccPartitionedGCSupport;
+
+/**
+ * Implementation
+ */
+
+/**
+ * Max compute capability supported
+ */
+#define __CUDA_OCC_MAJOR__ 9
+#define __CUDA_OCC_MINOR__ 0
+
+//////////////////////////////////////////
+//    Mathematical Helper Functions     //
+//////////////////////////////////////////
+
+static __OCC_INLINE int __occMin(int lhs, int rhs)
+{
+    return rhs < lhs ? rhs : lhs;
+}
+
+static __OCC_INLINE int __occDivideRoundUp(int x, int y)
+{
+    return (x + (y - 1)) / y;
+}
+
+static __OCC_INLINE int __occRoundUp(int x, int y)
+{
+    return y * __occDivideRoundUp(x, y);
+}
+
+//////////////////////////////////////////
+//      Architectural Properties        //
+//////////////////////////////////////////
+
+/**
+ * Granularity of shared memory allocation
+ */
+static __OCC_INLINE cudaOccError cudaOccSMemAllocationGranularity(int *limit, const cudaOccDeviceProp *properties)
+{
+    int value;
+
+    switch(properties->computeMajor) {
+        case 3:
+        case 5:
+        case 6:
+        case 7:
+            value = 256;
+            break;
+        case 8:
+        case 9:
+            value = 128;
+            break;
+        default:
+            return CUDA_OCC_ERROR_UNKNOWN_DEVICE;
+    }
+
+    *limit = value;
+
+    return CUDA_OCC_SUCCESS;
+}
+
+/**
+ * Maximum number of registers per thread
+ */
+static __OCC_INLINE cudaOccError cudaOccRegAllocationMaxPerThread(int *limit, const cudaOccDeviceProp *properties)
+{
+    int value;
+
+    switch(properties->computeMajor) {
+        case 3:
+        case 5:
+        case 6:
+            value = 255;
+            break;
+        case 7:
+        case 8:
+        case 9:
+            value = 256;
+            break;
+        default:
+            return CUDA_OCC_ERROR_UNKNOWN_DEVICE;
+    }
+
+    *limit = value;
+
+    return CUDA_OCC_SUCCESS;
+}
+
+/**
+ * Granularity of register allocation
+ */
+static __OCC_INLINE cudaOccError cudaOccRegAllocationGranularity(int *limit, const cudaOccDeviceProp *properties)
+{
+    int value;
+
+    switch(properties->computeMajor) {
+        case 3:
+        case 5:
+        case 6:
+        case 7:
+        case 8:
+        case 9:
+            value = 256;
+            break;
+        default:
+            return CUDA_OCC_ERROR_UNKNOWN_DEVICE;
+    }
+
+    *limit = value;
+
+    return CUDA_OCC_SUCCESS;
+}
+
+/**
+ * Number of sub-partitions
+ */
+static __OCC_INLINE cudaOccError cudaOccSubPartitionsPerMultiprocessor(int *limit, const cudaOccDeviceProp *properties)
+{
+    int value;
+
+    switch(properties->computeMajor) {
+        case 3:
+        case 5:
+        case 7:
+        case 8:
+        case 9:
+            value = 4;
+            break;
+        case 6:
+            value = properties->computeMinor ? 4 : 2;
+            break;
+        default:
+            return CUDA_OCC_ERROR_UNKNOWN_DEVICE;
+    }
+
+    *limit = value;
+
+    return CUDA_OCC_SUCCESS;
+}
+
+
+/**
+ * Maximum number of blocks that can run simultaneously on a multiprocessor
+ */
+static __OCC_INLINE cudaOccError cudaOccMaxBlocksPerMultiprocessor(int* limit, const cudaOccDeviceProp *properties)
+{
+    int value;
+
+    switch(properties->computeMajor) {
+        case 3:
+            value = 16;
+            break;
+        case 5:
+        case 6:
+            value = 32;
+            break;
+        case 7: {
+            int isTuring = properties->computeMinor == 5;
+            value = (isTuring) ? 16 : 32;
+            break;
+        }
+        case 8:
+            if (properties->computeMinor == 0) {
+                value = 32;
+            }
+            else if (properties->computeMinor == 9) {
+                value = 24;
+            }
+            else {
+                value = 16;
+            }
+            break;
+        case 9:
+            value = 32;
+            break;
+        default:
+            return CUDA_OCC_ERROR_UNKNOWN_DEVICE;
+    }
+
+    *limit = value;
+
+    return CUDA_OCC_SUCCESS;
+}
+
+/** 
+ * Align up shared memory based on compute major configurations
+ */
+static __OCC_INLINE cudaOccError cudaOccAlignUpShmemSizeVoltaPlus(size_t *shMemSize, const cudaOccDeviceProp *properties)
+{
+    // Volta and Turing have shared L1 cache / shared memory, and support cache
+    // configuration to trade one for the other. These values are needed to
+    // map carveout config ratio to the next available architecture size
+    size_t size = *shMemSize;
+
+    switch (properties->computeMajor) {
+    case 7: {
+        // Turing supports 32KB and 64KB shared mem.
+        int isTuring = properties->computeMinor == 5;
+        if (isTuring) {
+            if      (size <= 32 * 1024) {
+                *shMemSize = 32 * 1024;
+            }
+            else if (size <= 64 * 1024) {
+                *shMemSize = 64 * 1024;
+            }
+            else {
+                return CUDA_OCC_ERROR_INVALID_INPUT;
+            }
+        }
+        // Volta supports 0KB, 8KB, 16KB, 32KB, 64KB, and 96KB shared mem.
+        else {
+            if      (size == 0) {
+                *shMemSize = 0;
+            }
+            else if (size <= 8 * 1024) {
+                *shMemSize = 8 * 1024;
+            }
+            else if (size <= 16 * 1024) {
+                *shMemSize = 16 * 1024;
+            }
+            else if (size <= 32 * 1024) {
+                *shMemSize = 32 * 1024;
+            }
+            else if (size <= 64 * 1024) {
+                *shMemSize = 64 * 1024;
+            }
+            else if (size <= 96 * 1024) {
+                *shMemSize = 96 * 1024;
+            }
+            else {
+                return CUDA_OCC_ERROR_INVALID_INPUT;
+            }
+        }
+        break;
+    }
+    case 8:
+        if (properties->computeMinor == 0 || properties->computeMinor == 7) {
+            if      (size == 0) {
+                *shMemSize = 0;
+            }
+            else if (size <= 8 * 1024) {
+                *shMemSize = 8 * 1024;
+            }
+            else if (size <= 16 * 1024) {
+                *shMemSize = 16 * 1024;
+            }
+            else if (size <= 32 * 1024) {
+                *shMemSize = 32 * 1024;
+            }
+            else if (size <= 64 * 1024) {
+                *shMemSize = 64 * 1024;
+            }
+            else if (size <= 100 * 1024) {
+                *shMemSize = 100 * 1024;
+            }
+            else if (size <= 132 * 1024) {
+                *shMemSize = 132 * 1024;
+            }
+            else if (size <= 164 * 1024) {
+                *shMemSize = 164 * 1024;
+            }
+            else {
+                return CUDA_OCC_ERROR_INVALID_INPUT;
+            }
+        }
+        else {
+            if      (size == 0) {
+                *shMemSize = 0;
+            }
+            else if (size <= 8 * 1024) {
+                *shMemSize = 8 * 1024;
+            }
+            else if (size <= 16 * 1024) {
+                *shMemSize = 16 * 1024;
+            }
+            else if (size <= 32 * 1024) {
+                *shMemSize = 32 * 1024;
+            }
+            else if (size <= 64 * 1024) {
+                *shMemSize = 64 * 1024;
+            }
+            else if (size <= 100 * 1024) {
+                *shMemSize = 100 * 1024;
+            }
+            else {
+                return CUDA_OCC_ERROR_INVALID_INPUT;
+            }
+        }
+        break;
+    case 9: {
+        if      (size == 0) {
+            *shMemSize = 0;
+        }
+        else if (size <= 8 * 1024) {
+            *shMemSize = 8 * 1024;
+        }
+        else if (size <= 16 * 1024) {
+            *shMemSize = 16 * 1024;
+        }
+        else if (size <= 32 * 1024) {
+            *shMemSize = 32 * 1024;
+        }
+        else if (size <= 64 * 1024) {
+            *shMemSize = 64 * 1024;
+        }
+        else if (size <= 100 * 1024) {
+            *shMemSize = 100 * 1024;
+        }
+        else if (size <= 132 * 1024) {
+            *shMemSize = 132 * 1024;
+        }
+        else if (size <= 164 * 1024) {
+            *shMemSize = 164 * 1024;
+        }
+        else if (size <= 196 * 1024) {
+            *shMemSize = 196 * 1024;
+        }
+        else if (size <= 228 * 1024) {
+            *shMemSize = 228 * 1024;
+        }
+        else {
+            return CUDA_OCC_ERROR_INVALID_INPUT;
+        }
+        break;
+    }
+    default:
+        return CUDA_OCC_ERROR_UNKNOWN_DEVICE;
+    }
+
+    return CUDA_OCC_SUCCESS;
+}
+
+/**
+ * Shared memory based on the new carveoutConfig API introduced with Volta
+ */
+static __OCC_INLINE cudaOccError cudaOccSMemPreferenceVoltaPlus(size_t *limit, const cudaOccDeviceProp *properties, const cudaOccDeviceState *state)
+{
+    cudaOccError status = CUDA_OCC_SUCCESS;
+    size_t preferenceShmemSize;
+
+    // CUDA 9.0 introduces a new API to set shared memory - L1 configuration on supported
+    // devices. This preference will take precedence over the older cacheConfig setting.
+    // Map cacheConfig to its effective preference value.
+    int effectivePreference = state->carveoutConfig;
+    if ((effectivePreference < SHAREDMEM_CARVEOUT_DEFAULT) || (effectivePreference > SHAREDMEM_CARVEOUT_MAX_SHARED)) {
+        return CUDA_OCC_ERROR_INVALID_INPUT;
+    }
+    
+    if (effectivePreference == SHAREDMEM_CARVEOUT_DEFAULT) {
+        switch (state->cacheConfig)
+        {
+        case CACHE_PREFER_L1:
+            effectivePreference = SHAREDMEM_CARVEOUT_MAX_L1;
+            break;
+        case CACHE_PREFER_SHARED:
+            effectivePreference = SHAREDMEM_CARVEOUT_MAX_SHARED;
+            break;
+        case CACHE_PREFER_EQUAL:
+            effectivePreference = SHAREDMEM_CARVEOUT_HALF;
+            break;
+        default:
+            effectivePreference = SHAREDMEM_CARVEOUT_DEFAULT;
+            break;
+        }
+    }
+
+    if (effectivePreference == SHAREDMEM_CARVEOUT_DEFAULT) {
+        preferenceShmemSize = properties->sharedMemPerMultiprocessor;
+    }
+    else {
+        preferenceShmemSize = (size_t) (effectivePreference * properties->sharedMemPerMultiprocessor) / 100;
+    }
+
+    status = cudaOccAlignUpShmemSizeVoltaPlus(&preferenceShmemSize, properties);
+    *limit = preferenceShmemSize;
+    return status;
+}
+
+/**
+ * Shared memory based on the cacheConfig
+ */
+static __OCC_INLINE cudaOccError cudaOccSMemPreference(size_t *limit, const cudaOccDeviceProp *properties, const cudaOccDeviceState *state)
+{
+    size_t bytes                          = 0;
+    size_t sharedMemPerMultiprocessorHigh = properties->sharedMemPerMultiprocessor;
+    cudaOccCacheConfig cacheConfig        = state->cacheConfig;
+
+    // Kepler has shared L1 cache / shared memory, and support cache
+    // configuration to trade one for the other. These values are needed to
+    // calculate the correct shared memory size for user requested cache
+    // configuration.
+    //
+    size_t minCacheSize                   = 16384;
+    size_t maxCacheSize                   = 49152;
+    size_t cacheAndSharedTotal            = sharedMemPerMultiprocessorHigh + minCacheSize;
+    size_t sharedMemPerMultiprocessorLow  = cacheAndSharedTotal - maxCacheSize;
+
+    switch (properties->computeMajor) {
+        case 3:
+            // Kepler supports 16KB, 32KB, or 48KB partitions for L1. The rest
+            // is shared memory.
+            //
+            switch (cacheConfig) {
+                default :
+                case CACHE_PREFER_NONE:
+                case CACHE_PREFER_SHARED:
+                    bytes = sharedMemPerMultiprocessorHigh;
+                    break;
+                case CACHE_PREFER_L1:
+                    bytes = sharedMemPerMultiprocessorLow;
+                    break;
+                case CACHE_PREFER_EQUAL:
+                    // Equal is the mid-point between high and low. It should be
+                    // equivalent to low + 16KB.
+                    //
+                    bytes = (sharedMemPerMultiprocessorHigh + sharedMemPerMultiprocessorLow) / 2;
+                    break;
+            }
+            break;
+        case 5:
+        case 6:
+            // Maxwell and Pascal have dedicated shared memory.
+            //
+            bytes = sharedMemPerMultiprocessorHigh;
+            break;
+        default:
+            return CUDA_OCC_ERROR_UNKNOWN_DEVICE;
+    }
+
+    *limit = bytes;
+
+    return CUDA_OCC_SUCCESS;
+}
+
+/**
+ * Shared memory based on config requested by User
+ */
+static __OCC_INLINE cudaOccError cudaOccSMemPerMultiprocessor(size_t *limit, const cudaOccDeviceProp *properties, const cudaOccDeviceState *state)
+{
+    // Volta introduces a new API that allows for shared memory carveout preference. Because it is a shared memory preference,
+    // it is handled separately from the cache config preference.
+    if (properties->computeMajor >= 7) {
+        return cudaOccSMemPreferenceVoltaPlus(limit, properties, state);
+    }
+    return cudaOccSMemPreference(limit, properties, state);
+}
+
+/**
+ * Return the per block shared memory limit based on function config
+ */
+static __OCC_INLINE cudaOccError cudaOccSMemPerBlock(size_t *limit, const cudaOccDeviceProp *properties, cudaOccFuncShmemConfig shmemLimitConfig, size_t smemPerCta)
+{
+    switch (properties->computeMajor) {
+        case 2:
+        case 3:
+        case 4:
+        case 5:
+        case 6:
+            *limit = properties->sharedMemPerBlock;
+            break;
+        case 7:
+        case 8:
+        case 9:
+            switch (shmemLimitConfig) {
+                default:
+                case FUNC_SHMEM_LIMIT_DEFAULT:
+                    *limit = properties->sharedMemPerBlock;
+                    break;
+                case FUNC_SHMEM_LIMIT_OPTIN:
+                    if (smemPerCta > properties->sharedMemPerBlock) {
+                        *limit = properties->sharedMemPerBlockOptin;
+                    }
+                    else {
+                        *limit = properties->sharedMemPerBlock;
+                    }
+                    break;
+            }
+            break;
+        default:
+            return CUDA_OCC_ERROR_UNKNOWN_DEVICE;
+    }
+
+    // Starting Ampere, CUDA driver reserves additional shared memory per block
+    if (properties->computeMajor >= 8) {
+        *limit += properties->reservedSharedMemPerBlock;
+    }
+
+    return CUDA_OCC_SUCCESS;
+}
+
+/**
+ * Partitioned global caching mode support
+ */
+static __OCC_INLINE cudaOccError cudaOccPartitionedGlobalCachingModeSupport(cudaOccPartitionedGCSupport *limit, const cudaOccDeviceProp *properties)
+{
+    *limit = PARTITIONED_GC_NOT_SUPPORTED;
+
+    if ((properties->computeMajor == 5 && (properties->computeMinor == 2 || properties->computeMinor == 3)) ||
+        properties->computeMajor == 6) {
+        *limit = PARTITIONED_GC_SUPPORTED;
+    }
+
+    if (properties->computeMajor == 6 && properties->computeMinor == 0) {
+        *limit = PARTITIONED_GC_NOT_SUPPORTED;
+    }
+
+    return CUDA_OCC_SUCCESS;
+}
+
+///////////////////////////////////////////////
+//            User Input Sanity              //
+///////////////////////////////////////////////
+
+static __OCC_INLINE cudaOccError cudaOccDevicePropCheck(const cudaOccDeviceProp *properties)
+{
+    // Verify device properties
+    //
+    // Each of these limits must be a positive number.
+    //
+    // Compute capacity is checked during the occupancy calculation
+    //
+    if (properties->maxThreadsPerBlock          <= 0 ||
+        properties->maxThreadsPerMultiprocessor <= 0 ||
+        properties->regsPerBlock                <= 0 ||
+        properties->regsPerMultiprocessor       <= 0 ||
+        properties->warpSize                    <= 0 ||
+        properties->sharedMemPerBlock           <= 0 ||
+        properties->sharedMemPerMultiprocessor  <= 0 ||
+        properties->numSms                      <= 0) {
+        return CUDA_OCC_ERROR_INVALID_INPUT;
+    }
+
+    return CUDA_OCC_SUCCESS;
+}
+
+static __OCC_INLINE cudaOccError cudaOccFuncAttributesCheck(const cudaOccFuncAttributes *attributes)
+{
+    // Verify function attributes
+    //
+    if (attributes->maxThreadsPerBlock <= 0 ||
+        attributes->numRegs < 0) {            // Compiler may choose not to use
+                                              // any register (empty kernels,
+                                              // etc.)
+        return CUDA_OCC_ERROR_INVALID_INPUT;
+    }
+
+    return CUDA_OCC_SUCCESS;
+}
+
+static __OCC_INLINE cudaOccError cudaOccDeviceStateCheck(const cudaOccDeviceState *state)
+{
+    (void)state;   // silence unused-variable warning
+    // Placeholder
+    //
+
+    return CUDA_OCC_SUCCESS;
+}
+
+static __OCC_INLINE cudaOccError cudaOccInputCheck(
+    const cudaOccDeviceProp     *properties,
+    const cudaOccFuncAttributes *attributes,
+    const cudaOccDeviceState    *state)
+{
+    cudaOccError status = CUDA_OCC_SUCCESS;
+
+    status = cudaOccDevicePropCheck(properties);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    status = cudaOccFuncAttributesCheck(attributes);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    status = cudaOccDeviceStateCheck(state);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    return status;
+}
+
+///////////////////////////////////////////////
+//    Occupancy calculation Functions        //
+///////////////////////////////////////////////
+
+static __OCC_INLINE cudaOccPartitionedGCConfig cudaOccPartitionedGCExpected(
+    const cudaOccDeviceProp     *properties,
+    const cudaOccFuncAttributes *attributes)
+{
+    cudaOccPartitionedGCSupport gcSupport;
+    cudaOccPartitionedGCConfig gcConfig;
+
+    cudaOccPartitionedGlobalCachingModeSupport(&gcSupport, properties);
+
+    gcConfig = attributes->partitionedGCConfig;
+
+    if (gcSupport == PARTITIONED_GC_NOT_SUPPORTED) {
+        gcConfig = PARTITIONED_GC_OFF;
+    }
+
+    return gcConfig;
+}
+
+// Warp limit
+//
+static __OCC_INLINE cudaOccError cudaOccMaxBlocksPerSMWarpsLimit(
+    int                         *limit,
+    cudaOccPartitionedGCConfig   gcConfig,
+    const cudaOccDeviceProp     *properties,
+    const cudaOccFuncAttributes *attributes,
+    int                          blockSize)
+{
+    cudaOccError status = CUDA_OCC_SUCCESS;
+    int maxWarpsPerSm;
+    int warpsAllocatedPerCTA;
+    int maxBlocks;
+    (void)attributes;   // silence unused-variable warning
+
+    if (blockSize > properties->maxThreadsPerBlock) {
+        maxBlocks = 0;
+    }
+    else {
+        maxWarpsPerSm = properties->maxThreadsPerMultiprocessor / properties->warpSize;
+        warpsAllocatedPerCTA = __occDivideRoundUp(blockSize, properties->warpSize);
+        maxBlocks = 0;
+
+        if (gcConfig != PARTITIONED_GC_OFF) {
+            int maxBlocksPerSmPartition;
+            int maxWarpsPerSmPartition;
+
+            // If partitioned global caching is on, then a CTA can only use a SM
+            // partition (a half SM), and thus a half of the warp slots
+            // available per SM
+            //
+            maxWarpsPerSmPartition  = maxWarpsPerSm / 2;
+            maxBlocksPerSmPartition = maxWarpsPerSmPartition / warpsAllocatedPerCTA;
+            maxBlocks               = maxBlocksPerSmPartition * 2;
+        }
+        // On hardware that supports partitioned global caching, each half SM is
+        // guaranteed to support at least 32 warps (maximum number of warps of a
+        // CTA), so caching will not cause 0 occupancy due to insufficient warp
+        // allocation slots.
+        //
+        else {
+            maxBlocks = maxWarpsPerSm / warpsAllocatedPerCTA;
+        }
+    }
+
+    *limit = maxBlocks;
+
+    return status;
+}
+
+// Shared memory limit
+//
+static __OCC_INLINE cudaOccError cudaOccMaxBlocksPerSMSmemLimit(
+    int                         *limit,
+    cudaOccResult               *result,
+    const cudaOccDeviceProp     *properties,
+    const cudaOccFuncAttributes *attributes,
+    const cudaOccDeviceState    *state,
+    int                          blockSize,
+    size_t                       dynamicSmemSize)
+{
+    cudaOccError status = CUDA_OCC_SUCCESS;
+    int allocationGranularity;
+    size_t userSmemPreference = 0;
+    size_t totalSmemUsagePerCTA;
+    size_t maxSmemUsagePerCTA;
+    size_t smemAllocatedPerCTA;
+    size_t staticSmemSize;
+    size_t sharedMemPerMultiprocessor;
+    size_t smemLimitPerCTA;
+    int maxBlocks;
+    int dynamicSmemSizeExceeded = 0;
+    int totalSmemSizeExceeded = 0;
+    (void)blockSize;   // silence unused-variable warning
+
+    status = cudaOccSMemAllocationGranularity(&allocationGranularity, properties);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    // Obtain the user preferred shared memory size. This setting is ignored if
+    // user requests more shared memory than preferred.
+    //
+    status = cudaOccSMemPerMultiprocessor(&userSmemPreference, properties, state);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    staticSmemSize = attributes->sharedSizeBytes + properties->reservedSharedMemPerBlock;
+    totalSmemUsagePerCTA = staticSmemSize + dynamicSmemSize;
+    smemAllocatedPerCTA = __occRoundUp((int)totalSmemUsagePerCTA, (int)allocationGranularity);
+
+    maxSmemUsagePerCTA = staticSmemSize + attributes->maxDynamicSharedSizeBytes;
+
+    dynamicSmemSizeExceeded = 0;
+    totalSmemSizeExceeded   = 0;
+
+    // Obtain the user set maximum dynamic size if it exists
+    // If so, the current launch dynamic shared memory must not
+    // exceed the set limit
+    if (attributes->shmemLimitConfig != FUNC_SHMEM_LIMIT_DEFAULT &&
+        dynamicSmemSize > attributes->maxDynamicSharedSizeBytes) {
+        dynamicSmemSizeExceeded = 1;
+    }
+
+    status = cudaOccSMemPerBlock(&smemLimitPerCTA, properties, attributes->shmemLimitConfig, maxSmemUsagePerCTA);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    if (smemAllocatedPerCTA > smemLimitPerCTA) {
+        totalSmemSizeExceeded = 1;
+    }
+
+    if (dynamicSmemSizeExceeded || totalSmemSizeExceeded) {
+        maxBlocks = 0;
+    }
+    else {
+        // User requested shared memory limit is used as long as it is greater
+        // than the total shared memory used per CTA, i.e. as long as at least
+        // one CTA can be launched.
+        if (userSmemPreference >= smemAllocatedPerCTA) {
+            sharedMemPerMultiprocessor = userSmemPreference;
+        }
+        else {
+            // On Volta+, user requested shared memory will limit occupancy
+            // if it's less than shared memory per CTA. Otherwise, the
+            // maximum shared memory limit is used.
+            if (properties->computeMajor >= 7) {
+                sharedMemPerMultiprocessor = smemAllocatedPerCTA;
+                status = cudaOccAlignUpShmemSizeVoltaPlus(&sharedMemPerMultiprocessor, properties);
+                if (status != CUDA_OCC_SUCCESS) {
+                    return status;
+                }
+            }
+            else {
+                sharedMemPerMultiprocessor = properties->sharedMemPerMultiprocessor;
+            }
+        }
+
+        if (smemAllocatedPerCTA > 0) {
+            maxBlocks = (int)(sharedMemPerMultiprocessor / smemAllocatedPerCTA);
+        }
+        else {
+            maxBlocks = INT_MAX;
+        }
+    }
+
+    result->allocatedSharedMemPerBlock = smemAllocatedPerCTA;
+
+    *limit = maxBlocks;
+
+    return status;
+}
+
+static __OCC_INLINE
+cudaOccError cudaOccMaxBlocksPerSMRegsLimit(
+    int                         *limit,
+    cudaOccPartitionedGCConfig  *gcConfig,
+    cudaOccResult               *result,
+    const cudaOccDeviceProp     *properties,
+    const cudaOccFuncAttributes *attributes,
+    int                          blockSize)
+{
+    cudaOccError status = CUDA_OCC_SUCCESS;
+    int allocationGranularity;
+    int warpsAllocatedPerCTA;
+    int regsAllocatedPerCTA;
+    int regsAssumedPerCTA;
+    int regsPerWarp;
+    int regsAllocatedPerWarp;
+    int numSubPartitions;
+    int numRegsPerSubPartition;
+    int numWarpsPerSubPartition;
+    int numWarpsPerSM;
+    int maxBlocks;
+    int maxRegsPerThread;
+
+    status = cudaOccRegAllocationGranularity(
+        &allocationGranularity,
+        properties);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    status = cudaOccRegAllocationMaxPerThread(
+        &maxRegsPerThread,
+        properties);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    status = cudaOccSubPartitionsPerMultiprocessor(&numSubPartitions, properties);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    warpsAllocatedPerCTA = __occDivideRoundUp(blockSize, properties->warpSize);
+
+    // GPUs of compute capability 2.x and higher allocate registers to warps
+    //
+    // Number of regs per warp is regs per thread x warp size, rounded up to
+    // register allocation granularity
+    //
+    regsPerWarp          = attributes->numRegs * properties->warpSize;
+    regsAllocatedPerWarp = __occRoundUp(regsPerWarp, allocationGranularity);
+    regsAllocatedPerCTA  = regsAllocatedPerWarp * warpsAllocatedPerCTA;
+
+    // Hardware verifies if a launch fits the per-CTA register limit. For
+    // historical reasons, the verification logic assumes register
+    // allocations are made to all partitions simultaneously. Therefore, to
+    // simulate the hardware check, the warp allocation needs to be rounded
+    // up to the number of partitions.
+    //
+    regsAssumedPerCTA = regsAllocatedPerWarp * __occRoundUp(warpsAllocatedPerCTA, numSubPartitions);
+
+    if (properties->regsPerBlock < regsAssumedPerCTA ||   // Hardware check
+        properties->regsPerBlock < regsAllocatedPerCTA || // Software check
+        attributes->numRegs > maxRegsPerThread) {         // Per thread limit check
+        maxBlocks = 0;
+    }
+    else {
+        if (regsAllocatedPerWarp > 0) {
+            // Registers are allocated in each sub-partition. The max number
+            // of warps that can fit on an SM is equal to the max number of
+            // warps per sub-partition x number of sub-partitions.
+            //
+            numRegsPerSubPartition  = properties->regsPerMultiprocessor / numSubPartitions;
+            numWarpsPerSubPartition = numRegsPerSubPartition / regsAllocatedPerWarp;
+
+            maxBlocks = 0;
+
+            if (*gcConfig != PARTITIONED_GC_OFF) {
+                int numSubPartitionsPerSmPartition;
+                int numWarpsPerSmPartition;
+                int maxBlocksPerSmPartition;
+
+                // If partitioned global caching is on, then a CTA can only
+                // use a half SM, and thus a half of the registers available
+                // per SM
+                //
+                numSubPartitionsPerSmPartition = numSubPartitions / 2;
+                numWarpsPerSmPartition         = numWarpsPerSubPartition * numSubPartitionsPerSmPartition;
+                maxBlocksPerSmPartition        = numWarpsPerSmPartition / warpsAllocatedPerCTA;
+                maxBlocks                      = maxBlocksPerSmPartition * 2;
+            }
+
+            // Try again if partitioned global caching is not enabled, or if
+            // the CTA cannot fit on the SM with caching on (maxBlocks == 0).  In the latter
+            // case, the device will automatically turn off caching, except
+            // if the user forces enablement via PARTITIONED_GC_ON_STRICT to calculate
+            // occupancy and launch configuration.
+            //
+            if (maxBlocks == 0 && *gcConfig != PARTITIONED_GC_ON_STRICT) {
+               // In case *gcConfig was PARTITIONED_GC_ON flip it OFF since
+               // this is what it will be if we spread CTA across partitions.
+               //
+               *gcConfig = PARTITIONED_GC_OFF;
+               numWarpsPerSM = numWarpsPerSubPartition * numSubPartitions;
+               maxBlocks     = numWarpsPerSM / warpsAllocatedPerCTA;
+            }
+        }
+        else {
+            maxBlocks = INT_MAX;
+        }
+    }
+
+
+    result->allocatedRegistersPerBlock = regsAllocatedPerCTA;
+
+    *limit = maxBlocks;
+
+    return status;
+}
+
+// Barrier limit
+//
+static __OCC_INLINE cudaOccError cudaOccMaxBlocksPerSMBlockBarrierLimit(
+    int                         *limit,
+    int                          ctaLimitBlocks,
+    const cudaOccFuncAttributes *attributes)
+{
+    cudaOccError status = CUDA_OCC_SUCCESS;
+    int numBarriersAvailable = ctaLimitBlocks * 2;
+    int numBarriersUsed = attributes->numBlockBarriers;
+    int maxBlocks = INT_MAX;
+
+    if (numBarriersUsed) {
+        maxBlocks = numBarriersAvailable / numBarriersUsed;
+    }
+
+    *limit = maxBlocks;
+
+    return status;
+}
+
+///////////////////////////////////
+//      API Implementations      //
+///////////////////////////////////
+
+static __OCC_INLINE
+cudaOccError cudaOccMaxActiveBlocksPerMultiprocessor(
+    cudaOccResult               *result,
+    const cudaOccDeviceProp     *properties,
+    const cudaOccFuncAttributes *attributes,
+    const cudaOccDeviceState    *state,
+    int                          blockSize,
+    size_t                       dynamicSmemSize)
+{
+    cudaOccError status          = CUDA_OCC_SUCCESS;
+    int          ctaLimitWarps   = 0;
+    int          ctaLimitBlocks  = 0;
+    int          ctaLimitSMem    = 0;
+    int          ctaLimitRegs    = 0;
+    int          ctaLimitBars    = 0;
+    int          ctaLimit        = 0;
+    unsigned int limitingFactors = 0;
+    
+    cudaOccPartitionedGCConfig gcConfig = PARTITIONED_GC_OFF;
+
+    if (!result || !properties || !attributes || !state || blockSize <= 0) {
+        return CUDA_OCC_ERROR_INVALID_INPUT;
+    }
+
+    ///////////////////////////
+    // Check user input
+    ///////////////////////////
+
+    status = cudaOccInputCheck(properties, attributes, state);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    ///////////////////////////
+    // Initialization
+    ///////////////////////////
+
+    gcConfig = cudaOccPartitionedGCExpected(properties, attributes);
+
+    ///////////////////////////
+    // Compute occupancy
+    ///////////////////////////
+
+    // Limits due to registers/SM
+    // Also compute if partitioned global caching has to be turned off
+    //
+    status = cudaOccMaxBlocksPerSMRegsLimit(&ctaLimitRegs, &gcConfig, result, properties, attributes, blockSize);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    // SMs on GP100 (6.0) have 2 subpartitions, while those on GP10x have 4.
+    // As a result, an SM on GP100 may be able to run more CTAs than the one on GP10x.
+    // For forward compatibility within Pascal family, if a function cannot run on GP10x (maxBlock == 0),
+    // we do not let it run on any Pascal processor, even though it may be able to run on GP100.
+    // Therefore, we check the occupancy on GP10x when it can run on GP100
+    //
+    if (properties->computeMajor == 6 && properties->computeMinor == 0 && ctaLimitRegs) {
+        cudaOccDeviceProp propertiesGP10x;
+        cudaOccPartitionedGCConfig gcConfigGP10x = gcConfig;
+        int ctaLimitRegsGP10x = 0;
+
+        // Set up properties for GP10x
+        memcpy(&propertiesGP10x, properties, sizeof(propertiesGP10x));
+        propertiesGP10x.computeMinor = 1;
+
+        status = cudaOccMaxBlocksPerSMRegsLimit(&ctaLimitRegsGP10x, &gcConfigGP10x, result, &propertiesGP10x, attributes, blockSize);
+        if (status != CUDA_OCC_SUCCESS) {
+            return status;
+        }
+
+        if (ctaLimitRegsGP10x == 0) {
+            ctaLimitRegs = 0;
+        }
+    }
+
+    // Limits due to warps/SM
+    //
+    status = cudaOccMaxBlocksPerSMWarpsLimit(&ctaLimitWarps, gcConfig, properties, attributes, blockSize);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    // Limits due to blocks/SM
+    //
+    status = cudaOccMaxBlocksPerMultiprocessor(&ctaLimitBlocks, properties);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    // Limits due to shared memory/SM
+    //
+    status = cudaOccMaxBlocksPerSMSmemLimit(&ctaLimitSMem, result, properties, attributes, state, blockSize, dynamicSmemSize);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    ///////////////////////////
+    // Overall occupancy
+    ///////////////////////////
+
+    // Overall limit is min() of limits due to above reasons
+    //
+    ctaLimit = __occMin(ctaLimitRegs, __occMin(ctaLimitSMem, __occMin(ctaLimitWarps, ctaLimitBlocks)));
+
+    // Determine occupancy limiting factors
+    //
+    if (ctaLimit == ctaLimitWarps) {
+        limitingFactors |= OCC_LIMIT_WARPS;
+    }
+    if (ctaLimit == ctaLimitRegs) {
+        limitingFactors |= OCC_LIMIT_REGISTERS;
+    }
+    if (ctaLimit == ctaLimitSMem) {
+        limitingFactors |= OCC_LIMIT_SHARED_MEMORY;
+    }
+    if (ctaLimit == ctaLimitBlocks) {
+        limitingFactors |= OCC_LIMIT_BLOCKS;
+    }
+
+    // For Hopper onwards compute the limits to occupancy based on block barrier count
+    //
+    if (properties->computeMajor >= 9 && attributes->numBlockBarriers > 0) {
+        // Limits due to barrier/SM
+        //
+        status = cudaOccMaxBlocksPerSMBlockBarrierLimit(&ctaLimitBars, ctaLimitBlocks, attributes);
+        if (status != CUDA_OCC_SUCCESS) {
+            return status;
+        }
+
+        // Recompute overall limit based on barrier/SM
+        //
+        ctaLimit = __occMin(ctaLimitBars, ctaLimit);
+
+        // Determine if this is occupancy limiting factor
+        //
+        if (ctaLimit == ctaLimitBars) {
+            limitingFactors |= OCC_LIMIT_BARRIERS;
+        }
+    }
+    else {
+        ctaLimitBars = INT_MAX;
+    }
+
+    // Fill in the return values
+    //
+    result->limitingFactors = limitingFactors;
+
+    result->blockLimitRegs      = ctaLimitRegs;
+    result->blockLimitSharedMem = ctaLimitSMem;
+    result->blockLimitWarps     = ctaLimitWarps;
+    result->blockLimitBlocks    = ctaLimitBlocks;
+    result->blockLimitBarriers  = ctaLimitBars;
+    result->partitionedGCConfig = gcConfig;
+
+    // Final occupancy
+    result->activeBlocksPerMultiprocessor = ctaLimit;
+
+    return CUDA_OCC_SUCCESS;
+}
+
+static __OCC_INLINE
+cudaOccError cudaOccAvailableDynamicSMemPerBlock(
+    size_t                      *bytesAvailable,
+    const cudaOccDeviceProp     *properties,
+    const cudaOccFuncAttributes *attributes,
+    const cudaOccDeviceState    *state,
+    int                         numBlocks,
+    int                         blockSize)
+{
+    int allocationGranularity;
+    size_t smemLimitPerBlock;
+    size_t smemAvailableForDynamic;
+    size_t userSmemPreference = 0;
+    size_t sharedMemPerMultiprocessor;
+    cudaOccResult result;
+    cudaOccError status = CUDA_OCC_SUCCESS;
+
+    if (numBlocks <= 0)
+        return CUDA_OCC_ERROR_INVALID_INPUT;
+
+    // First compute occupancy of potential kernel launch.
+    //
+    status = cudaOccMaxActiveBlocksPerMultiprocessor(&result, properties, attributes, state, blockSize, 0);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+    // Check if occupancy is achievable given user requested number of blocks. 
+    //
+    if (result.activeBlocksPerMultiprocessor < numBlocks) {
+        return CUDA_OCC_ERROR_INVALID_INPUT;
+    }
+
+    status = cudaOccSMemAllocationGranularity(&allocationGranularity, properties);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    // Return the per block shared memory limit based on function config.
+    //
+    status = cudaOccSMemPerBlock(&smemLimitPerBlock, properties, attributes->shmemLimitConfig, properties->sharedMemPerMultiprocessor);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    // If there is only a single block needed per SM, then the user preference can be ignored and the fully SW
+    // limit is allowed to be used as shared memory otherwise if more than one block is needed, then the user
+    // preference sets the total limit of available shared memory.
+    //
+    cudaOccSMemPerMultiprocessor(&userSmemPreference, properties, state);
+    if (numBlocks == 1) {
+        sharedMemPerMultiprocessor = smemLimitPerBlock;
+    }
+    else {
+        if (!userSmemPreference) {
+            userSmemPreference = 1 ;
+            status = cudaOccAlignUpShmemSizeVoltaPlus(&userSmemPreference, properties);
+            if (status != CUDA_OCC_SUCCESS) {
+                return status;
+            }
+        }
+        sharedMemPerMultiprocessor = userSmemPreference;
+    }
+
+    // Compute total shared memory available per SM
+    //
+    smemAvailableForDynamic =  sharedMemPerMultiprocessor / numBlocks;
+    smemAvailableForDynamic = (smemAvailableForDynamic / allocationGranularity) * allocationGranularity;
+
+    // Cap shared memory
+    //
+    if (smemAvailableForDynamic > smemLimitPerBlock) {
+        smemAvailableForDynamic = smemLimitPerBlock;
+    }
+
+    // Now compute dynamic shared memory size
+    smemAvailableForDynamic = smemAvailableForDynamic - attributes->sharedSizeBytes; 
+
+    // Cap computed dynamic SM by user requested limit specified via cuFuncSetAttribute()
+    //
+    if (smemAvailableForDynamic > attributes->maxDynamicSharedSizeBytes)
+        smemAvailableForDynamic = attributes->maxDynamicSharedSizeBytes;
+
+    *bytesAvailable = smemAvailableForDynamic;
+    return CUDA_OCC_SUCCESS;
+}
+
+static __OCC_INLINE
+cudaOccError cudaOccMaxPotentialOccupancyBlockSize(
+    int                         *minGridSize,
+    int                         *blockSize,
+    const cudaOccDeviceProp     *properties,
+    const cudaOccFuncAttributes *attributes,
+    const cudaOccDeviceState    *state,
+    size_t                     (*blockSizeToDynamicSMemSize)(int),
+    size_t                       dynamicSMemSize)
+{
+    cudaOccError  status = CUDA_OCC_SUCCESS;
+    cudaOccResult result;
+
+    // Limits
+    int occupancyLimit;
+    int granularity;
+    int blockSizeLimit;
+
+    // Recorded maximum
+    int maxBlockSize = 0;
+    int numBlocks    = 0;
+    int maxOccupancy = 0;
+
+    // Temporary
+    int blockSizeToTryAligned;
+    int blockSizeToTry;
+    int blockSizeLimitAligned;
+    int occupancyInBlocks;
+    int occupancyInThreads;
+
+    ///////////////////////////
+    // Check user input
+    ///////////////////////////
+
+    if (!minGridSize || !blockSize || !properties || !attributes || !state) {
+        return CUDA_OCC_ERROR_INVALID_INPUT;
+    }
+
+    status = cudaOccInputCheck(properties, attributes, state);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    /////////////////////////////////////////////////////////////////////////////////
+    // Try each block size, and pick the block size with maximum occupancy
+    /////////////////////////////////////////////////////////////////////////////////
+
+    occupancyLimit = properties->maxThreadsPerMultiprocessor;
+    granularity    = properties->warpSize;
+
+    blockSizeLimit        = __occMin(properties->maxThreadsPerBlock, attributes->maxThreadsPerBlock);
+    blockSizeLimitAligned = __occRoundUp(blockSizeLimit, granularity);
+
+    for (blockSizeToTryAligned = blockSizeLimitAligned; blockSizeToTryAligned > 0; blockSizeToTryAligned -= granularity) {
+        blockSizeToTry = __occMin(blockSizeLimit, blockSizeToTryAligned);
+
+        // Ignore dynamicSMemSize if the user provides a mapping
+        //
+        if (blockSizeToDynamicSMemSize) {
+            dynamicSMemSize = (*blockSizeToDynamicSMemSize)(blockSizeToTry);
+        }
+
+        status = cudaOccMaxActiveBlocksPerMultiprocessor(
+            &result,
+            properties,
+            attributes,
+            state,
+            blockSizeToTry,
+            dynamicSMemSize);
+
+        if (status != CUDA_OCC_SUCCESS) {
+            return status;
+        }
+
+        occupancyInBlocks = result.activeBlocksPerMultiprocessor;
+        occupancyInThreads = blockSizeToTry * occupancyInBlocks;
+
+        if (occupancyInThreads > maxOccupancy) {
+            maxBlockSize = blockSizeToTry;
+            numBlocks    = occupancyInBlocks;
+            maxOccupancy = occupancyInThreads;
+        }
+
+        // Early out if we have reached the maximum
+        //
+        if (occupancyLimit == maxOccupancy) {
+            break;
+        }
+    }
+
+    ///////////////////////////
+    // Return best available
+    ///////////////////////////
+
+    // Suggested min grid size to achieve a full machine launch
+    //
+    *minGridSize = numBlocks * properties->numSms;
+    *blockSize = maxBlockSize;
+
+    return status;
+}
+
+
+#if defined(__cplusplus)
+
+namespace {
+
+__OCC_INLINE
+cudaOccError cudaOccMaxPotentialOccupancyBlockSize(
+    int                         *minGridSize,
+    int                         *blockSize,
+    const cudaOccDeviceProp     *properties,
+    const cudaOccFuncAttributes *attributes,
+    const cudaOccDeviceState    *state,
+    size_t                       dynamicSMemSize)
+{
+    return cudaOccMaxPotentialOccupancyBlockSize(
+        minGridSize,
+        blockSize,
+        properties,
+        attributes,
+        state,
+        NULL,
+        dynamicSMemSize);
+}
+
+template <typename UnaryFunction>
+__OCC_INLINE
+cudaOccError cudaOccMaxPotentialOccupancyBlockSizeVariableSMem(
+    int                         *minGridSize,
+    int                         *blockSize,
+    const cudaOccDeviceProp     *properties,
+    const cudaOccFuncAttributes *attributes,
+    const cudaOccDeviceState    *state,
+    UnaryFunction                blockSizeToDynamicSMemSize)
+{
+    cudaOccError  status = CUDA_OCC_SUCCESS;
+    cudaOccResult result;
+
+    // Limits
+    int occupancyLimit;
+    int granularity;
+    int blockSizeLimit;
+
+    // Recorded maximum
+    int maxBlockSize = 0;
+    int numBlocks    = 0;
+    int maxOccupancy = 0;
+
+    // Temporary
+    int blockSizeToTryAligned;
+    int blockSizeToTry;
+    int blockSizeLimitAligned;
+    int occupancyInBlocks;
+    int occupancyInThreads;
+    size_t dynamicSMemSize;
+
+    ///////////////////////////
+    // Check user input
+    ///////////////////////////
+
+    if (!minGridSize || !blockSize || !properties || !attributes || !state) {
+        return CUDA_OCC_ERROR_INVALID_INPUT;
+    }
+
+    status = cudaOccInputCheck(properties, attributes, state);
+    if (status != CUDA_OCC_SUCCESS) {
+        return status;
+    }
+
+    /////////////////////////////////////////////////////////////////////////////////
+    // Try each block size, and pick the block size with maximum occupancy
+    /////////////////////////////////////////////////////////////////////////////////
+
+    occupancyLimit = properties->maxThreadsPerMultiprocessor;
+    granularity    = properties->warpSize;
+    blockSizeLimit        = __occMin(properties->maxThreadsPerBlock, attributes->maxThreadsPerBlock);
+    blockSizeLimitAligned = __occRoundUp(blockSizeLimit, granularity);
+
+    for (blockSizeToTryAligned = blockSizeLimitAligned; blockSizeToTryAligned > 0; blockSizeToTryAligned -= granularity) {
+        blockSizeToTry = __occMin(blockSizeLimit, blockSizeToTryAligned);
+
+        dynamicSMemSize = blockSizeToDynamicSMemSize(blockSizeToTry);
+
+        status = cudaOccMaxActiveBlocksPerMultiprocessor(
+            &result,
+            properties,
+            attributes,
+            state,
+            blockSizeToTry,
+            dynamicSMemSize);
+
+        if (status != CUDA_OCC_SUCCESS) {
+            return status;
+        }
+
+        occupancyInBlocks = result.activeBlocksPerMultiprocessor;
+
+        occupancyInThreads = blockSizeToTry * occupancyInBlocks;
+
+        if (occupancyInThreads > maxOccupancy) {
+            maxBlockSize = blockSizeToTry;
+            numBlocks    = occupancyInBlocks;
+            maxOccupancy = occupancyInThreads;
+        }
+
+        // Early out if we have reached the maximum
+        //
+        if (occupancyLimit == maxOccupancy) {
+            break;
+        }
+    }
+
+    ///////////////////////////
+    // Return best available
+    ///////////////////////////
+
+    // Suggested min grid size to achieve a full machine launch
+    //
+    *minGridSize = numBlocks * properties->numSms;
+    *blockSize = maxBlockSize;
+
+    return status;
+}
+
+} // namespace anonymous
+
+#endif /*__cplusplus */
+
+#undef __OCC_INLINE
+
+#endif /*__cuda_occupancy_h__*/

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cuda_vdpau_interop.h

@@ -0,0 +1,201 @@
+/*
+ * Copyright 1993-2012 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__CUDA_VDPAU_INTEROP_H__)
+#define __CUDA_VDPAU_INTEROP_H__
+
+#include "cuda_runtime_api.h"
+
+#include <vdpau/vdpau.h>
+
+#if defined(__cplusplus)
+extern "C" {
+#endif /* __cplusplus */
+
+/**
+ * \addtogroup CUDART_VDPAU VDPAU Interoperability
+ * This section describes the VDPAU interoperability functions of the CUDA
+ * runtime application programming interface.
+ *
+ * @{
+ */
+
+/**
+ * \brief Gets the CUDA device associated with a VdpDevice.
+ *
+ * Returns the CUDA device associated with a VdpDevice, if applicable.
+ *
+ * \param device - Returns the device associated with vdpDevice, or -1 if
+ * the device associated with vdpDevice is not a compute device.
+ * \param vdpDevice - A VdpDevice handle
+ * \param vdpGetProcAddress - VDPAU's VdpGetProcAddress function pointer
+ *
+ * \return
+ * ::cudaSuccess
+ * \notefnerr
+ *
+ * \sa
+ * ::cudaVDPAUSetVDPAUDevice,
+ * ::cuVDPAUGetDevice
+ */
+extern __host__ cudaError_t CUDARTAPI cudaVDPAUGetDevice(int *device, VdpDevice vdpDevice, VdpGetProcAddress *vdpGetProcAddress);
+
+/**
+ * \brief Sets a CUDA device to use VDPAU interoperability
+ *
+ * Records \p vdpDevice as the VdpDevice for VDPAU interoperability 
+ * with the CUDA device \p device and sets \p device as the current 
+ * device for the calling host thread.
+ *
+ * This function will immediately initialize the primary context on 
+ * \p device if needed.
+ *
+ * If \p device has already been initialized then this call will fail 
+ * with the error ::cudaErrorSetOnActiveProcess.  In this case it is 
+ * necessary to reset \p device using ::cudaDeviceReset() before 
+ * VDPAU interoperability on \p device may be enabled.
+ *
+ * \param device - Device to use for VDPAU interoperability
+ * \param vdpDevice - The VdpDevice to interoperate with
+ * \param vdpGetProcAddress - VDPAU's VdpGetProcAddress function pointer
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidDevice,
+ * ::cudaErrorSetOnActiveProcess
+ * \notefnerr
+ *
+ * \sa ::cudaGraphicsVDPAURegisterVideoSurface,
+ * ::cudaGraphicsVDPAURegisterOutputSurface,
+ * ::cudaDeviceReset
+ */
+extern __host__ cudaError_t CUDARTAPI cudaVDPAUSetVDPAUDevice(int device, VdpDevice vdpDevice, VdpGetProcAddress *vdpGetProcAddress);
+
+/**
+ * \brief Register a VdpVideoSurface object
+ *
+ * Registers the VdpVideoSurface specified by \p vdpSurface for access by CUDA.
+ * A handle to the registered object is returned as \p resource.
+ * The surface's intended usage is specified using \p flags, as follows:
+ *
+ * - ::cudaGraphicsMapFlagsNone: Specifies no hints about how this
+ *   resource will be used. It is therefore assumed that this resource will be
+ *   read from and written to by CUDA. This is the default value.
+ * - ::cudaGraphicsMapFlagsReadOnly: Specifies that CUDA
+ *   will not write to this resource.
+ * - ::cudaGraphicsMapFlagsWriteDiscard: Specifies that
+ *   CUDA will not read from this resource and will write over the
+ *   entire contents of the resource, so none of the data previously
+ *   stored in the resource will be preserved.
+ *
+ * \param resource - Pointer to the returned object handle
+ * \param vdpSurface - VDPAU object to be registered
+ * \param flags - Map flags
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidDevice,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorInvalidResourceHandle,
+ * ::cudaErrorUnknown
+ * \notefnerr
+ *
+ * \sa
+ * ::cudaVDPAUSetVDPAUDevice,
+ * ::cudaGraphicsUnregisterResource,
+ * ::cudaGraphicsSubResourceGetMappedArray,
+ * ::cuGraphicsVDPAURegisterVideoSurface
+ */
+extern __host__ cudaError_t CUDARTAPI cudaGraphicsVDPAURegisterVideoSurface(struct cudaGraphicsResource **resource, VdpVideoSurface vdpSurface, unsigned int flags);
+
+/**
+ * \brief Register a VdpOutputSurface object
+ *
+ * Registers the VdpOutputSurface specified by \p vdpSurface for access by CUDA.
+ * A handle to the registered object is returned as \p resource.
+ * The surface's intended usage is specified using \p flags, as follows:
+ *
+ * - ::cudaGraphicsMapFlagsNone: Specifies no hints about how this
+ *   resource will be used. It is therefore assumed that this resource will be
+ *   read from and written to by CUDA. This is the default value.
+ * - ::cudaGraphicsMapFlagsReadOnly: Specifies that CUDA
+ *   will not write to this resource.
+ * - ::cudaGraphicsMapFlagsWriteDiscard: Specifies that
+ *   CUDA will not read from this resource and will write over the
+ *   entire contents of the resource, so none of the data previously
+ *   stored in the resource will be preserved.
+ *
+ * \param resource - Pointer to the returned object handle
+ * \param vdpSurface - VDPAU object to be registered
+ * \param flags - Map flags
+ *
+ * \return
+ * ::cudaSuccess,
+ * ::cudaErrorInvalidDevice,
+ * ::cudaErrorInvalidValue,
+ * ::cudaErrorInvalidResourceHandle,
+ * ::cudaErrorUnknown
+ * \notefnerr
+ *
+ * \sa
+ * ::cudaVDPAUSetVDPAUDevice,
+ * ::cudaGraphicsUnregisterResource,
+ * ::cudaGraphicsSubResourceGetMappedArray,
+ * ::cuGraphicsVDPAURegisterOutputSurface
+ */
+extern __host__ cudaError_t CUDARTAPI cudaGraphicsVDPAURegisterOutputSurface(struct cudaGraphicsResource **resource, VdpOutputSurface vdpSurface, unsigned int flags);
+
+/** @} */ /* END CUDART_VDPAU */
+
+#if defined(__cplusplus)
+}
+#endif /* __cplusplus */
+
+#endif /* __CUDA_VDPAU_INTEROP_H__ */
+

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cudart_platform.h

@@ -0,0 +1,57 @@
+/*
+ * Copyright 2016 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#ifndef __CUDART_PLATFORM_H__
+#define __CUDART_PLATFORM_H__
+
+#if ((defined(__linux__) || defined(__QNX__)) && (defined(__arm__) || defined(__aarch64__) || defined(__x86_64__)))
+#define isEglSupported 1
+#endif
+
+#endif

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/device_atomic_functions.hpp

@@ -0,0 +1,224 @@
+/*
+ * Copyright 1993-2014 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__DEVICE_ATOMIC_FUNCTIONS_HPP__)
+#define __DEVICE_ATOMIC_FUNCTIONS_HPP__
+
+#if defined(__CUDACC_RTC__)
+#define __DEVICE_ATOMIC_FUNCTIONS_DECL__ __device__
+#else /* __CUDACC_RTC__ */
+#define __DEVICE_ATOMIC_FUNCTIONS_DECL__ static __inline__ __device__
+#endif /* __CUDACC_RTC__ */
+
+#if defined(__cplusplus) && defined(__CUDACC__)
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+#include "cuda_runtime_api.h"
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ int atomicAdd(int *address, int val)
+{
+  return __iAtomicAdd(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ unsigned int atomicAdd(unsigned int *address, unsigned int val)
+{
+  return __uAtomicAdd(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ int atomicSub(int *address, int val)
+{
+  return __iAtomicAdd(address, (unsigned int)-(int)val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ unsigned int atomicSub(unsigned int *address, unsigned int val)
+{
+  return __uAtomicAdd(address, (unsigned int)-(int)val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ int atomicExch(int *address, int val)
+{
+  return __iAtomicExch(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ unsigned int atomicExch(unsigned int *address, unsigned int val)
+{
+  return __uAtomicExch(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ float atomicExch(float *address, float val)
+{
+  return __fAtomicExch(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ int atomicMin(int *address, int val)
+{
+  return __iAtomicMin(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ unsigned int atomicMin(unsigned int *address, unsigned int val)
+{
+  return __uAtomicMin(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ int atomicMax(int *address, int val)
+{
+  return __iAtomicMax(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ unsigned int atomicMax(unsigned int *address, unsigned int val)
+{
+  return __uAtomicMax(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ unsigned int atomicInc(unsigned int *address, unsigned int val)
+{
+  return __uAtomicInc(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ unsigned int atomicDec(unsigned int *address, unsigned int val)
+{
+  return __uAtomicDec(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ int atomicAnd(int *address, int val)
+{
+  return __iAtomicAnd(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ unsigned int atomicAnd(unsigned int *address, unsigned int val)
+{
+  return __uAtomicAnd(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ int atomicOr(int *address, int val)
+{
+  return __iAtomicOr(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ unsigned int atomicOr(unsigned int *address, unsigned int val)
+{
+  return __uAtomicOr(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ int atomicXor(int *address, int val)
+{
+  return __iAtomicXor(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ unsigned int atomicXor(unsigned int *address, unsigned int val)
+{
+  return __uAtomicXor(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ int atomicCAS(int *address, int compare, int val)
+{
+  return __iAtomicCAS(address, compare, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ unsigned int atomicCAS(unsigned int *address, unsigned int compare, unsigned int val)
+{
+  return __uAtomicCAS(address, compare, val);
+}
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+#include "cuda_runtime_api.h"
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ unsigned long long int atomicAdd(unsigned long long int *address, unsigned long long int val)
+{
+  return __ullAtomicAdd(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ unsigned long long int atomicExch(unsigned long long int *address, unsigned long long int val)
+{
+  return __ullAtomicExch(address, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ unsigned long long int atomicCAS(unsigned long long int *address, unsigned long long int compare, unsigned long long int val)
+{
+  return __ullAtomicCAS(address, compare, val);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ bool any(bool cond)
+{
+  return (bool)__any((int)cond);
+}
+
+__DEVICE_ATOMIC_FUNCTIONS_DECL__ bool all(bool cond)
+{
+  return (bool)__all((int)cond);
+}
+
+#endif /* __cplusplus && __CUDACC__ */
+
+#undef __DEVICE_ATOMIC_FUNCTIONS_DECL__
+
+#endif /* !__DEVICE_ATOMIC_FUNCTIONS_HPP__ */
+

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/device_functions.h

@@ -0,0 +1,65 @@
+/*
+ * Copyright 1993-2018 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__)
+#if defined(_MSC_VER)
+#pragma message("device_functions.h is an internal header file and must not be used directly.  This file will be removed in a future CUDA release.  Please use cuda_runtime_api.h or cuda_runtime.h instead.")
+#else
+#warning "device_functions.h is an internal header file and must not be used directly.  This file will be removed in a future CUDA release.  Please use cuda_runtime_api.h or cuda_runtime.h instead."
+#endif
+#define __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
+#define __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_DEVICE_FUNCTIONS_H_WRAPPER__
+#endif
+
+#include "crt/device_functions.h"
+
+#if defined(__UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_DEVICE_FUNCTIONS_H_WRAPPER__)
+#undef __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
+#undef __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_DEVICE_FUNCTIONS_H_WRAPPER__
+#endif

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/device_types.h

@@ -0,0 +1,81 @@
+/*
+ * Copyright 1993-2018 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__DEVICE_TYPES_H__)
+#define __DEVICE_TYPES_H__
+
+#if !defined(__CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__)
+#define __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
+#define __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_DEVICE_TYPES_H__
+#endif
+
+#ifndef __DOXYGEN_ONLY__
+#include "crt/host_defines.h"
+#endif
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+enum __device_builtin__ cudaRoundMode
+{
+    cudaRoundNearest,
+    cudaRoundZero,
+    cudaRoundPosInf,
+    cudaRoundMinInf
+};
+
+#if defined(__UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_DEVICE_TYPES_H__)
+#undef __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
+#undef __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_DEVICE_TYPES_H__
+#endif
+
+#endif /* !__DEVICE_TYPES_H__ */

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/host_defines.h

@@ -0,0 +1,65 @@
+/*
+ * Copyright 1993-2018 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__)
+#if defined(_MSC_VER)
+#pragma message("host_defines.h is an internal header file and must not be used directly.  This file will be removed in a future CUDA release.  Please use cuda_runtime_api.h or cuda_runtime.h instead.")
+#else
+#warning "host_defines.h is an internal header file and must not be used directly.  This file will be removed in a future CUDA release.  Please use cuda_runtime_api.h or cuda_runtime.h instead."
+#endif
+#define __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
+#define __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_HOST_DEFINES_H_WRAPPER__
+#endif
+
+#include "crt/host_defines.h"
+
+#if defined(__UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_HOST_DEFINES_H_WRAPPER__)
+#undef __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
+#undef __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_HOST_DEFINES_H_WRAPPER__
+#endif

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/math_functions.h

@@ -0,0 +1,65 @@
+/*
+ * Copyright 1993-2018 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__)
+#if defined(_MSC_VER)
+#pragma message("math_functions.h is an internal header file and must not be used directly.  This file will be removed in a future CUDA release.  Please use cuda_runtime_api.h or cuda_runtime.h instead.")
+#else
+#warning "math_functions.h is an internal header file and must not be used directly.  This file will be removed in a future CUDA release.  Please use cuda_runtime_api.h or cuda_runtime.h instead."
+#endif
+#define __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
+#define __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_MATH_FUNCTIONS_H_WRAPPER__
+#endif
+
+#include "crt/math_functions.h"
+
+#if defined(__UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_MATH_FUNCTIONS_H_WRAPPER__)
+#undef __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
+#undef __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_MATH_FUNCTIONS_H_WRAPPER__
+#endif

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/mma.h

@@ -0,0 +1,60 @@
+/*
+ * Copyright 1993-2018 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__)
+#define __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
+#define __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_CUDA_MMA_H_WRAPPER__
+#endif
+
+#include "crt/mma.h"
+
+#if defined(__UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_CUDA_MMA_H_WRAPPER__)
+#undef __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
+#undef __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_CUDA_MMA_H_WRAPPER__
+#endif

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/sm_20_atomic_functions.h

@@ -0,0 +1,114 @@
+/*
+ * Copyright 1993-2014 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__SM_20_ATOMIC_FUNCTIONS_H__)
+#define __SM_20_ATOMIC_FUNCTIONS_H__
+
+#if defined(__CUDACC_RTC__)
+#define __SM_20_ATOMIC_FUNCTIONS_DECL__ __device__
+#elif defined(_NVHPC_CUDA)
+#define __SM_20_ATOMIC_FUNCTIONS_DECL__ extern __device__ __cudart_builtin__
+#else /* __CUDACC_RTC__ */
+#define __SM_20_ATOMIC_FUNCTIONS_DECL__ static __inline__ __device__
+#endif /* __CUDACC_RTC__ */
+
+#if defined(__cplusplus) && defined(__CUDACC__)
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+#include "cuda_runtime_api.h"
+
+#if defined(_NVHPC_CUDA)
+#undef __device_builtin__
+#define __device_builtin__ __location__(device) __location__(host)
+#endif /* _NVHPC_CUDA */
+
+/* Add !defined(_NVHPC_CUDA) to avoid empty function definition in CUDA
+ * C++ compiler where the macro __CUDA_ARCH__ is not defined. */
+#if !defined(__CUDA_ARCH__) && !defined(_NVHPC_CUDA)
+#define __DEF_IF_HOST { }
+#else  /* !__CUDA_ARCH__ */
+#define __DEF_IF_HOST ;
+#endif /* __CUDA_ARCH__ */
+
+
+#if defined(__CUDA_ARCH__) || defined(_NVHPC_CUDA)
+extern "C"
+{
+extern __device__ __device_builtin__ float __fAtomicAdd(float *address, float val);
+}
+#endif /* __CUDA_ARCH__ */
+
+#if defined(_NVHPC_CUDA)
+#undef __device_builtin__
+#define __device_builtin__
+#endif /* _NVHPC_CUDA */
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+__SM_20_ATOMIC_FUNCTIONS_DECL__ float atomicAdd(float *address, float val) __DEF_IF_HOST
+
+#endif /* __cplusplus && __CUDACC__ */
+
+#undef __DEF_IF_HOST
+#undef __SM_20_ATOMIC_FUNCTIONS_DECL__
+
+#if !defined(__CUDACC_RTC__) && (defined(__CUDA_ARCH__) || defined(_NVHPC_CUDA))
+#include "sm_20_atomic_functions.hpp"
+#endif /* !__CUDACC_RTC__ && defined(__CUDA_ARCH__) || defined(_NVHPC_CUDA) */
+
+#endif /* !__SM_20_ATOMIC_FUNCTIONS_H__ */

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/sm_30_intrinsics.h

@@ -0,0 +1,221 @@
+/*
+ * Copyright 1993-2014 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__SM_30_INTRINSICS_H__)
+#define __SM_30_INTRINSICS_H__
+
+#if defined(__CUDACC_RTC__)
+#define __SM_30_INTRINSICS_DECL__ __device__
+#elif defined(_NVHPC_CUDA)
+#define __SM_30_INTRINSICS_DECL__ extern __device__ __cudart_builtin__
+#else /* !__CUDACC_RTC__ */
+#define __SM_30_INTRINSICS_DECL__ static __device__ __inline__
+#endif /* __CUDACC_RTC__ */
+
+#if defined(__cplusplus) && defined(__CUDACC__)
+
+#if defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 300
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+#include "cuda_runtime_api.h"
+
+/* Add !defined(_NVHPC_CUDA) to avoid empty function definition in CUDA
+ * C++ compiler where the macro __CUDA_ARCH__ is not defined. */
+#if !defined(__CUDA_ARCH__) && !defined(_NVHPC_CUDA)
+#define __DEF_IF_HOST { }
+#else  /* !__CUDA_ARCH__ */
+#define __DEF_IF_HOST ;
+#endif /* __CUDA_ARCH__ */
+
+
+/*******************************************************************************
+*                                                                              *
+*  Below are declarations of SM-3.0 intrinsics which are included as           *
+*  source (instead of being built in to the compiler)                          *
+*                                                                              *
+*******************************************************************************/
+
+#if !defined warpSize && !defined __local_warpSize
+#define warpSize    32
+#define __local_warpSize
+#endif
+
+#if defined(_WIN32)
+# define __DEPRECATED__(msg) __declspec(deprecated(msg))
+#elif (defined(__GNUC__) && (__GNUC__ < 4 || (__GNUC__ == 4 && __GNUC_MINOR__ < 5 && !defined(__clang__))))
+# define __DEPRECATED__(msg) __attribute__((deprecated))
+#else
+# define __DEPRECATED__(msg) __attribute__((deprecated(msg)))
+#endif
+
+#if defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || __CUDA_ARCH__ < 700
+#define __WSB_DEPRECATION_MESSAGE(x) #x"() is deprecated in favor of "#x"_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning)."
+#elif defined(_NVHPC_CUDA)
+#define __WSB_DEPRECATION_MESSAGE(x) #x"() is not valid on cc70 and above, and should be replaced with "#x"_sync()."
+#endif
+
+__SM_30_INTRINSICS_DECL__ unsigned  __fns(unsigned mask, unsigned base, int offset) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ void  __barrier_sync(unsigned id) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ void  __barrier_sync_count(unsigned id, unsigned cnt) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ void  __syncwarp(unsigned mask=0xFFFFFFFF) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ int __all_sync(unsigned mask, int pred) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ int __any_sync(unsigned mask, int pred) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ int __uni_sync(unsigned mask, int pred) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ unsigned __ballot_sync(unsigned mask, int pred) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ unsigned __activemask() __DEF_IF_HOST
+
+// Warp register exchange (shuffle) intrinsics.
+// Notes:
+// a) Warp size is hardcoded to 32 here, because the compiler does not know
+//    the "warpSize" constant at this time
+// b) we cannot map the float __shfl to the int __shfl because it'll mess with
+//    the register number (especially if you're doing two shfls to move a double).
+#if defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || __CUDA_ARCH__ < 700
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl)) int __shfl(int var, int srcLane, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl)) unsigned int __shfl(unsigned int var, int srcLane, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_up)) int __shfl_up(int var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_up)) unsigned int __shfl_up(unsigned int var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_down)) int __shfl_down(int var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_down)) unsigned int __shfl_down(unsigned int var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_xor)) int __shfl_xor(int var, int laneMask, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_xor)) unsigned int __shfl_xor(unsigned int var, int laneMask, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl)) float __shfl(float var, int srcLane, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_up)) float __shfl_up(float var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_down)) float __shfl_down(float var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_xor)) float __shfl_xor(float var, int laneMask, int width=warpSize) __DEF_IF_HOST
+#endif
+
+__SM_30_INTRINSICS_DECL__ int __shfl_sync(unsigned mask, int var, int srcLane, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ unsigned int __shfl_sync(unsigned mask, unsigned int var, int srcLane, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ int __shfl_up_sync(unsigned mask, int var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ unsigned int __shfl_up_sync(unsigned mask, unsigned int var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ int __shfl_down_sync(unsigned mask, int var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ unsigned int __shfl_down_sync(unsigned mask, unsigned int var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ int __shfl_xor_sync(unsigned mask, int var, int laneMask, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ unsigned int __shfl_xor_sync(unsigned mask, unsigned int var, int laneMask, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ float __shfl_sync(unsigned mask, float var, int srcLane, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ float __shfl_up_sync(unsigned mask, float var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ float __shfl_down_sync(unsigned mask, float var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ float __shfl_xor_sync(unsigned mask, float var, int laneMask, int width=warpSize) __DEF_IF_HOST
+
+// 64-bits SHFL
+#if defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || __CUDA_ARCH__ < 700
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl)) unsigned long long __shfl(unsigned long long var, int srcLane, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl)) long long __shfl(long long var, int srcLane, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_up)) long long __shfl_up(long long var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_up)) unsigned long long __shfl_up(unsigned long long var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_down)) long long __shfl_down(long long var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_down)) unsigned long long __shfl_down(unsigned long long var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_xor)) long long __shfl_xor(long long var, int laneMask, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_xor)) unsigned long long __shfl_xor(unsigned long long var, int laneMask, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl)) double __shfl(double var, int srcLane, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_up)) double __shfl_up(double var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_down)) double __shfl_down(double var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_xor)) double __shfl_xor(double var, int laneMask, int width=warpSize) __DEF_IF_HOST
+#endif
+
+__SM_30_INTRINSICS_DECL__ long long __shfl_sync(unsigned mask, long long var, int srcLane, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ unsigned long long __shfl_sync(unsigned mask, unsigned long long var, int srcLane, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ long long __shfl_up_sync(unsigned mask, long long var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ unsigned long long __shfl_up_sync(unsigned mask, unsigned long long var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ long long __shfl_down_sync(unsigned mask, long long var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ unsigned long long __shfl_down_sync(unsigned mask, unsigned long long var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ long long __shfl_xor_sync(unsigned mask, long long var, int laneMask, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ unsigned long long __shfl_xor_sync(unsigned mask, unsigned long long var, int laneMask, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ double __shfl_sync(unsigned mask, double var, int srcLane, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ double __shfl_up_sync(unsigned mask, double var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ double __shfl_down_sync(unsigned mask, double var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ double __shfl_xor_sync(unsigned mask, double var, int laneMask, int width=warpSize) __DEF_IF_HOST
+
+// long needs some help to choose between 32-bits and 64-bits
+#if defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || __CUDA_ARCH__ < 700
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl)) long __shfl(long var, int srcLane, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl)) unsigned long __shfl(unsigned long var, int srcLane, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_up)) long __shfl_up(long var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_up)) unsigned long __shfl_up(unsigned long var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_down)) long __shfl_down(long var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_down)) unsigned long __shfl_down(unsigned long var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_xor)) long __shfl_xor(long var, int laneMask, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ __DEPRECATED__(__WSB_DEPRECATION_MESSAGE(__shfl_xor)) unsigned long __shfl_xor(unsigned long var, int laneMask, int width=warpSize) __DEF_IF_HOST
+#endif
+
+__SM_30_INTRINSICS_DECL__ long __shfl_sync(unsigned mask, long var, int srcLane, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ unsigned long __shfl_sync(unsigned mask, unsigned long var, int srcLane, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ long __shfl_up_sync(unsigned mask, long var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ unsigned long __shfl_up_sync(unsigned mask, unsigned long var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ long __shfl_down_sync(unsigned mask, long var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ unsigned long __shfl_down_sync(unsigned mask, unsigned long var, unsigned int delta, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ long __shfl_xor_sync(unsigned mask, long var, int laneMask, int width=warpSize) __DEF_IF_HOST
+__SM_30_INTRINSICS_DECL__ unsigned long __shfl_xor_sync(unsigned mask, unsigned long var, int laneMask, int width=warpSize) __DEF_IF_HOST
+
+#undef __DEPRECATED__
+#undef __WSB_DEPRECATION_MESSAGE
+
+#if defined(__local_warpSize)
+#undef warpSize
+#undef __local_warpSize
+#endif
+
+#endif /* !__CUDA_ARCH__ || __CUDA_ARCH__ >= 300 */
+
+#endif /* __cplusplus && __CUDACC__ */
+
+#undef __DEF_IF_HOST
+#undef __SM_30_INTRINSICS_DECL__
+
+#if !defined(__CUDACC_RTC__) && defined(__CUDA_ARCH__)
+#include "sm_30_intrinsics.hpp"
+#endif /* !__CUDACC_RTC__ && defined(__CUDA_ARCH__) */
+
+#endif /* !__SM_30_INTRINSICS_H__ */

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/sm_30_intrinsics.hpp

@@ -0,0 +1,604 @@
+/*
+ * Copyright 1993-2014 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__SM_30_INTRINSICS_HPP__)
+#define __SM_30_INTRINSICS_HPP__
+
+#if defined(__CUDACC_RTC__)
+#define __SM_30_INTRINSICS_DECL__ __device__
+#else /* !__CUDACC_RTC__ */
+#define __SM_30_INTRINSICS_DECL__ static __device__ __inline__
+#endif /* __CUDACC_RTC__ */
+
+#if defined(__cplusplus) && defined(__CUDACC__)
+
+#if defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 300
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+#include "cuda_runtime_api.h"
+
+// In here are intrinsics which are built in to the compiler. These may be
+// referenced by intrinsic implementations from this file.
+extern "C"
+{
+}
+
+/*******************************************************************************
+*                                                                              *
+*  Below are implementations of SM-3.0 intrinsics which are included as        *
+*  source (instead of being built in to the compiler)                          *
+*                                                                              *
+*******************************************************************************/
+
+#if !defined warpSize && !defined __local_warpSize
+#define warpSize    32
+#define __local_warpSize
+#endif
+
+__SM_30_INTRINSICS_DECL__
+unsigned __fns(unsigned mask, unsigned base, int offset) {
+  extern __device__ __device_builtin__ unsigned int __nvvm_fns(unsigned int mask, unsigned int base, int offset);
+  return __nvvm_fns(mask, base, offset);
+}
+
+__SM_30_INTRINSICS_DECL__ 
+void  __barrier_sync(unsigned id) {
+  extern __device__ __device_builtin__ void __nvvm_barrier_sync(unsigned id);
+  return __nvvm_barrier_sync(id);
+}
+
+__SM_30_INTRINSICS_DECL__ 
+void  __barrier_sync_count(unsigned id, unsigned cnt) {
+  extern __device__ __device_builtin__ void __nvvm_barrier_sync_cnt(unsigned id, unsigned cnt);
+  return __nvvm_barrier_sync_cnt(id, cnt);
+}
+
+__SM_30_INTRINSICS_DECL__ 
+void  __syncwarp(unsigned mask) {
+  extern __device__ __device_builtin__ void __nvvm_bar_warp_sync(unsigned mask);
+  return __nvvm_bar_warp_sync(mask);
+}
+
+__SM_30_INTRINSICS_DECL__ 
+int __all_sync(unsigned mask, int pred) {
+  extern __device__ __device_builtin__ int __nvvm_vote_all_sync(unsigned int mask, int pred); 
+  return __nvvm_vote_all_sync(mask, pred);
+}
+
+__SM_30_INTRINSICS_DECL__ 
+int __any_sync(unsigned mask, int pred) {
+  extern __device__ __device_builtin__ int __nvvm_vote_any_sync(unsigned int mask, int pred); 
+  return __nvvm_vote_any_sync(mask, pred);
+}
+
+__SM_30_INTRINSICS_DECL__ 
+int __uni_sync(unsigned mask, int pred) {
+  extern __device__ __device_builtin__ int __nvvm_vote_uni_sync(unsigned int mask, int pred); 
+  return __nvvm_vote_uni_sync(mask, pred);
+}
+
+__SM_30_INTRINSICS_DECL__ 
+unsigned __ballot_sync(unsigned mask, int pred) {
+  extern __device__ __device_builtin__ unsigned int __nvvm_vote_ballot_sync(unsigned int mask, int pred); 
+  return __nvvm_vote_ballot_sync(mask, pred);
+}
+
+__SM_30_INTRINSICS_DECL__
+unsigned __activemask() {
+    unsigned ret;
+    asm volatile ("activemask.b32 %0;" : "=r"(ret));
+    return ret;
+}
+
+// These are removed starting with compute_70 and onwards
+#if defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || __CUDA_ARCH__ < 700
+
+__SM_30_INTRINSICS_DECL__ int __shfl(int var, int srcLane, int width) {
+	int ret;
+	int c = ((warpSize-width) << 8) | 0x1f;
+	asm volatile ("shfl.idx.b32 %0, %1, %2, %3;" : "=r"(ret) : "r"(var), "r"(srcLane), "r"(c));
+	return ret;
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned int __shfl(unsigned int var, int srcLane, int width) {
+	return (unsigned int) __shfl((int)var, srcLane, width);
+}
+
+__SM_30_INTRINSICS_DECL__ int __shfl_up(int var, unsigned int delta, int width) {
+	int ret;
+	int c = (warpSize-width) << 8;
+	asm volatile ("shfl.up.b32 %0, %1, %2, %3;" : "=r"(ret) : "r"(var), "r"(delta), "r"(c));
+	return ret;
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned int __shfl_up(unsigned int var, unsigned int delta, int width) {
+	return (unsigned int) __shfl_up((int)var, delta, width);
+}
+
+__SM_30_INTRINSICS_DECL__ int __shfl_down(int var, unsigned int delta, int width) {
+	int ret;
+	int c = ((warpSize-width) << 8) | 0x1f;
+	asm volatile ("shfl.down.b32 %0, %1, %2, %3;" : "=r"(ret) : "r"(var), "r"(delta), "r"(c));
+	return ret;
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned int __shfl_down(unsigned int var, unsigned int delta, int width) {
+	return (unsigned int) __shfl_down((int)var, delta, width);
+}
+
+__SM_30_INTRINSICS_DECL__ int __shfl_xor(int var, int laneMask, int width) {
+	int ret;
+	int c = ((warpSize-width) << 8) | 0x1f;
+	asm volatile ("shfl.bfly.b32 %0, %1, %2, %3;" : "=r"(ret) : "r"(var), "r"(laneMask), "r"(c));
+	return ret;
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned int __shfl_xor(unsigned int var, int laneMask, int width) {
+	return (unsigned int) __shfl_xor((int)var, laneMask, width);
+}
+
+__SM_30_INTRINSICS_DECL__ float __shfl(float var, int srcLane, int width) {
+	float ret;
+        int c;
+	c = ((warpSize-width) << 8) | 0x1f;
+	asm volatile ("shfl.idx.b32 %0, %1, %2, %3;" : "=f"(ret) : "f"(var), "r"(srcLane), "r"(c));
+	return ret;
+}
+
+__SM_30_INTRINSICS_DECL__ float __shfl_up(float var, unsigned int delta, int width) {
+	float ret;
+        int c;
+	c = (warpSize-width) << 8;
+	asm volatile ("shfl.up.b32 %0, %1, %2, %3;" : "=f"(ret) : "f"(var), "r"(delta), "r"(c));
+	return ret;
+}
+
+__SM_30_INTRINSICS_DECL__ float __shfl_down(float var, unsigned int delta, int width) {
+	float ret;
+        int c;
+	c = ((warpSize-width) << 8) | 0x1f;
+	asm volatile ("shfl.down.b32 %0, %1, %2, %3;" : "=f"(ret) : "f"(var), "r"(delta), "r"(c));
+	return ret;
+}
+
+__SM_30_INTRINSICS_DECL__ float __shfl_xor(float var, int laneMask, int width) {
+	float ret;
+        int c;
+	c = ((warpSize-width) << 8) | 0x1f;
+	asm volatile ("shfl.bfly.b32 %0, %1, %2, %3;" : "=f"(ret) : "f"(var), "r"(laneMask), "r"(c));
+	return ret;
+}
+
+// 64-bits SHFL
+
+__SM_30_INTRINSICS_DECL__ long long __shfl(long long var, int srcLane, int width) {
+	int lo, hi;
+	asm volatile("mov.b64 {%0,%1}, %2;" : "=r"(lo), "=r"(hi) : "l"(var));
+	hi = __shfl(hi, srcLane, width);
+	lo = __shfl(lo, srcLane, width);
+	asm volatile("mov.b64 %0, {%1,%2};" : "=l"(var) : "r"(lo), "r"(hi));
+	return var;
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned long long __shfl(unsigned long long var, int srcLane, int width) {
+	return (unsigned long long) __shfl((long long) var, srcLane, width);
+}
+
+__SM_30_INTRINSICS_DECL__ long long __shfl_up(long long var, unsigned int delta, int width) {
+	int lo, hi;
+	asm volatile("mov.b64 {%0,%1}, %2;" : "=r"(lo), "=r"(hi) : "l"(var));
+	hi = __shfl_up(hi, delta, width);
+	lo = __shfl_up(lo, delta, width);
+	asm volatile("mov.b64 %0, {%1,%2};" : "=l"(var) : "r"(lo), "r"(hi));
+	return var;
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned long long __shfl_up(unsigned long long var, unsigned int delta, int width) {
+	return (unsigned long long) __shfl_up((long long) var, delta, width);
+}
+
+__SM_30_INTRINSICS_DECL__ long long __shfl_down(long long var, unsigned int delta, int width) {
+	int lo, hi;
+	asm volatile("mov.b64 {%0,%1}, %2;" : "=r"(lo), "=r"(hi) : "l"(var));
+	hi = __shfl_down(hi, delta, width);
+	lo = __shfl_down(lo, delta, width);
+	asm volatile("mov.b64 %0, {%1,%2};" : "=l"(var) : "r"(lo), "r"(hi));
+	return var;
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned long long __shfl_down(unsigned long long var, unsigned int delta, int width) {
+	return (unsigned long long) __shfl_down((long long) var, delta, width);
+}
+
+__SM_30_INTRINSICS_DECL__ long long __shfl_xor(long long var, int laneMask, int width) {
+	int lo, hi;
+	asm volatile("mov.b64 {%0,%1}, %2;" : "=r"(lo), "=r"(hi) : "l"(var));
+	hi = __shfl_xor(hi, laneMask, width);
+	lo = __shfl_xor(lo, laneMask, width);
+	asm volatile("mov.b64 %0, {%1,%2};" : "=l"(var) : "r"(lo), "r"(hi));
+	return var;
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned long long __shfl_xor(unsigned long long var, int laneMask, int width) {
+	return (unsigned long long) __shfl_xor((long long) var, laneMask, width);
+}
+
+__SM_30_INTRINSICS_DECL__ double __shfl(double var, int srcLane, int width) {
+	unsigned lo, hi;
+	asm volatile("mov.b64 {%0,%1}, %2;" : "=r"(lo), "=r"(hi) : "d"(var));
+	hi = __shfl(hi, srcLane, width);
+	lo = __shfl(lo, srcLane, width);
+	asm volatile("mov.b64 %0, {%1,%2};" : "=d"(var) : "r"(lo), "r"(hi));
+	return var;
+}
+
+__SM_30_INTRINSICS_DECL__ double __shfl_up(double var, unsigned int delta, int width) {
+	unsigned lo, hi;
+	asm volatile("mov.b64 {%0,%1}, %2;" : "=r"(lo), "=r"(hi) : "d"(var));
+	hi = __shfl_up(hi, delta, width);
+	lo = __shfl_up(lo, delta, width);
+	asm volatile("mov.b64 %0, {%1,%2};" : "=d"(var) : "r"(lo), "r"(hi));
+	return var;
+}
+
+__SM_30_INTRINSICS_DECL__ double __shfl_down(double var, unsigned int delta, int width) {
+	unsigned lo, hi;
+	asm volatile("mov.b64 {%0,%1}, %2;" : "=r"(lo), "=r"(hi) : "d"(var));
+	hi = __shfl_down(hi, delta, width);
+	lo = __shfl_down(lo, delta, width);
+	asm volatile("mov.b64 %0, {%1,%2};" : "=d"(var) : "r"(lo), "r"(hi));
+	return var;
+}
+
+__SM_30_INTRINSICS_DECL__ double __shfl_xor(double var, int laneMask, int width) {
+	unsigned lo, hi;
+	asm volatile("mov.b64 {%0,%1}, %2;" : "=r"(lo), "=r"(hi) : "d"(var));
+	hi = __shfl_xor(hi, laneMask, width);
+	lo = __shfl_xor(lo, laneMask, width);
+	asm volatile("mov.b64 %0, {%1,%2};" : "=d"(var) : "r"(lo), "r"(hi));
+	return var;
+}
+
+__SM_30_INTRINSICS_DECL__ long __shfl(long var, int srcLane, int width) {
+	return (sizeof(long) == sizeof(long long)) ?
+		__shfl((long long) var, srcLane, width) :
+		__shfl((int) var, srcLane, width);
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned long __shfl(unsigned long var, int srcLane, int width) {
+	return (sizeof(long) == sizeof(long long)) ?
+		__shfl((unsigned long long) var, srcLane, width) :
+		__shfl((unsigned int) var, srcLane, width);
+}
+
+__SM_30_INTRINSICS_DECL__ long __shfl_up(long var, unsigned int delta, int width) {
+	return (sizeof(long) == sizeof(long long)) ?
+		__shfl_up((long long) var, delta, width) :
+		__shfl_up((int) var, delta, width);
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned long __shfl_up(unsigned long var, unsigned int delta, int width) {
+	return (sizeof(long) == sizeof(long long)) ?
+		__shfl_up((unsigned long long) var, delta, width) :
+		__shfl_up((unsigned int) var, delta, width);
+}
+
+__SM_30_INTRINSICS_DECL__ long __shfl_down(long var, unsigned int delta, int width) {
+	return (sizeof(long) == sizeof(long long)) ?
+		__shfl_down((long long) var, delta, width) :
+		__shfl_down((int) var, delta, width);
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned long __shfl_down(unsigned long var, unsigned int delta, int width) {
+	return (sizeof(long) == sizeof(long long)) ?
+		__shfl_down((unsigned long long) var, delta, width) :
+		__shfl_down((unsigned int) var, delta, width);
+}
+
+__SM_30_INTRINSICS_DECL__ long __shfl_xor(long var, int laneMask, int width) {
+	return (sizeof(long) == sizeof(long long)) ?
+		__shfl_xor((long long) var, laneMask, width) :
+		__shfl_xor((int) var, laneMask, width);
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned long __shfl_xor(unsigned long var, int laneMask, int width) {
+	return (sizeof(long) == sizeof(long long)) ?
+		__shfl_xor((unsigned long long) var, laneMask, width) :
+		__shfl_xor((unsigned int) var, laneMask, width);
+}
+
+#endif /* defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || __CUDA_ARCH__ < 700 */
+
+// Warp register exchange (shuffle) intrinsics.
+// Notes:
+// a) Warp size is hardcoded to 32 here, because the compiler does not know
+//    the "warpSize" constant at this time
+// b) we cannot map the float __shfl to the int __shfl because it'll mess with
+//    the register number (especially if you're doing two shfls to move a double).
+__SM_30_INTRINSICS_DECL__ int __shfl_sync(unsigned mask, int var, int srcLane, int width) {
+        extern __device__ __device_builtin__ unsigned __nvvm_shfl_idx_sync(unsigned mask, unsigned a, unsigned b, unsigned c);
+	int ret;
+	int c = ((warpSize-width) << 8) | 0x1f;
+        ret = __nvvm_shfl_idx_sync(mask, var, srcLane, c);
+	return ret;
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned int __shfl_sync(unsigned mask, unsigned int var, int srcLane, int width) {
+        return (unsigned int) __shfl_sync(mask, (int)var, srcLane, width);
+}
+
+__SM_30_INTRINSICS_DECL__ int __shfl_up_sync(unsigned mask, int var, unsigned int delta, int width) {
+        extern __device__ __device_builtin__ unsigned __nvvm_shfl_up_sync(unsigned mask, unsigned a, unsigned b, unsigned c);
+	int ret;
+	int c = (warpSize-width) << 8;
+        ret = __nvvm_shfl_up_sync(mask, var, delta, c);
+	return ret;
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned int __shfl_up_sync(unsigned mask, unsigned int var, unsigned int delta, int width) {
+        return (unsigned int) __shfl_up_sync(mask, (int)var, delta, width);
+}
+
+__SM_30_INTRINSICS_DECL__ int __shfl_down_sync(unsigned mask, int var, unsigned int delta, int width) {
+        extern __device__ __device_builtin__ unsigned __nvvm_shfl_down_sync(unsigned mask, unsigned a, unsigned b, unsigned c);
+	int ret;
+	int c = ((warpSize-width) << 8) | 0x1f;
+        ret = __nvvm_shfl_down_sync(mask, var, delta, c);
+	return ret;
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned int __shfl_down_sync(unsigned mask, unsigned int var, unsigned int delta, int width) {
+        return (unsigned int) __shfl_down_sync(mask, (int)var, delta, width);
+}
+
+__SM_30_INTRINSICS_DECL__ int __shfl_xor_sync(unsigned mask, int var, int laneMask, int width) {
+        extern __device__ __device_builtin__ unsigned __nvvm_shfl_bfly_sync(unsigned mask, unsigned a, unsigned b, unsigned c);
+	int ret;
+	int c = ((warpSize-width) << 8) | 0x1f;
+        ret = __nvvm_shfl_bfly_sync(mask, var, laneMask, c);
+	return ret;
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned int __shfl_xor_sync(unsigned mask, unsigned int var, int laneMask, int width) {
+	return (unsigned int) __shfl_xor_sync(mask, (int)var, laneMask, width);
+}
+
+__SM_30_INTRINSICS_DECL__ float __shfl_sync(unsigned mask, float var, int srcLane, int width) {
+        extern __device__ __device_builtin__ unsigned __nvvm_shfl_idx_sync(unsigned mask, unsigned a, unsigned b, unsigned c);
+        int ret;
+        int c;
+	c = ((warpSize-width) << 8) | 0x1f;
+        ret = __nvvm_shfl_idx_sync(mask, __float_as_int(var), srcLane, c);
+	return __int_as_float(ret);
+}
+
+__SM_30_INTRINSICS_DECL__ float __shfl_up_sync(unsigned mask, float var, unsigned int delta, int width) {
+        extern __device__ __device_builtin__ unsigned __nvvm_shfl_up_sync(unsigned mask, unsigned a, unsigned b, unsigned c);
+	int ret;
+        int c;
+	c = (warpSize-width) << 8;
+        ret = __nvvm_shfl_up_sync(mask, __float_as_int(var), delta, c);
+	return __int_as_float(ret);
+}
+
+__SM_30_INTRINSICS_DECL__ float __shfl_down_sync(unsigned mask, float var, unsigned int delta, int width) {
+        extern __device__ __device_builtin__ unsigned __nvvm_shfl_down_sync(unsigned mask, unsigned a, unsigned b, unsigned c);
+	int ret;
+        int c;
+	c = ((warpSize-width) << 8) | 0x1f;
+        ret = __nvvm_shfl_down_sync(mask, __float_as_int(var), delta, c);
+	return __int_as_float(ret);
+}
+
+__SM_30_INTRINSICS_DECL__ float __shfl_xor_sync(unsigned mask, float var, int laneMask, int width) {
+        extern __device__ __device_builtin__ unsigned __nvvm_shfl_bfly_sync(unsigned mask, unsigned a, unsigned b, unsigned c);
+	int ret;
+        int c;
+	c = ((warpSize-width) << 8) | 0x1f;
+        ret = __nvvm_shfl_bfly_sync(mask, __float_as_int(var), laneMask, c);
+	return __int_as_float(ret);
+}
+
+// 64-bits SHFL
+__SM_30_INTRINSICS_DECL__ long long __shfl_sync(unsigned mask, long long var, int srcLane, int width) {
+	int lo, hi;
+	asm volatile("mov.b64 {%0,%1}, %2;" : "=r"(lo), "=r"(hi) : "l"(var));
+	hi = __shfl_sync(mask, hi, srcLane, width);
+	lo = __shfl_sync(mask, lo, srcLane, width);
+	asm volatile("mov.b64 %0, {%1,%2};" : "=l"(var) : "r"(lo), "r"(hi));
+	return var;
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned long long __shfl_sync(unsigned mask, unsigned long long var, int srcLane, int width) {
+        return (unsigned long long) __shfl_sync(mask, (long long) var, srcLane, width);
+}
+
+__SM_30_INTRINSICS_DECL__ long long __shfl_up_sync(unsigned mask, long long var, unsigned int delta, int width) {
+	int lo, hi;
+	asm volatile("mov.b64 {%0,%1}, %2;" : "=r"(lo), "=r"(hi) : "l"(var));
+	hi = __shfl_up_sync(mask, hi, delta, width);
+	lo = __shfl_up_sync(mask, lo, delta, width);
+	asm volatile("mov.b64 %0, {%1,%2};" : "=l"(var) : "r"(lo), "r"(hi));
+	return var;
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned long long __shfl_up_sync(unsigned mask, unsigned long long var, unsigned int delta, int width) {
+        return (unsigned long long) __shfl_up_sync(mask, (long long) var, delta, width);
+}
+
+__SM_30_INTRINSICS_DECL__ long long __shfl_down_sync(unsigned mask, long long var, unsigned int delta, int width) {
+	int lo, hi;
+	asm volatile("mov.b64 {%0,%1}, %2;" : "=r"(lo), "=r"(hi) : "l"(var));
+	hi = __shfl_down_sync(mask, hi, delta, width);
+	lo = __shfl_down_sync(mask, lo, delta, width);
+	asm volatile("mov.b64 %0, {%1,%2};" : "=l"(var) : "r"(lo), "r"(hi));
+	return var;
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned long long __shfl_down_sync(unsigned mask, unsigned long long var, unsigned int delta, int width) {
+        return (unsigned long long) __shfl_down_sync(mask, (long long) var, delta, width);
+}
+
+__SM_30_INTRINSICS_DECL__ long long __shfl_xor_sync(unsigned mask, long long var, int laneMask, int width) {
+	int lo, hi;
+	asm volatile("mov.b64 {%0,%1}, %2;" : "=r"(lo), "=r"(hi) : "l"(var));
+	hi = __shfl_xor_sync(mask, hi, laneMask, width);
+	lo = __shfl_xor_sync(mask, lo, laneMask, width);
+	asm volatile("mov.b64 %0, {%1,%2};" : "=l"(var) : "r"(lo), "r"(hi));
+	return var;
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned long long __shfl_xor_sync(unsigned mask, unsigned long long var, int laneMask, int width) {
+        return (unsigned long long) __shfl_xor_sync(mask, (long long) var, laneMask, width);
+}
+
+__SM_30_INTRINSICS_DECL__ double __shfl_sync(unsigned mask, double var, int srcLane, int width) {
+	unsigned lo, hi;
+	asm volatile("mov.b64 {%0,%1}, %2;" : "=r"(lo), "=r"(hi) : "d"(var));
+	hi = __shfl_sync(mask, hi, srcLane, width);
+	lo = __shfl_sync(mask, lo, srcLane, width);
+	asm volatile("mov.b64 %0, {%1,%2};" : "=d"(var) : "r"(lo), "r"(hi));
+	return var;
+}
+
+__SM_30_INTRINSICS_DECL__ double __shfl_up_sync(unsigned mask, double var, unsigned int delta, int width) {
+	unsigned lo, hi;
+	asm volatile("mov.b64 {%0,%1}, %2;" : "=r"(lo), "=r"(hi) : "d"(var));
+	hi = __shfl_up_sync(mask, hi, delta, width);
+	lo = __shfl_up_sync(mask, lo, delta, width);
+	asm volatile("mov.b64 %0, {%1,%2};" : "=d"(var) : "r"(lo), "r"(hi));
+	return var;
+}
+
+__SM_30_INTRINSICS_DECL__ double __shfl_down_sync(unsigned mask, double var, unsigned int delta, int width) {
+	unsigned lo, hi;
+	asm volatile("mov.b64 {%0,%1}, %2;" : "=r"(lo), "=r"(hi) : "d"(var));
+	hi = __shfl_down_sync(mask, hi, delta, width);
+	lo = __shfl_down_sync(mask, lo, delta, width);
+	asm volatile("mov.b64 %0, {%1,%2};" : "=d"(var) : "r"(lo), "r"(hi));
+	return var;
+}
+
+__SM_30_INTRINSICS_DECL__ double __shfl_xor_sync(unsigned mask, double var, int laneMask, int width) {
+	unsigned lo, hi;
+	asm volatile("mov.b64 {%0,%1}, %2;" : "=r"(lo), "=r"(hi) : "d"(var));
+	hi = __shfl_xor_sync(mask, hi, laneMask, width);
+	lo = __shfl_xor_sync(mask, lo, laneMask, width);
+	asm volatile("mov.b64 %0, {%1,%2};" : "=d"(var) : "r"(lo), "r"(hi));
+	return var;
+}
+
+// long needs some help to choose between 32-bits and 64-bits
+
+__SM_30_INTRINSICS_DECL__ long __shfl_sync(unsigned mask, long var, int srcLane, int width) {
+	return (sizeof(long) == sizeof(long long)) ?
+                __shfl_sync(mask, (long long) var, srcLane, width) :
+		__shfl_sync(mask, (int) var, srcLane, width);
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned long __shfl_sync(unsigned mask, unsigned long var, int srcLane, int width) {
+	return (sizeof(long) == sizeof(long long)) ?
+                __shfl_sync(mask, (unsigned long long) var, srcLane, width) :
+		__shfl_sync(mask, (unsigned int) var, srcLane, width);
+}
+
+__SM_30_INTRINSICS_DECL__ long __shfl_up_sync(unsigned mask, long var, unsigned int delta, int width) {
+	return (sizeof(long) == sizeof(long long)) ?
+		__shfl_up_sync(mask, (long long) var, delta, width) :
+		__shfl_up_sync(mask, (int) var, delta, width);
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned long __shfl_up_sync(unsigned mask, unsigned long var, unsigned int delta, int width) {
+	return (sizeof(long) == sizeof(long long)) ?
+		__shfl_up_sync(mask, (unsigned long long) var, delta, width) :
+		__shfl_up_sync(mask, (unsigned int) var, delta, width);
+}
+
+__SM_30_INTRINSICS_DECL__ long __shfl_down_sync(unsigned mask, long var, unsigned int delta, int width) {
+	return (sizeof(long) == sizeof(long long)) ?
+		__shfl_down_sync(mask, (long long) var, delta, width) :
+		__shfl_down_sync(mask, (int) var, delta, width);
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned long __shfl_down_sync(unsigned mask, unsigned long var, unsigned int delta, int width) {
+	return (sizeof(long) == sizeof(long long)) ?
+		__shfl_down_sync(mask, (unsigned long long) var, delta, width) :
+		__shfl_down_sync(mask, (unsigned int) var, delta, width);
+}
+
+__SM_30_INTRINSICS_DECL__ long __shfl_xor_sync(unsigned mask, long var, int laneMask, int width) {
+	return (sizeof(long) == sizeof(long long)) ?
+		__shfl_xor_sync(mask, (long long) var, laneMask, width) :
+		__shfl_xor_sync(mask, (int) var, laneMask, width);
+}
+
+__SM_30_INTRINSICS_DECL__ unsigned long __shfl_xor_sync(unsigned mask, unsigned long var, int laneMask, int width) {
+	return (sizeof(long) == sizeof(long long)) ?
+		__shfl_xor_sync(mask, (unsigned long long) var, laneMask, width) :
+		__shfl_xor_sync(mask, (unsigned int) var, laneMask, width);
+}
+
+#if defined(__local_warpSize)
+#undef warpSize
+#undef __local_warpSize
+#endif
+
+#endif /* _NVHPC_CUDA || !__CUDA_ARCH__ || __CUDA_ARCH__ >= 300 */
+
+#endif /* __cplusplus && __CUDACC__ */
+
+#undef __SM_30_INTRINSICS_DECL__
+
+#endif /* !__SM_30_INTRINSICS_HPP__ */
+

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/sm_32_atomic_functions.h

@@ -0,0 +1,141 @@
+/*
+ * Copyright 1993-2014 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 35.235 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.35.235 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__SM_32_ATOMIC_FUNCTIONS_H__)
+#define __SM_32_ATOMIC_FUNCTIONS_H__
+
+#if defined(__CUDACC_RTC__)
+#define __SM_32_ATOMIC_FUNCTIONS_DECL__ __device__
+#else /* !__CUDACC_RTC__ */
+#define __SM_32_ATOMIC_FUNCTIONS_DECL__ static __inline__ __device__
+#endif /* __CUDACC_RTC__ */
+
+#if defined(__cplusplus) && defined(__CUDACC__)
+
+#if defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 320
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+#include "cuda_runtime_api.h"
+
+#if defined(_NVHPC_CUDA)
+#undef __device_builtin__
+#define __device_builtin__ __location__(device) __location__(host)
+#endif /* _NVHPC_CUDA */
+
+#ifndef __CUDA_ARCH__
+#define __DEF_IF_HOST { }
+#else  /* !__CUDA_ARCH__ */
+#define __DEF_IF_HOST ;
+#endif /* __CUDA_ARCH__ */
+
+
+#ifdef __CUDA_ARCH__
+extern "C"
+{
+extern __device__ __device_builtin__ long long __illAtomicMin(long long *address, long long val);
+extern __device__ __device_builtin__ long long __illAtomicMax(long long *address, long long val);
+extern __device__ __device_builtin__ long long __llAtomicAnd(long long *address, long long val);
+extern __device__ __device_builtin__ long long __llAtomicOr(long long *address, long long val);
+extern __device__ __device_builtin__ long long __llAtomicXor(long long *address, long long val);
+extern __device__ __device_builtin__ unsigned long long __ullAtomicMin(unsigned long long *address, unsigned long long val);
+extern __device__ __device_builtin__ unsigned long long __ullAtomicMax(unsigned long long *address, unsigned long long val);
+extern __device__ __device_builtin__ unsigned long long __ullAtomicAnd(unsigned long long *address, unsigned long long val);
+extern __device__ __device_builtin__ unsigned long long __ullAtomicOr (unsigned long long *address, unsigned long long val);
+extern __device__ __device_builtin__ unsigned long long __ullAtomicXor(unsigned long long *address, unsigned long long val);
+}
+#endif /* __CUDA_ARCH__ */
+
+#if defined(_NVHPC_CUDA)
+#undef __device_builtin__
+#define __device_builtin__
+#endif /* _NVHPC_CUDA */
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ long long atomicMin(long long *address, long long val) __DEF_IF_HOST
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ long long atomicMax(long long *address, long long val) __DEF_IF_HOST
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ long long atomicAnd(long long *address, long long val) __DEF_IF_HOST
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ long long atomicOr(long long *address, long long val) __DEF_IF_HOST
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ long long atomicXor(long long *address, long long val) __DEF_IF_HOST
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ unsigned long long atomicMin(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ unsigned long long atomicMax(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ unsigned long long atomicAnd(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ unsigned long long atomicOr(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ unsigned long long atomicXor(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+#endif /* !__CUDA_ARCH__ || __CUDA_ARCH__ >= 320 */
+
+#endif /* __cplusplus && __CUDACC__ */
+
+#undef __DEF_IF_HOST
+#undef __SM_32_ATOMIC_FUNCTIONS_DECL__
+
+#if !defined(__CUDACC_RTC__) && defined(__CUDA_ARCH__)
+#include "sm_32_atomic_functions.hpp"
+#endif /* !__CUDACC_RTC__  && defined(__CUDA_ARCH__) */
+
+#endif /* !__SM_32_ATOMIC_FUNCTIONS_H__ */

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/sm_32_atomic_functions.hpp

@@ -0,0 +1,134 @@
+/*
+ * Copyright 1993-2014 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 35.235 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.35.235 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__SM_32_ATOMIC_FUNCTIONS_HPP__)
+#define __SM_32_ATOMIC_FUNCTIONS_HPP__
+
+#if defined(__CUDACC_RTC__)
+#define __SM_32_ATOMIC_FUNCTIONS_DECL__ __device__
+#else /* !__CUDACC_RTC__ */
+#define __SM_32_ATOMIC_FUNCTIONS_DECL__ static __inline__ __device__
+#endif /* __CUDACC_RTC__ */
+
+#if defined(__cplusplus) && defined(__CUDACC__)
+
+#if defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 320
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+#include "cuda_runtime_api.h"
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ long long atomicMin(long long *address, long long val)
+{
+    return __illAtomicMin(address, val);
+}
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ long long atomicMax(long long *address, long long val)
+{
+    return __illAtomicMax(address, val);
+}
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ long long atomicAnd(long long *address, long long val)
+{
+    return __llAtomicAnd(address, val);
+}
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ long long atomicOr(long long *address, long long val)
+{
+    return __llAtomicOr(address, val);
+}
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ long long atomicXor(long long *address, long long val)
+{
+    return __llAtomicXor(address, val);
+}
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ unsigned long long atomicMin(unsigned long long *address, unsigned long long val)
+{
+    return __ullAtomicMin(address, val);
+}
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ unsigned long long atomicMax(unsigned long long *address, unsigned long long val)
+{
+    return __ullAtomicMax(address, val);
+}
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ unsigned long long atomicAnd(unsigned long long *address, unsigned long long val)
+{
+    return __ullAtomicAnd(address, val);
+}
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ unsigned long long atomicOr(unsigned long long *address, unsigned long long val)
+{
+    return __ullAtomicOr(address, val);
+}
+
+__SM_32_ATOMIC_FUNCTIONS_DECL__ unsigned long long atomicXor(unsigned long long *address, unsigned long long val)
+{
+    return __ullAtomicXor(address, val);
+}
+
+#endif /* _NVHPC_CUDA || !__CUDA_ARCH__ || __CUDA_ARCH__ >= 320 */
+
+#endif /* __cplusplus && __CUDACC__ */
+
+#undef __SM_32_ATOMIC_FUNCTIONS_DECL__
+
+#endif /* !__SM_32_ATOMIC_FUNCTIONS_HPP__ */
+

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/sm_32_intrinsics.hpp

@@ -0,0 +1,588 @@
+/*
+ * Copyright 1993-2020 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__SM_32_INTRINSICS_HPP__)
+#define __SM_32_INTRINSICS_HPP__
+
+#if defined(__CUDACC_RTC__)
+#define __SM_32_INTRINSICS_DECL__ __device__
+#else /* !__CUDACC_RTC__ */
+#define __SM_32_INTRINSICS_DECL__ static __device__ __inline__
+#endif /* __CUDACC_RTC__ */
+
+#if defined(__cplusplus) && defined(__CUDACC__)
+
+#if defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 320
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+#include "cuda_runtime_api.h"
+
+// In here are intrinsics which are built in to the compiler. These may be
+// referenced by intrinsic implementations from this file.
+extern "C"
+{
+    // There are no intrinsics built in to the compiler for SM-3.5,
+    // all intrinsics are now implemented as inline PTX below.
+}
+
+/*******************************************************************************
+*                                                                              *
+*  Below are implementations of SM-3.5 intrinsics which are included as        *
+*  source (instead of being built in to the compiler)                          *
+*                                                                              *
+*******************************************************************************/
+
+// LDG is a "load from global via texture path" command which can exhibit higher
+// bandwidth on GK110 than a regular LD.
+// Define a different pointer storage size for 64 and 32 bit
+#if (defined(_MSC_VER) && defined(_WIN64)) || defined(__LP64__) || defined(__CUDACC_RTC__)
+#define __LDG_PTR   "l"
+#else
+#define __LDG_PTR   "r"
+#endif
+
+/******************************************************************************
+ *                                   __ldg                                    *
+ ******************************************************************************/
+
+// Size of long is architecture and OS specific.
+#if defined(__LP64__) // 64 bits
+__SM_32_INTRINSICS_DECL__ long __ldg(const long *ptr) { unsigned long ret; asm volatile ("ld.global.nc.s64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr)); return (long)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long __ldg(const unsigned long *ptr) { unsigned long ret; asm volatile ("ld.global.nc.u64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr)); return ret; }
+#else // 32 bits
+__SM_32_INTRINSICS_DECL__ long __ldg(const long *ptr) { unsigned long ret; asm volatile ("ld.global.nc.s32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return (long)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long __ldg(const unsigned long *ptr) { unsigned long ret; asm volatile ("ld.global.nc.u32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return ret; }
+#endif
+
+
+__SM_32_INTRINSICS_DECL__ char __ldg(const char *ptr) { unsigned int ret; asm volatile ("ld.global.nc.s8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return (char)ret; }
+__SM_32_INTRINSICS_DECL__ signed char __ldg(const signed char *ptr) { unsigned int ret; asm volatile ("ld.global.nc.s8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return (signed char)ret; }
+__SM_32_INTRINSICS_DECL__ short __ldg(const short *ptr) { unsigned short ret; asm volatile ("ld.global.nc.s16 %0, [%1];"  : "=h"(ret) : __LDG_PTR (ptr)); return (short)ret; }
+__SM_32_INTRINSICS_DECL__ int __ldg(const int *ptr) { unsigned int ret; asm volatile ("ld.global.nc.s32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return (int)ret; }
+__SM_32_INTRINSICS_DECL__ long long __ldg(const long long *ptr) { unsigned long long ret; asm volatile ("ld.global.nc.s64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr)); return (long long)ret; }
+__SM_32_INTRINSICS_DECL__ char2 __ldg(const char2 *ptr) { char2 ret; int2 tmp; asm volatile ("ld.global.nc.v2.s8 {%0,%1}, [%2];"  : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr)); ret.x = (char)tmp.x; ret.y = (char)tmp.y; return ret; }
+__SM_32_INTRINSICS_DECL__ char4 __ldg(const char4 *ptr) { char4 ret; int4 tmp; asm volatile ("ld.global.nc.v4.s8 {%0,%1,%2,%3}, [%4];"  : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr)); ret.x = (char)tmp.x; ret.y = (char)tmp.y; ret.z = (char)tmp.z; ret.w = (char)tmp.w; return ret; }
+__SM_32_INTRINSICS_DECL__ short2 __ldg(const short2 *ptr) { short2 ret; asm volatile ("ld.global.nc.v2.s16 {%0,%1}, [%2];"  : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ short4 __ldg(const short4 *ptr) { short4 ret; asm volatile ("ld.global.nc.v4.s16 {%0,%1,%2,%3}, [%4];"  : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ int2 __ldg(const int2 *ptr) { int2 ret; asm volatile ("ld.global.nc.v2.s32 {%0,%1}, [%2];"  : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ int4 __ldg(const int4 *ptr) { int4 ret; asm volatile ("ld.global.nc.v4.s32 {%0,%1,%2,%3}, [%4];"  : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ longlong2 __ldg(const longlong2 *ptr) { longlong2 ret; asm volatile ("ld.global.nc.v2.s64 {%0,%1}, [%2];"  : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr)); return ret; }
+
+__SM_32_INTRINSICS_DECL__ unsigned char __ldg(const unsigned char *ptr) { unsigned int ret; asm volatile ("ld.global.nc.u8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr));  return (unsigned char)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned short __ldg(const unsigned short *ptr) { unsigned short ret; asm volatile ("ld.global.nc.u16 %0, [%1];"  : "=h"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ unsigned int __ldg(const unsigned int *ptr) { unsigned int ret; asm volatile ("ld.global.nc.u32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long long __ldg(const unsigned long long *ptr) { unsigned long long ret; asm volatile ("ld.global.nc.u64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ uchar2 __ldg(const uchar2 *ptr) { uchar2 ret; uint2 tmp; asm volatile ("ld.global.nc.v2.u8 {%0,%1}, [%2];"  : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr)); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; return ret; }
+__SM_32_INTRINSICS_DECL__ uchar4 __ldg(const uchar4 *ptr) { uchar4 ret; uint4 tmp; asm volatile ("ld.global.nc.v4.u8 {%0,%1,%2,%3}, [%4];"  : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr)); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; ret.z = (unsigned char)tmp.z; ret.w = (unsigned char)tmp.w; return ret; }
+__SM_32_INTRINSICS_DECL__ ushort2 __ldg(const ushort2 *ptr) { ushort2 ret; asm volatile ("ld.global.nc.v2.u16 {%0,%1}, [%2];"  : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ ushort4 __ldg(const ushort4 *ptr) { ushort4 ret; asm volatile ("ld.global.nc.v4.u16 {%0,%1,%2,%3}, [%4];"  : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ uint2 __ldg(const uint2 *ptr) { uint2 ret; asm volatile ("ld.global.nc.v2.u32 {%0,%1}, [%2];"  : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ uint4 __ldg(const uint4 *ptr) { uint4 ret; asm volatile ("ld.global.nc.v4.u32 {%0,%1,%2,%3}, [%4];"  : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ ulonglong2 __ldg(const ulonglong2 *ptr) { ulonglong2 ret; asm volatile ("ld.global.nc.v2.u64 {%0,%1}, [%2];"  : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr)); return ret; }
+
+__SM_32_INTRINSICS_DECL__ float __ldg(const float *ptr) { float ret; asm volatile ("ld.global.nc.f32 %0, [%1];"  : "=f"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ double __ldg(const double *ptr) { double ret; asm volatile ("ld.global.nc.f64 %0, [%1];"  : "=d"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ float2 __ldg(const float2 *ptr) { float2 ret; asm volatile ("ld.global.nc.v2.f32 {%0,%1}, [%2];"  : "=f"(ret.x), "=f"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ float4 __ldg(const float4 *ptr) { float4 ret; asm volatile ("ld.global.nc.v4.f32 {%0,%1,%2,%3}, [%4];"  : "=f"(ret.x), "=f"(ret.y), "=f"(ret.z), "=f"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ double2 __ldg(const double2 *ptr) { double2 ret; asm volatile ("ld.global.nc.v2.f64 {%0,%1}, [%2];"  : "=d"(ret.x), "=d"(ret.y) : __LDG_PTR (ptr)); return ret; }
+
+
+/******************************************************************************
+ *                                   __ldcg                                    *
+ ******************************************************************************/
+
+// Size of long is architecture and OS specific.
+#if defined(__LP64__) // 64 bits
+__SM_32_INTRINSICS_DECL__ long __ldcg(const long *ptr) { unsigned long ret; asm volatile ("ld.global.cg.s64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr)); return (long)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long __ldcg(const unsigned long *ptr) { unsigned long ret; asm volatile ("ld.global.cg.u64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr)); return ret; }
+#else // 32 bits
+__SM_32_INTRINSICS_DECL__ long __ldcg(const long *ptr) { unsigned long ret; asm volatile ("ld.global.cg.s32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return (long)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long __ldcg(const unsigned long *ptr) { unsigned long ret; asm volatile ("ld.global.cg.u32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return ret; }
+#endif
+
+
+__SM_32_INTRINSICS_DECL__ char __ldcg(const char *ptr) { unsigned int ret; asm volatile ("ld.global.cg.s8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return (char)ret; }
+__SM_32_INTRINSICS_DECL__ signed char __ldcg(const signed char *ptr) { unsigned int ret; asm volatile ("ld.global.cg.s8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return (signed char)ret; }
+__SM_32_INTRINSICS_DECL__ short __ldcg(const short *ptr) { unsigned short ret; asm volatile ("ld.global.cg.s16 %0, [%1];"  : "=h"(ret) : __LDG_PTR (ptr)); return (short)ret; }
+__SM_32_INTRINSICS_DECL__ int __ldcg(const int *ptr) { unsigned int ret; asm volatile ("ld.global.cg.s32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return (int)ret; }
+__SM_32_INTRINSICS_DECL__ long long __ldcg(const long long *ptr) { unsigned long long ret; asm volatile ("ld.global.cg.s64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr)); return (long long)ret; }
+__SM_32_INTRINSICS_DECL__ char2 __ldcg(const char2 *ptr) { char2 ret; int2 tmp; asm volatile ("ld.global.cg.v2.s8 {%0,%1}, [%2];"  : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr)); ret.x = (char)tmp.x; ret.y = (char)tmp.y; return ret; }
+__SM_32_INTRINSICS_DECL__ char4 __ldcg(const char4 *ptr) { char4 ret; int4 tmp; asm volatile ("ld.global.cg.v4.s8 {%0,%1,%2,%3}, [%4];"  : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr)); ret.x = (char)tmp.x; ret.y = (char)tmp.y; ret.z = (char)tmp.z; ret.w = (char)tmp.w; return ret; }
+__SM_32_INTRINSICS_DECL__ short2 __ldcg(const short2 *ptr) { short2 ret; asm volatile ("ld.global.cg.v2.s16 {%0,%1}, [%2];"  : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ short4 __ldcg(const short4 *ptr) { short4 ret; asm volatile ("ld.global.cg.v4.s16 {%0,%1,%2,%3}, [%4];"  : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ int2 __ldcg(const int2 *ptr) { int2 ret; asm volatile ("ld.global.cg.v2.s32 {%0,%1}, [%2];"  : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ int4 __ldcg(const int4 *ptr) { int4 ret; asm volatile ("ld.global.cg.v4.s32 {%0,%1,%2,%3}, [%4];"  : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ longlong2 __ldcg(const longlong2 *ptr) { longlong2 ret; asm volatile ("ld.global.cg.v2.s64 {%0,%1}, [%2];"  : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr)); return ret; }
+
+__SM_32_INTRINSICS_DECL__ unsigned char __ldcg(const unsigned char *ptr) { unsigned int ret; asm volatile ("ld.global.cg.u8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr));  return (unsigned char)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned short __ldcg(const unsigned short *ptr) { unsigned short ret; asm volatile ("ld.global.cg.u16 %0, [%1];"  : "=h"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ unsigned int __ldcg(const unsigned int *ptr) { unsigned int ret; asm volatile ("ld.global.cg.u32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long long __ldcg(const unsigned long long *ptr) { unsigned long long ret; asm volatile ("ld.global.cg.u64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ uchar2 __ldcg(const uchar2 *ptr) { uchar2 ret; uint2 tmp; asm volatile ("ld.global.cg.v2.u8 {%0,%1}, [%2];"  : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr)); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; return ret; }
+__SM_32_INTRINSICS_DECL__ uchar4 __ldcg(const uchar4 *ptr) { uchar4 ret; uint4 tmp; asm volatile ("ld.global.cg.v4.u8 {%0,%1,%2,%3}, [%4];"  : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr)); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; ret.z = (unsigned char)tmp.z; ret.w = (unsigned char)tmp.w; return ret; }
+__SM_32_INTRINSICS_DECL__ ushort2 __ldcg(const ushort2 *ptr) { ushort2 ret; asm volatile ("ld.global.cg.v2.u16 {%0,%1}, [%2];"  : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ ushort4 __ldcg(const ushort4 *ptr) { ushort4 ret; asm volatile ("ld.global.cg.v4.u16 {%0,%1,%2,%3}, [%4];"  : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ uint2 __ldcg(const uint2 *ptr) { uint2 ret; asm volatile ("ld.global.cg.v2.u32 {%0,%1}, [%2];"  : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ uint4 __ldcg(const uint4 *ptr) { uint4 ret; asm volatile ("ld.global.cg.v4.u32 {%0,%1,%2,%3}, [%4];"  : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ ulonglong2 __ldcg(const ulonglong2 *ptr) { ulonglong2 ret; asm volatile ("ld.global.cg.v2.u64 {%0,%1}, [%2];"  : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr)); return ret; }
+
+__SM_32_INTRINSICS_DECL__ float __ldcg(const float *ptr) { float ret; asm volatile ("ld.global.cg.f32 %0, [%1];"  : "=f"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ double __ldcg(const double *ptr) { double ret; asm volatile ("ld.global.cg.f64 %0, [%1];"  : "=d"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ float2 __ldcg(const float2 *ptr) { float2 ret; asm volatile ("ld.global.cg.v2.f32 {%0,%1}, [%2];"  : "=f"(ret.x), "=f"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ float4 __ldcg(const float4 *ptr) { float4 ret; asm volatile ("ld.global.cg.v4.f32 {%0,%1,%2,%3}, [%4];"  : "=f"(ret.x), "=f"(ret.y), "=f"(ret.z), "=f"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ double2 __ldcg(const double2 *ptr) { double2 ret; asm volatile ("ld.global.cg.v2.f64 {%0,%1}, [%2];"  : "=d"(ret.x), "=d"(ret.y) : __LDG_PTR (ptr)); return ret; }
+
+/******************************************************************************
+ *                                   __ldca                                    *
+ ******************************************************************************/
+
+// Size of long is architecture and OS specific.
+#if defined(__LP64__) // 64 bits
+__SM_32_INTRINSICS_DECL__ long __ldca(const long *ptr) { unsigned long ret; asm volatile ("ld.global.ca.s64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr)); return (long)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long __ldca(const unsigned long *ptr) { unsigned long ret; asm volatile ("ld.global.ca.u64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr)); return ret; }
+#else // 32 bits
+__SM_32_INTRINSICS_DECL__ long __ldca(const long *ptr) { unsigned long ret; asm volatile ("ld.global.ca.s32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return (long)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long __ldca(const unsigned long *ptr) { unsigned long ret; asm volatile ("ld.global.ca.u32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return ret; }
+#endif
+
+
+__SM_32_INTRINSICS_DECL__ char __ldca(const char *ptr) { unsigned int ret; asm volatile ("ld.global.ca.s8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return (char)ret; }
+__SM_32_INTRINSICS_DECL__ signed char __ldca(const signed char *ptr) { unsigned int ret; asm volatile ("ld.global.ca.s8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return (signed char)ret; }
+__SM_32_INTRINSICS_DECL__ short __ldca(const short *ptr) { unsigned short ret; asm volatile ("ld.global.ca.s16 %0, [%1];"  : "=h"(ret) : __LDG_PTR (ptr)); return (short)ret; }
+__SM_32_INTRINSICS_DECL__ int __ldca(const int *ptr) { unsigned int ret; asm volatile ("ld.global.ca.s32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return (int)ret; }
+__SM_32_INTRINSICS_DECL__ long long __ldca(const long long *ptr) { unsigned long long ret; asm volatile ("ld.global.ca.s64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr)); return (long long)ret; }
+__SM_32_INTRINSICS_DECL__ char2 __ldca(const char2 *ptr) { char2 ret; int2 tmp; asm volatile ("ld.global.ca.v2.s8 {%0,%1}, [%2];"  : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr)); ret.x = (char)tmp.x; ret.y = (char)tmp.y; return ret; }
+__SM_32_INTRINSICS_DECL__ char4 __ldca(const char4 *ptr) { char4 ret; int4 tmp; asm volatile ("ld.global.ca.v4.s8 {%0,%1,%2,%3}, [%4];"  : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr)); ret.x = (char)tmp.x; ret.y = (char)tmp.y; ret.z = (char)tmp.z; ret.w = (char)tmp.w; return ret; }
+__SM_32_INTRINSICS_DECL__ short2 __ldca(const short2 *ptr) { short2 ret; asm volatile ("ld.global.ca.v2.s16 {%0,%1}, [%2];"  : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ short4 __ldca(const short4 *ptr) { short4 ret; asm volatile ("ld.global.ca.v4.s16 {%0,%1,%2,%3}, [%4];"  : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ int2 __ldca(const int2 *ptr) { int2 ret; asm volatile ("ld.global.ca.v2.s32 {%0,%1}, [%2];"  : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ int4 __ldca(const int4 *ptr) { int4 ret; asm volatile ("ld.global.ca.v4.s32 {%0,%1,%2,%3}, [%4];"  : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ longlong2 __ldca(const longlong2 *ptr) { longlong2 ret; asm volatile ("ld.global.ca.v2.s64 {%0,%1}, [%2];"  : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr)); return ret; }
+
+__SM_32_INTRINSICS_DECL__ unsigned char __ldca(const unsigned char *ptr) { unsigned int ret; asm volatile ("ld.global.ca.u8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr));  return (unsigned char)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned short __ldca(const unsigned short *ptr) { unsigned short ret; asm volatile ("ld.global.ca.u16 %0, [%1];"  : "=h"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ unsigned int __ldca(const unsigned int *ptr) { unsigned int ret; asm volatile ("ld.global.ca.u32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long long __ldca(const unsigned long long *ptr) { unsigned long long ret; asm volatile ("ld.global.ca.u64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ uchar2 __ldca(const uchar2 *ptr) { uchar2 ret; uint2 tmp; asm volatile ("ld.global.ca.v2.u8 {%0,%1}, [%2];"  : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr)); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; return ret; }
+__SM_32_INTRINSICS_DECL__ uchar4 __ldca(const uchar4 *ptr) { uchar4 ret; uint4 tmp; asm volatile ("ld.global.ca.v4.u8 {%0,%1,%2,%3}, [%4];"  : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr)); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; ret.z = (unsigned char)tmp.z; ret.w = (unsigned char)tmp.w; return ret; }
+__SM_32_INTRINSICS_DECL__ ushort2 __ldca(const ushort2 *ptr) { ushort2 ret; asm volatile ("ld.global.ca.v2.u16 {%0,%1}, [%2];"  : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ ushort4 __ldca(const ushort4 *ptr) { ushort4 ret; asm volatile ("ld.global.ca.v4.u16 {%0,%1,%2,%3}, [%4];"  : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ uint2 __ldca(const uint2 *ptr) { uint2 ret; asm volatile ("ld.global.ca.v2.u32 {%0,%1}, [%2];"  : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ uint4 __ldca(const uint4 *ptr) { uint4 ret; asm volatile ("ld.global.ca.v4.u32 {%0,%1,%2,%3}, [%4];"  : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ ulonglong2 __ldca(const ulonglong2 *ptr) { ulonglong2 ret; asm volatile ("ld.global.ca.v2.u64 {%0,%1}, [%2];"  : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr)); return ret; }
+
+__SM_32_INTRINSICS_DECL__ float __ldca(const float *ptr) { float ret; asm volatile ("ld.global.ca.f32 %0, [%1];"  : "=f"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ double __ldca(const double *ptr) { double ret; asm volatile ("ld.global.ca.f64 %0, [%1];"  : "=d"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ float2 __ldca(const float2 *ptr) { float2 ret; asm volatile ("ld.global.ca.v2.f32 {%0,%1}, [%2];"  : "=f"(ret.x), "=f"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ float4 __ldca(const float4 *ptr) { float4 ret; asm volatile ("ld.global.ca.v4.f32 {%0,%1,%2,%3}, [%4];"  : "=f"(ret.x), "=f"(ret.y), "=f"(ret.z), "=f"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ double2 __ldca(const double2 *ptr) { double2 ret; asm volatile ("ld.global.ca.v2.f64 {%0,%1}, [%2];"  : "=d"(ret.x), "=d"(ret.y) : __LDG_PTR (ptr)); return ret; }
+
+/******************************************************************************
+ *                                   __ldcs                                    *
+ ******************************************************************************/
+
+// Size of long is architecture and OS specific.
+#if defined(__LP64__) // 64 bits
+__SM_32_INTRINSICS_DECL__ long __ldcs(const long *ptr) { unsigned long ret; asm volatile ("ld.global.cs.s64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr)); return (long)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long __ldcs(const unsigned long *ptr) { unsigned long ret; asm volatile ("ld.global.cs.u64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr)); return ret; }
+#else // 32 bits
+__SM_32_INTRINSICS_DECL__ long __ldcs(const long *ptr) { unsigned long ret; asm volatile ("ld.global.cs.s32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return (long)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long __ldcs(const unsigned long *ptr) { unsigned long ret; asm volatile ("ld.global.cs.u32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return ret; }
+#endif
+
+
+__SM_32_INTRINSICS_DECL__ char __ldcs(const char *ptr) { unsigned int ret; asm volatile ("ld.global.cs.s8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return (char)ret; }
+__SM_32_INTRINSICS_DECL__ signed char __ldcs(const signed char *ptr) { unsigned int ret; asm volatile ("ld.global.cs.s8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return (signed char)ret; }
+__SM_32_INTRINSICS_DECL__ short __ldcs(const short *ptr) { unsigned short ret; asm volatile ("ld.global.cs.s16 %0, [%1];"  : "=h"(ret) : __LDG_PTR (ptr)); return (short)ret; }
+__SM_32_INTRINSICS_DECL__ int __ldcs(const int *ptr) { unsigned int ret; asm volatile ("ld.global.cs.s32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return (int)ret; }
+__SM_32_INTRINSICS_DECL__ long long __ldcs(const long long *ptr) { unsigned long long ret; asm volatile ("ld.global.cs.s64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr)); return (long long)ret; }
+__SM_32_INTRINSICS_DECL__ char2 __ldcs(const char2 *ptr) { char2 ret; int2 tmp; asm volatile ("ld.global.cs.v2.s8 {%0,%1}, [%2];"  : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr)); ret.x = (char)tmp.x; ret.y = (char)tmp.y; return ret; }
+__SM_32_INTRINSICS_DECL__ char4 __ldcs(const char4 *ptr) { char4 ret; int4 tmp; asm volatile ("ld.global.cs.v4.s8 {%0,%1,%2,%3}, [%4];"  : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr)); ret.x = (char)tmp.x; ret.y = (char)tmp.y; ret.z = (char)tmp.z; ret.w = (char)tmp.w; return ret; }
+__SM_32_INTRINSICS_DECL__ short2 __ldcs(const short2 *ptr) { short2 ret; asm volatile ("ld.global.cs.v2.s16 {%0,%1}, [%2];"  : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ short4 __ldcs(const short4 *ptr) { short4 ret; asm volatile ("ld.global.cs.v4.s16 {%0,%1,%2,%3}, [%4];"  : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ int2 __ldcs(const int2 *ptr) { int2 ret; asm volatile ("ld.global.cs.v2.s32 {%0,%1}, [%2];"  : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ int4 __ldcs(const int4 *ptr) { int4 ret; asm volatile ("ld.global.cs.v4.s32 {%0,%1,%2,%3}, [%4];"  : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ longlong2 __ldcs(const longlong2 *ptr) { longlong2 ret; asm volatile ("ld.global.cs.v2.s64 {%0,%1}, [%2];"  : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr)); return ret; }
+
+__SM_32_INTRINSICS_DECL__ unsigned char __ldcs(const unsigned char *ptr) { unsigned int ret; asm volatile ("ld.global.cs.u8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr));  return (unsigned char)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned short __ldcs(const unsigned short *ptr) { unsigned short ret; asm volatile ("ld.global.cs.u16 %0, [%1];"  : "=h"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ unsigned int __ldcs(const unsigned int *ptr) { unsigned int ret; asm volatile ("ld.global.cs.u32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long long __ldcs(const unsigned long long *ptr) { unsigned long long ret; asm volatile ("ld.global.cs.u64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ uchar2 __ldcs(const uchar2 *ptr) { uchar2 ret; uint2 tmp; asm volatile ("ld.global.cs.v2.u8 {%0,%1}, [%2];"  : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr)); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; return ret; }
+__SM_32_INTRINSICS_DECL__ uchar4 __ldcs(const uchar4 *ptr) { uchar4 ret; uint4 tmp; asm volatile ("ld.global.cs.v4.u8 {%0,%1,%2,%3}, [%4];"  : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr)); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; ret.z = (unsigned char)tmp.z; ret.w = (unsigned char)tmp.w; return ret; }
+__SM_32_INTRINSICS_DECL__ ushort2 __ldcs(const ushort2 *ptr) { ushort2 ret; asm volatile ("ld.global.cs.v2.u16 {%0,%1}, [%2];"  : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ ushort4 __ldcs(const ushort4 *ptr) { ushort4 ret; asm volatile ("ld.global.cs.v4.u16 {%0,%1,%2,%3}, [%4];"  : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ uint2 __ldcs(const uint2 *ptr) { uint2 ret; asm volatile ("ld.global.cs.v2.u32 {%0,%1}, [%2];"  : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ uint4 __ldcs(const uint4 *ptr) { uint4 ret; asm volatile ("ld.global.cs.v4.u32 {%0,%1,%2,%3}, [%4];"  : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ ulonglong2 __ldcs(const ulonglong2 *ptr) { ulonglong2 ret; asm volatile ("ld.global.cs.v2.u64 {%0,%1}, [%2];"  : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr)); return ret; }
+
+__SM_32_INTRINSICS_DECL__ float __ldcs(const float *ptr) { float ret; asm volatile ("ld.global.cs.f32 %0, [%1];"  : "=f"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ double __ldcs(const double *ptr) { double ret; asm volatile ("ld.global.cs.f64 %0, [%1];"  : "=d"(ret) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ float2 __ldcs(const float2 *ptr) { float2 ret; asm volatile ("ld.global.cs.v2.f32 {%0,%1}, [%2];"  : "=f"(ret.x), "=f"(ret.y) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ float4 __ldcs(const float4 *ptr) { float4 ret; asm volatile ("ld.global.cs.v4.f32 {%0,%1,%2,%3}, [%4];"  : "=f"(ret.x), "=f"(ret.y), "=f"(ret.z), "=f"(ret.w) : __LDG_PTR (ptr)); return ret; }
+__SM_32_INTRINSICS_DECL__ double2 __ldcs(const double2 *ptr) { double2 ret; asm volatile ("ld.global.cs.v2.f64 {%0,%1}, [%2];"  : "=d"(ret.x), "=d"(ret.y) : __LDG_PTR (ptr)); return ret; }
+
+/******************************************************************************
+ *                                   __ldlu                                    *
+ ******************************************************************************/
+
+// Size of long is architecture and OS specific.
+#if defined(__LP64__) // 64 bits
+__SM_32_INTRINSICS_DECL__ long __ldlu(const long *ptr) { unsigned long ret; asm ("ld.global.lu.s64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr) : "memory"); return (long)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long __ldlu(const unsigned long *ptr) { unsigned long ret; asm ("ld.global.lu.u64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
+#else // 32 bits
+__SM_32_INTRINSICS_DECL__ long __ldlu(const long *ptr) { unsigned long ret; asm ("ld.global.lu.s32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (long)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long __ldlu(const unsigned long *ptr) { unsigned long ret; asm ("ld.global.lu.u32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
+#endif
+
+
+__SM_32_INTRINSICS_DECL__ char __ldlu(const char *ptr) { unsigned int ret; asm ("ld.global.lu.s8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (char)ret; }
+__SM_32_INTRINSICS_DECL__ signed char __ldlu(const signed char *ptr) { unsigned int ret; asm ("ld.global.lu.s8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (signed char)ret; }
+__SM_32_INTRINSICS_DECL__ short __ldlu(const short *ptr) { unsigned short ret; asm ("ld.global.lu.s16 %0, [%1];"  : "=h"(ret) : __LDG_PTR (ptr) : "memory"); return (short)ret; }
+__SM_32_INTRINSICS_DECL__ int __ldlu(const int *ptr) { unsigned int ret; asm ("ld.global.lu.s32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (int)ret; }
+__SM_32_INTRINSICS_DECL__ long long __ldlu(const long long *ptr) { unsigned long long ret; asm ("ld.global.lu.s64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr) : "memory"); return (long long)ret; }
+__SM_32_INTRINSICS_DECL__ char2 __ldlu(const char2 *ptr) { char2 ret; int2 tmp; asm ("ld.global.lu.v2.s8 {%0,%1}, [%2];"  : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr) : "memory"); ret.x = (char)tmp.x; ret.y = (char)tmp.y; return ret; }
+__SM_32_INTRINSICS_DECL__ char4 __ldlu(const char4 *ptr) { char4 ret; int4 tmp; asm ("ld.global.lu.v4.s8 {%0,%1,%2,%3}, [%4];"  : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr) : "memory"); ret.x = (char)tmp.x; ret.y = (char)tmp.y; ret.z = (char)tmp.z; ret.w = (char)tmp.w; return ret; }
+__SM_32_INTRINSICS_DECL__ short2 __ldlu(const short2 *ptr) { short2 ret; asm ("ld.global.lu.v2.s16 {%0,%1}, [%2];"  : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ short4 __ldlu(const short4 *ptr) { short4 ret; asm ("ld.global.lu.v4.s16 {%0,%1,%2,%3}, [%4];"  : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ int2 __ldlu(const int2 *ptr) { int2 ret; asm ("ld.global.lu.v2.s32 {%0,%1}, [%2];"  : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ int4 __ldlu(const int4 *ptr) { int4 ret; asm ("ld.global.lu.v4.s32 {%0,%1,%2,%3}, [%4];"  : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ longlong2 __ldlu(const longlong2 *ptr) { longlong2 ret; asm ("ld.global.lu.v2.s64 {%0,%1}, [%2];"  : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
+
+__SM_32_INTRINSICS_DECL__ unsigned char __ldlu(const unsigned char *ptr) { unsigned int ret; asm ("ld.global.lu.u8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr) : "memory");  return (unsigned char)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned short __ldlu(const unsigned short *ptr) { unsigned short ret; asm ("ld.global.lu.u16 %0, [%1];"  : "=h"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ unsigned int __ldlu(const unsigned int *ptr) { unsigned int ret; asm ("ld.global.lu.u32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long long __ldlu(const unsigned long long *ptr) { unsigned long long ret; asm ("ld.global.lu.u64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ uchar2 __ldlu(const uchar2 *ptr) { uchar2 ret; uint2 tmp; asm ("ld.global.lu.v2.u8 {%0,%1}, [%2];"  : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr) : "memory"); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; return ret; }
+__SM_32_INTRINSICS_DECL__ uchar4 __ldlu(const uchar4 *ptr) { uchar4 ret; uint4 tmp; asm ("ld.global.lu.v4.u8 {%0,%1,%2,%3}, [%4];"  : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr) : "memory"); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; ret.z = (unsigned char)tmp.z; ret.w = (unsigned char)tmp.w; return ret; }
+__SM_32_INTRINSICS_DECL__ ushort2 __ldlu(const ushort2 *ptr) { ushort2 ret; asm ("ld.global.lu.v2.u16 {%0,%1}, [%2];"  : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ ushort4 __ldlu(const ushort4 *ptr) { ushort4 ret; asm ("ld.global.lu.v4.u16 {%0,%1,%2,%3}, [%4];"  : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ uint2 __ldlu(const uint2 *ptr) { uint2 ret; asm ("ld.global.lu.v2.u32 {%0,%1}, [%2];"  : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ uint4 __ldlu(const uint4 *ptr) { uint4 ret; asm ("ld.global.lu.v4.u32 {%0,%1,%2,%3}, [%4];"  : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ ulonglong2 __ldlu(const ulonglong2 *ptr) { ulonglong2 ret; asm ("ld.global.lu.v2.u64 {%0,%1}, [%2];"  : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
+
+__SM_32_INTRINSICS_DECL__ float __ldlu(const float *ptr) { float ret; asm ("ld.global.lu.f32 %0, [%1];"  : "=f"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ double __ldlu(const double *ptr) { double ret; asm ("ld.global.lu.f64 %0, [%1];"  : "=d"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ float2 __ldlu(const float2 *ptr) { float2 ret; asm ("ld.global.lu.v2.f32 {%0,%1}, [%2];"  : "=f"(ret.x), "=f"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ float4 __ldlu(const float4 *ptr) { float4 ret; asm ("ld.global.lu.v4.f32 {%0,%1,%2,%3}, [%4];"  : "=f"(ret.x), "=f"(ret.y), "=f"(ret.z), "=f"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ double2 __ldlu(const double2 *ptr) { double2 ret; asm ("ld.global.lu.v2.f64 {%0,%1}, [%2];"  : "=d"(ret.x), "=d"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
+
+/******************************************************************************
+ *                                   __ldcv                                    *
+ ******************************************************************************/
+
+// Size of long is architecture and OS specific.
+#if defined(__LP64__) // 64 bits
+__SM_32_INTRINSICS_DECL__ long __ldcv(const long *ptr) { unsigned long ret; asm ("ld.global.cv.s64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr) : "memory"); return (long)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long __ldcv(const unsigned long *ptr) { unsigned long ret; asm ("ld.global.cv.u64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
+#else // 32 bits
+__SM_32_INTRINSICS_DECL__ long __ldcv(const long *ptr) { unsigned long ret; asm ("ld.global.cv.s32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (long)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long __ldcv(const unsigned long *ptr) { unsigned long ret; asm ("ld.global.cv.u32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
+#endif
+
+
+__SM_32_INTRINSICS_DECL__ char __ldcv(const char *ptr) { unsigned int ret; asm ("ld.global.cv.s8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (char)ret; }
+__SM_32_INTRINSICS_DECL__ signed char __ldcv(const signed char *ptr) { unsigned int ret; asm ("ld.global.cv.s8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (signed char)ret; }
+__SM_32_INTRINSICS_DECL__ short __ldcv(const short *ptr) { unsigned short ret; asm ("ld.global.cv.s16 %0, [%1];"  : "=h"(ret) : __LDG_PTR (ptr) : "memory"); return (short)ret; }
+__SM_32_INTRINSICS_DECL__ int __ldcv(const int *ptr) { unsigned int ret; asm ("ld.global.cv.s32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (int)ret; }
+__SM_32_INTRINSICS_DECL__ long long __ldcv(const long long *ptr) { unsigned long long ret; asm ("ld.global.cv.s64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr) : "memory"); return (long long)ret; }
+__SM_32_INTRINSICS_DECL__ char2 __ldcv(const char2 *ptr) { char2 ret; int2 tmp; asm ("ld.global.cv.v2.s8 {%0,%1}, [%2];"  : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr) : "memory"); ret.x = (char)tmp.x; ret.y = (char)tmp.y; return ret; }
+__SM_32_INTRINSICS_DECL__ char4 __ldcv(const char4 *ptr) { char4 ret; int4 tmp; asm ("ld.global.cv.v4.s8 {%0,%1,%2,%3}, [%4];"  : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr) : "memory"); ret.x = (char)tmp.x; ret.y = (char)tmp.y; ret.z = (char)tmp.z; ret.w = (char)tmp.w; return ret; }
+__SM_32_INTRINSICS_DECL__ short2 __ldcv(const short2 *ptr) { short2 ret; asm ("ld.global.cv.v2.s16 {%0,%1}, [%2];"  : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ short4 __ldcv(const short4 *ptr) { short4 ret; asm ("ld.global.cv.v4.s16 {%0,%1,%2,%3}, [%4];"  : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ int2 __ldcv(const int2 *ptr) { int2 ret; asm ("ld.global.cv.v2.s32 {%0,%1}, [%2];"  : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ int4 __ldcv(const int4 *ptr) { int4 ret; asm ("ld.global.cv.v4.s32 {%0,%1,%2,%3}, [%4];"  : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ longlong2 __ldcv(const longlong2 *ptr) { longlong2 ret; asm ("ld.global.cv.v2.s64 {%0,%1}, [%2];"  : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
+
+__SM_32_INTRINSICS_DECL__ unsigned char __ldcv(const unsigned char *ptr) { unsigned int ret; asm ("ld.global.cv.u8 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr) : "memory");  return (unsigned char)ret; }
+__SM_32_INTRINSICS_DECL__ unsigned short __ldcv(const unsigned short *ptr) { unsigned short ret; asm ("ld.global.cv.u16 %0, [%1];"  : "=h"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ unsigned int __ldcv(const unsigned int *ptr) { unsigned int ret; asm ("ld.global.cv.u32 %0, [%1];"  : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ unsigned long long __ldcv(const unsigned long long *ptr) { unsigned long long ret; asm ("ld.global.cv.u64 %0, [%1];"  : "=l"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ uchar2 __ldcv(const uchar2 *ptr) { uchar2 ret; uint2 tmp; asm ("ld.global.cv.v2.u8 {%0,%1}, [%2];"  : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr) : "memory"); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; return ret; }
+__SM_32_INTRINSICS_DECL__ uchar4 __ldcv(const uchar4 *ptr) { uchar4 ret; uint4 tmp; asm ("ld.global.cv.v4.u8 {%0,%1,%2,%3}, [%4];"  : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr) : "memory"); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; ret.z = (unsigned char)tmp.z; ret.w = (unsigned char)tmp.w; return ret; }
+__SM_32_INTRINSICS_DECL__ ushort2 __ldcv(const ushort2 *ptr) { ushort2 ret; asm ("ld.global.cv.v2.u16 {%0,%1}, [%2];"  : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ ushort4 __ldcv(const ushort4 *ptr) { ushort4 ret; asm ("ld.global.cv.v4.u16 {%0,%1,%2,%3}, [%4];"  : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ uint2 __ldcv(const uint2 *ptr) { uint2 ret; asm ("ld.global.cv.v2.u32 {%0,%1}, [%2];"  : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ uint4 __ldcv(const uint4 *ptr) { uint4 ret; asm ("ld.global.cv.v4.u32 {%0,%1,%2,%3}, [%4];"  : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ ulonglong2 __ldcv(const ulonglong2 *ptr) { ulonglong2 ret; asm ("ld.global.cv.v2.u64 {%0,%1}, [%2];"  : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
+
+__SM_32_INTRINSICS_DECL__ float __ldcv(const float *ptr) { float ret; asm ("ld.global.cv.f32 %0, [%1];"  : "=f"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ double __ldcv(const double *ptr) { double ret; asm ("ld.global.cv.f64 %0, [%1];"  : "=d"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ float2 __ldcv(const float2 *ptr) { float2 ret; asm ("ld.global.cv.v2.f32 {%0,%1}, [%2];"  : "=f"(ret.x), "=f"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ float4 __ldcv(const float4 *ptr) { float4 ret; asm ("ld.global.cv.v4.f32 {%0,%1,%2,%3}, [%4];"  : "=f"(ret.x), "=f"(ret.y), "=f"(ret.z), "=f"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
+__SM_32_INTRINSICS_DECL__ double2 __ldcv(const double2 *ptr) { double2 ret; asm ("ld.global.cv.v2.f64 {%0,%1}, [%2];"  : "=d"(ret.x), "=d"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
+
+/******************************************************************************
+ *                                   __stwb                                    *
+ ******************************************************************************/
+
+// Size of long is architecture and OS specific.
+#if defined(__LP64__) // 64 bits
+__SM_32_INTRINSICS_DECL__ void __stwb(long *ptr, long value) { asm ("st.global.wb.s64 [%0], %1;"  :: __LDG_PTR (ptr), "l"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(unsigned long *ptr, unsigned long value) { asm ("st.global.wb.u64 [%0], %1;"  :: __LDG_PTR (ptr), "l"(value) : "memory"); }
+#else // 32 bits
+__SM_32_INTRINSICS_DECL__ void __stwb(long *ptr, long value) { asm ("st.global.wb.s32 [%0], %1;"  :: __LDG_PTR (ptr),  "r"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(unsigned long *ptr, unsigned long value) { asm ("st.global.wb.u32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
+#endif
+
+
+__SM_32_INTRINSICS_DECL__ void __stwb(char *ptr, char value) { asm ("st.global.wb.s8 [%0], %1;"  :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(signed char *ptr, signed char value) { asm ("st.global.wb.s8 [%0], %1;"  :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(short *ptr, short value) { asm ("st.global.wb.s16 [%0], %1;"  :: __LDG_PTR (ptr), "h"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(int *ptr, int value) { asm ("st.global.wb.s32 [%0], %1;"  :: __LDG_PTR (ptr), "r"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(long long *ptr, long long value) { asm ("st.global.wb.s64 [%0], %1;"  :: __LDG_PTR (ptr), "l"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(char2 *ptr, char2 value) { const int x = value.x, y = value.y; asm ("st.global.wb.v2.s8 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(x), "r"(y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(char4 *ptr, char4 value) { const int x = value.x, y = value.y, z = value.z, w = value.w; asm ("st.global.wb.v4.s8 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(x), "r"(y), "r"(z), "r"(w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(short2 *ptr, short2 value) { asm ("st.global.wb.v2.s16 [%0], {%1,%2};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(short4 *ptr, short4 value) { asm ("st.global.wb.v4.s16 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y), "h"(value.z), "h"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(int2 *ptr, int2 value) { asm ("st.global.wb.v2.s32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(int4 *ptr, int4 value) { asm ("st.global.wb.v4.s32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y), "r"(value.z), "r"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(longlong2 *ptr, longlong2 value) { asm ("st.global.wb.v2.s64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "l"(value.x), "l"(value.y) : "memory"); }
+
+__SM_32_INTRINSICS_DECL__ void __stwb(unsigned char *ptr, unsigned char value) { asm ("st.global.wb.u8 [%0], %1;"  :: __LDG_PTR (ptr), "r"((int)value) : "memory");  }
+__SM_32_INTRINSICS_DECL__ void __stwb(unsigned short *ptr, unsigned short value) { asm ("st.global.wb.u16 [%0], %1;"  :: __LDG_PTR (ptr), "h"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(unsigned int *ptr, unsigned int value) { asm ("st.global.wb.u32 [%0], %1;"  :: __LDG_PTR (ptr), "r"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(unsigned long long *ptr, unsigned long long value) { asm ("st.global.wb.u64 [%0], %1;"  :: __LDG_PTR (ptr), "l"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(uchar2 *ptr, uchar2 value) { const int x = value.x, y = value.y; asm ("st.global.wb.v2.u8 [%0], {%1,%2};"  :: __LDG_PTR (ptr),  "r"(x), "r"(y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(uchar4 *ptr, uchar4 value) { const int x = value.x, y = value.y, z = value.z, w = value.w; asm ("st.global.wb.v4.u8 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(x), "r"(y), "r"(z), "r"(w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(ushort2 *ptr, ushort2 value) { asm ("st.global.wb.v2.u16 [%0], {%1,%2};"  :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(ushort4 *ptr, ushort4 value) { asm ("st.global.wb.v4.u16 [%0], {%1,%2,%3,%4};"  :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y), "h"(value.z), "h"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(uint2 *ptr, uint2 value) { asm ("st.global.wb.v2.u32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(uint4 *ptr, uint4 value) { asm ("st.global.wb.v4.u32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y), "r"(value.z), "r"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(ulonglong2 *ptr, ulonglong2 value) { asm ("st.global.wb.v2.u64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "l"(value.x), "l"(value.y) : "memory"); }
+
+__SM_32_INTRINSICS_DECL__ void __stwb(float *ptr, float value) { asm ("st.global.wb.f32 [%0], %1;"  :: __LDG_PTR (ptr), "f"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(double *ptr, double value) { asm ("st.global.wb.f64 [%0], %1;"  :: __LDG_PTR (ptr), "d"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(float2 *ptr, float2 value) { asm ("st.global.wb.v2.f32 [%0], {%1,%2};"  :: __LDG_PTR (ptr), "f"(value.x), "f"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(float4 *ptr, float4 value) { asm ("st.global.wb.v4.f32 [%0], {%1,%2,%3,%4};"  :: __LDG_PTR (ptr), "f"(value.x), "f"(value.y), "f"(value.z), "f"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwb(double2 *ptr, double2 value) { asm ("st.global.wb.v2.f64 [%0], {%1,%2};"  :: __LDG_PTR (ptr), "d"(value.x), "d"(value.y) : "memory"); }
+
+/******************************************************************************
+ *                                   __stcg                                    *
+ ******************************************************************************/
+
+// Size of long is architecture and OS specific.
+#if defined(__LP64__) // 64 bits
+__SM_32_INTRINSICS_DECL__ void __stcg(long *ptr, long value) { asm ("st.global.cg.s64 [%0], %1;"  :: __LDG_PTR (ptr), "l"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(unsigned long *ptr, unsigned long value) { asm ("st.global.cg.u64 [%0], %1;"  :: __LDG_PTR (ptr), "l"(value) : "memory"); }
+#else // 32 bits
+__SM_32_INTRINSICS_DECL__ void __stcg(long *ptr, long value) { asm ("st.global.cg.s32 [%0], %1;"  :: __LDG_PTR (ptr),  "r"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(unsigned long *ptr, unsigned long value) { asm ("st.global.cg.u32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
+#endif
+
+
+__SM_32_INTRINSICS_DECL__ void __stcg(char *ptr, char value) { asm ("st.global.cg.s8 [%0], %1;"  :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(signed char *ptr, signed char value) { asm ("st.global.cg.s8 [%0], %1;"  :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(short *ptr, short value) { asm ("st.global.cg.s16 [%0], %1;"  :: __LDG_PTR (ptr), "h"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(int *ptr, int value) { asm ("st.global.cg.s32 [%0], %1;"  :: __LDG_PTR (ptr), "r"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(long long *ptr, long long value) { asm ("st.global.cg.s64 [%0], %1;"  :: __LDG_PTR (ptr), "l"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(char2 *ptr, char2 value) { const int x = value.x, y = value.y; asm ("st.global.cg.v2.s8 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(x), "r"(y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(char4 *ptr, char4 value) { const int x = value.x, y = value.y, z = value.z, w = value.w; asm ("st.global.cg.v4.s8 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(x), "r"(y), "r"(z), "r"(w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(short2 *ptr, short2 value) { asm ("st.global.cg.v2.s16 [%0], {%1,%2};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(short4 *ptr, short4 value) { asm ("st.global.cg.v4.s16 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y), "h"(value.z), "h"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(int2 *ptr, int2 value) { asm ("st.global.cg.v2.s32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(int4 *ptr, int4 value) { asm ("st.global.cg.v4.s32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y), "r"(value.z), "r"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(longlong2 *ptr, longlong2 value) { asm ("st.global.cg.v2.s64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "l"(value.x), "l"(value.y) : "memory"); }
+
+__SM_32_INTRINSICS_DECL__ void __stcg(unsigned char *ptr, unsigned char value) { asm ("st.global.cg.u8 [%0], %1;"  :: __LDG_PTR (ptr), "r"((int)value) : "memory");  }
+__SM_32_INTRINSICS_DECL__ void __stcg(unsigned short *ptr, unsigned short value) { asm ("st.global.cg.u16 [%0], %1;"  :: __LDG_PTR (ptr), "h"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(unsigned int *ptr, unsigned int value) { asm ("st.global.cg.u32 [%0], %1;"  :: __LDG_PTR (ptr), "r"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(unsigned long long *ptr, unsigned long long value) { asm ("st.global.cg.u64 [%0], %1;"  :: __LDG_PTR (ptr), "l"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(uchar2 *ptr, uchar2 value) { const int x = value.x, y = value.y; asm ("st.global.cg.v2.u8 [%0], {%1,%2};"  :: __LDG_PTR (ptr),  "r"(x), "r"(y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(uchar4 *ptr, uchar4 value) { const int x = value.x, y = value.y, z = value.z, w = value.w; asm ("st.global.cg.v4.u8 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(x), "r"(y), "r"(z), "r"(w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(ushort2 *ptr, ushort2 value) { asm ("st.global.cg.v2.u16 [%0], {%1,%2};"  :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(ushort4 *ptr, ushort4 value) { asm ("st.global.cg.v4.u16 [%0], {%1,%2,%3,%4};"  :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y), "h"(value.z), "h"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(uint2 *ptr, uint2 value) { asm ("st.global.cg.v2.u32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(uint4 *ptr, uint4 value) { asm ("st.global.cg.v4.u32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y), "r"(value.z), "r"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(ulonglong2 *ptr, ulonglong2 value) { asm ("st.global.cg.v2.u64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "l"(value.x), "l"(value.y) : "memory"); }
+
+__SM_32_INTRINSICS_DECL__ void __stcg(float *ptr, float value) { asm ("st.global.cg.f32 [%0], %1;"  :: __LDG_PTR (ptr), "f"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(double *ptr, double value) { asm ("st.global.cg.f64 [%0], %1;"  :: __LDG_PTR (ptr), "d"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(float2 *ptr, float2 value) { asm ("st.global.cg.v2.f32 [%0], {%1,%2};"  :: __LDG_PTR (ptr), "f"(value.x), "f"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(float4 *ptr, float4 value) { asm ("st.global.cg.v4.f32 [%0], {%1,%2,%3,%4};"  :: __LDG_PTR (ptr), "f"(value.x), "f"(value.y), "f"(value.z), "f"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcg(double2 *ptr, double2 value) { asm ("st.global.cg.v2.f64 [%0], {%1,%2};"  :: __LDG_PTR (ptr), "d"(value.x), "d"(value.y) : "memory"); }
+
+/******************************************************************************
+ *                                   __stcs                                    *
+ ******************************************************************************/
+
+// Size of long is architecture and OS specific.
+#if defined(__LP64__) // 64 bits
+__SM_32_INTRINSICS_DECL__ void __stcs(long *ptr, long value) { asm ("st.global.cs.s64 [%0], %1;"  :: __LDG_PTR (ptr), "l"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(unsigned long *ptr, unsigned long value) { asm ("st.global.cs.u64 [%0], %1;"  :: __LDG_PTR (ptr), "l"(value) : "memory"); }
+#else // 32 bits
+__SM_32_INTRINSICS_DECL__ void __stcs(long *ptr, long value) { asm ("st.global.cs.s32 [%0], %1;"  :: __LDG_PTR (ptr),  "r"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(unsigned long *ptr, unsigned long value) { asm ("st.global.cs.u32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
+#endif
+
+
+__SM_32_INTRINSICS_DECL__ void __stcs(char *ptr, char value) { asm ("st.global.cs.s8 [%0], %1;"  :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(signed char *ptr, signed char value) { asm ("st.global.cs.s8 [%0], %1;"  :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(short *ptr, short value) { asm ("st.global.cs.s16 [%0], %1;"  :: __LDG_PTR (ptr), "h"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(int *ptr, int value) { asm ("st.global.cs.s32 [%0], %1;"  :: __LDG_PTR (ptr), "r"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(long long *ptr, long long value) { asm ("st.global.cs.s64 [%0], %1;"  :: __LDG_PTR (ptr), "l"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(char2 *ptr, char2 value) { const int x = value.x, y = value.y; asm ("st.global.cs.v2.s8 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(x), "r"(y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(char4 *ptr, char4 value) { const int x = value.x, y = value.y, z = value.z, w = value.w; asm ("st.global.cs.v4.s8 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(x), "r"(y), "r"(z), "r"(w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(short2 *ptr, short2 value) { asm ("st.global.cs.v2.s16 [%0], {%1,%2};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(short4 *ptr, short4 value) { asm ("st.global.cs.v4.s16 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y), "h"(value.z), "h"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(int2 *ptr, int2 value) { asm ("st.global.cs.v2.s32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(int4 *ptr, int4 value) { asm ("st.global.cs.v4.s32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y), "r"(value.z), "r"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(longlong2 *ptr, longlong2 value) { asm ("st.global.cs.v2.s64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "l"(value.x), "l"(value.y) : "memory"); }
+
+__SM_32_INTRINSICS_DECL__ void __stcs(unsigned char *ptr, unsigned char value) { asm ("st.global.cs.u8 [%0], %1;"  :: __LDG_PTR (ptr), "r"((int)value) : "memory");  }
+__SM_32_INTRINSICS_DECL__ void __stcs(unsigned short *ptr, unsigned short value) { asm ("st.global.cs.u16 [%0], %1;"  :: __LDG_PTR (ptr), "h"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(unsigned int *ptr, unsigned int value) { asm ("st.global.cs.u32 [%0], %1;"  :: __LDG_PTR (ptr), "r"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(unsigned long long *ptr, unsigned long long value) { asm ("st.global.cs.u64 [%0], %1;"  :: __LDG_PTR (ptr), "l"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(uchar2 *ptr, uchar2 value) { const int x = value.x, y = value.y; asm ("st.global.cs.v2.u8 [%0], {%1,%2};"  :: __LDG_PTR (ptr),  "r"(x), "r"(y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(uchar4 *ptr, uchar4 value) { const int x = value.x, y = value.y, z = value.z, w = value.w; asm ("st.global.cs.v4.u8 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(x), "r"(y), "r"(z), "r"(w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(ushort2 *ptr, ushort2 value) { asm ("st.global.cs.v2.u16 [%0], {%1,%2};"  :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(ushort4 *ptr, ushort4 value) { asm ("st.global.cs.v4.u16 [%0], {%1,%2,%3,%4};"  :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y), "h"(value.z), "h"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(uint2 *ptr, uint2 value) { asm ("st.global.cs.v2.u32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(uint4 *ptr, uint4 value) { asm ("st.global.cs.v4.u32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y), "r"(value.z), "r"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(ulonglong2 *ptr, ulonglong2 value) { asm ("st.global.cs.v2.u64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "l"(value.x), "l"(value.y) : "memory"); }
+
+__SM_32_INTRINSICS_DECL__ void __stcs(float *ptr, float value) { asm ("st.global.cs.f32 [%0], %1;"  :: __LDG_PTR (ptr), "f"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(double *ptr, double value) { asm ("st.global.cs.f64 [%0], %1;"  :: __LDG_PTR (ptr), "d"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(float2 *ptr, float2 value) { asm ("st.global.cs.v2.f32 [%0], {%1,%2};"  :: __LDG_PTR (ptr), "f"(value.x), "f"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(float4 *ptr, float4 value) { asm ("st.global.cs.v4.f32 [%0], {%1,%2,%3,%4};"  :: __LDG_PTR (ptr), "f"(value.x), "f"(value.y), "f"(value.z), "f"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stcs(double2 *ptr, double2 value) { asm ("st.global.cs.v2.f64 [%0], {%1,%2};"  :: __LDG_PTR (ptr), "d"(value.x), "d"(value.y) : "memory"); }
+
+/******************************************************************************
+ *                                   __stwt                                    *
+ ******************************************************************************/
+
+// Size of long is architecture and OS specific.
+#if defined(__LP64__) // 64 bits
+__SM_32_INTRINSICS_DECL__ void __stwt(long *ptr, long value) { asm ("st.global.wt.s64 [%0], %1;"  :: __LDG_PTR (ptr), "l"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(unsigned long *ptr, unsigned long value) { asm ("st.global.wt.u64 [%0], %1;"  :: __LDG_PTR (ptr), "l"(value) : "memory"); }
+#else // 32 bits
+__SM_32_INTRINSICS_DECL__ void __stwt(long *ptr, long value) { asm ("st.global.wt.s32 [%0], %1;"  :: __LDG_PTR (ptr),  "r"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(unsigned long *ptr, unsigned long value) { asm ("st.global.wt.u32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
+#endif
+
+
+__SM_32_INTRINSICS_DECL__ void __stwt(char *ptr, char value) { asm ("st.global.wt.s8 [%0], %1;"  :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(signed char *ptr, signed char value) { asm ("st.global.wt.s8 [%0], %1;"  :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(short *ptr, short value) { asm ("st.global.wt.s16 [%0], %1;"  :: __LDG_PTR (ptr), "h"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(int *ptr, int value) { asm ("st.global.wt.s32 [%0], %1;"  :: __LDG_PTR (ptr), "r"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(long long *ptr, long long value) { asm ("st.global.wt.s64 [%0], %1;"  :: __LDG_PTR (ptr), "l"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(char2 *ptr, char2 value) { const int x = value.x, y = value.y; asm ("st.global.wt.v2.s8 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(x), "r"(y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(char4 *ptr, char4 value) { const int x = value.x, y = value.y, z = value.z, w = value.w; asm ("st.global.wt.v4.s8 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(x), "r"(y), "r"(z), "r"(w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(short2 *ptr, short2 value) { asm ("st.global.wt.v2.s16 [%0], {%1,%2};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(short4 *ptr, short4 value) { asm ("st.global.wt.v4.s16 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y), "h"(value.z), "h"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(int2 *ptr, int2 value) { asm ("st.global.wt.v2.s32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(int4 *ptr, int4 value) { asm ("st.global.wt.v4.s32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y), "r"(value.z), "r"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(longlong2 *ptr, longlong2 value) { asm ("st.global.wt.v2.s64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "l"(value.x), "l"(value.y) : "memory"); }
+
+__SM_32_INTRINSICS_DECL__ void __stwt(unsigned char *ptr, unsigned char value) { asm ("st.global.wt.u8 [%0], %1;"  :: __LDG_PTR (ptr), "r"((int)value) : "memory");  }
+__SM_32_INTRINSICS_DECL__ void __stwt(unsigned short *ptr, unsigned short value) { asm ("st.global.wt.u16 [%0], %1;"  :: __LDG_PTR (ptr), "h"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(unsigned int *ptr, unsigned int value) { asm ("st.global.wt.u32 [%0], %1;"  :: __LDG_PTR (ptr), "r"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(unsigned long long *ptr, unsigned long long value) { asm ("st.global.wt.u64 [%0], %1;"  :: __LDG_PTR (ptr), "l"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(uchar2 *ptr, uchar2 value) { const int x = value.x, y = value.y; asm ("st.global.wt.v2.u8 [%0], {%1,%2};"  :: __LDG_PTR (ptr),  "r"(x), "r"(y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(uchar4 *ptr, uchar4 value) { const int x = value.x, y = value.y, z = value.z, w = value.w; asm ("st.global.wt.v4.u8 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(x), "r"(y), "r"(z), "r"(w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(ushort2 *ptr, ushort2 value) { asm ("st.global.wt.v2.u16 [%0], {%1,%2};"  :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(ushort4 *ptr, ushort4 value) { asm ("st.global.wt.v4.u16 [%0], {%1,%2,%3,%4};"  :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y), "h"(value.z), "h"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(uint2 *ptr, uint2 value) { asm ("st.global.wt.v2.u32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(uint4 *ptr, uint4 value) { asm ("st.global.wt.v4.u32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y), "r"(value.z), "r"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(ulonglong2 *ptr, ulonglong2 value) { asm ("st.global.wt.v2.u64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "l"(value.x), "l"(value.y) : "memory"); }
+
+__SM_32_INTRINSICS_DECL__ void __stwt(float *ptr, float value) { asm ("st.global.wt.f32 [%0], %1;"  :: __LDG_PTR (ptr), "f"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(double *ptr, double value) { asm ("st.global.wt.f64 [%0], %1;"  :: __LDG_PTR (ptr), "d"(value) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(float2 *ptr, float2 value) { asm ("st.global.wt.v2.f32 [%0], {%1,%2};"  :: __LDG_PTR (ptr), "f"(value.x), "f"(value.y) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(float4 *ptr, float4 value) { asm ("st.global.wt.v4.f32 [%0], {%1,%2,%3,%4};"  :: __LDG_PTR (ptr), "f"(value.x), "f"(value.y), "f"(value.z), "f"(value.w) : "memory"); }
+__SM_32_INTRINSICS_DECL__ void __stwt(double2 *ptr, double2 value) { asm ("st.global.wt.v2.f64 [%0], {%1,%2};"  :: __LDG_PTR (ptr), "d"(value.x), "d"(value.y) : "memory"); }
+
+#undef __LDG_PTR
+
+
+// SHF is the "funnel shift" operation - an accelerated left/right shift with carry
+// operating on 64-bit quantities, which are concatenations of two 32-bit registers.
+
+// This shifts [b:a] left by "shift" bits, returning the most significant bits of the result.
+__SM_32_INTRINSICS_DECL__ unsigned int __funnelshift_l(unsigned int lo, unsigned int hi, unsigned int shift)
+{
+    unsigned int ret;
+    asm volatile ("shf.l.wrap.b32 %0, %1, %2, %3;" : "=r"(ret) : "r"(lo), "r"(hi), "r"(shift));
+    return ret;
+}
+__SM_32_INTRINSICS_DECL__ unsigned int __funnelshift_lc(unsigned int lo, unsigned int hi, unsigned int shift)
+{
+    unsigned int ret;
+    asm volatile ("shf.l.clamp.b32 %0, %1, %2, %3;" : "=r"(ret) : "r"(lo), "r"(hi), "r"(shift));
+    return ret;
+}
+
+// This shifts [b:a] right by "shift" bits, returning the least significant bits of the result.
+__SM_32_INTRINSICS_DECL__ unsigned int __funnelshift_r(unsigned int lo, unsigned int hi, unsigned int shift)
+{
+    unsigned int ret;
+    asm volatile ("shf.r.wrap.b32 %0, %1, %2, %3;" : "=r"(ret) : "r"(lo), "r"(hi), "r"(shift));
+    return ret;
+}
+__SM_32_INTRINSICS_DECL__ unsigned int __funnelshift_rc(unsigned int lo, unsigned int hi, unsigned int shift)
+{
+    unsigned int ret;
+    asm volatile ("shf.r.clamp.b32 %0, %1, %2, %3;" : "=r"(ret) : "r"(lo), "r"(hi), "r"(shift));
+    return ret;
+}
+
+
+#endif /* _NVHPC_CUDA || !__CUDA_ARCH__ || __CUDA_ARCH__ >= 320 */
+
+#endif /* __cplusplus && __CUDACC__ */
+
+#undef __SM_32_INTRINSICS_DECL__
+
+#endif /* !__SM_32_INTRINSICS_HPP__ */
+

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/sm_60_atomic_functions.h

@@ -0,0 +1,543 @@
+/*
+ * Copyright 1993-2014 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__SM_60_ATOMIC_FUNCTIONS_H__)
+#define __SM_60_ATOMIC_FUNCTIONS_H__
+
+
+#if defined(__CUDACC_RTC__)
+#define __SM_60_ATOMIC_FUNCTIONS_DECL__ __device__
+#elif defined(_NVHPC_CUDA)
+#define __SM_60_ATOMIC_FUNCTIONS_DECL__ extern __device__ __cudart_builtin__
+#else /* __CUDACC_RTC__ */
+#define __SM_60_ATOMIC_FUNCTIONS_DECL__ static __inline__ __device__
+#endif /* __CUDACC_RTC__ */
+
+#if defined(__cplusplus) && defined(__CUDACC__)
+
+#if defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 600
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+#include "cuda_runtime_api.h"
+
+/* Add !defined(_NVHPC_CUDA) to avoid empty function definition in CUDA
+ * C++ compiler where the macro __CUDA_ARCH__ is not defined. */
+#if !defined(__CUDA_ARCH__) && !defined(_NVHPC_CUDA)
+#define __DEF_IF_HOST { }
+#else  /* !__CUDA_ARCH__ */
+#define __DEF_IF_HOST ;
+#endif /* __CUDA_ARCH__ */
+
+
+
+#ifdef __CUDA_ARCH__ 
+extern "C"
+{
+extern __device__ __device_builtin__ double __dAtomicAdd(double *address, double val);
+
+extern __device__ __device_builtin__
+int __iAtomicAdd_block(int *address, int val);
+
+extern __device__ __device_builtin__
+int __iAtomicAdd_system(int *address, int val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicAdd_block(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicAdd_system(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned long long __ullAtomicAdd_block(unsigned long long *address, unsigned long long val);
+
+extern __device__ __device_builtin__
+unsigned long long __ullAtomicAdd_system(unsigned long long *address, unsigned long long val);
+
+extern __device__ __device_builtin__
+float __fAtomicAdd_block(float *address, float val);
+
+extern __device__ __device_builtin__
+float __fAtomicAdd_system(float *address, float val);
+
+extern __device__ __device_builtin__
+double __dAtomicAdd_block(double *address, double val);
+
+extern __device__ __device_builtin__
+double __dAtomicAdd_system(double *address, double val);
+
+extern __device__ __device_builtin__
+int __iAtomicExch_block(int *address, int val);
+
+extern __device__ __device_builtin__
+int __iAtomicExch_system(int *address, int val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicExch_block(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicExch_system(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned long long __ullAtomicExch_block(unsigned long long *address, unsigned long long val);
+
+extern __device__ __device_builtin__
+unsigned long long __ullAtomicExch_system(unsigned long long *address, unsigned long long val);
+
+extern __device__ __device_builtin__
+float __fAtomicExch_block(float *address, float val);
+
+extern __device__ __device_builtin__
+float __fAtomicExch_system(float *address, float val);
+
+extern __device__ __device_builtin__
+int __iAtomicMin_block(int *address, int val);
+
+extern __device__ __device_builtin__
+int __iAtomicMin_system(int *address, int val);
+
+extern __device__ __device_builtin__
+long long __illAtomicMin_block(long long *address, long long val);
+
+extern __device__ __device_builtin__
+long long __illAtomicMin_system(long long *address, long long val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicMin_block(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicMin_system(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned long long __ullAtomicMin_block(unsigned long long *address, unsigned long long val);
+
+extern __device__ __device_builtin__
+unsigned long long __ullAtomicMin_system(unsigned long long *address, unsigned long long val);
+
+extern __device__ __device_builtin__
+int __iAtomicMax_block(int *address, int val);
+
+extern __device__ __device_builtin__
+int __iAtomicMax_system(int *address, int val);
+
+extern __device__ __device_builtin__
+long long __illAtomicMax_block(long long *address, long long val);
+
+extern __device__ __device_builtin__
+long long __illAtomicMax_system(long long *address, long long val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicMax_block(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicMax_system(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned long long __ullAtomicMax_block(unsigned long long *address, unsigned long long val);
+
+extern __device__ __device_builtin__
+unsigned long long __ullAtomicMax_system(unsigned long long *address, unsigned long long val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicInc_block(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicInc_system(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicDec_block(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicDec_system(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+int __iAtomicCAS_block(int *address, int compare, int val);
+
+extern __device__ __device_builtin__
+int __iAtomicCAS_system(int *address, int compare, int val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicCAS_block(unsigned int *address, unsigned int compare,
+                                unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicCAS_system(unsigned int *address, unsigned int compare,
+                                 unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned long long __ullAtomicCAS_block(unsigned long long int *address,
+                                        unsigned long long int compare,
+                                        unsigned long long int val);
+
+extern __device__ __device_builtin__
+unsigned long long __ullAtomicCAS_system(unsigned long long int *address,
+                                         unsigned long long int compare,
+                                         unsigned long long int val);
+
+extern __device__ __device_builtin__
+int __iAtomicAnd_block(int *address, int val);
+
+extern __device__ __device_builtin__
+int __iAtomicAnd_system(int *address, int val);
+
+extern __device__ __device_builtin__
+long long __llAtomicAnd_block(long long *address, long long val);
+
+extern __device__ __device_builtin__
+long long __llAtomicAnd_system(long long *address, long long val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicAnd_block(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicAnd_system(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned long long __ullAtomicAnd_block(unsigned long long *address, unsigned long long val);
+
+extern __device__ __device_builtin__
+unsigned long long __ullAtomicAnd_system(unsigned long long *address, unsigned long long val);
+
+extern __device__ __device_builtin__
+int __iAtomicOr_block(int *address, int val);
+
+extern __device__ __device_builtin__
+int __iAtomicOr_system(int *address, int val);
+
+extern __device__ __device_builtin__
+long long __llAtomicOr_block(long long *address, long long val);
+
+extern __device__ __device_builtin__
+long long __llAtomicOr_system(long long *address, long long val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicOr_block(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicOr_system(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned long long __ullAtomicOr_block(unsigned long long *address, unsigned long long val);
+
+extern __device__ __device_builtin__
+unsigned long long __ullAtomicOr_system(unsigned long long *address, unsigned long long val);
+
+extern __device__ __device_builtin__
+int __iAtomicXor_block(int *address, int val);
+
+extern __device__ __device_builtin__
+int __iAtomicXor_system(int *address, int val);
+
+extern __device__ __device_builtin__
+long long __llAtomicXor_block(long long *address, long long val);
+
+extern __device__ __device_builtin__
+long long __llAtomicXor_system(long long *address, long long val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicXor_block(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned int __uAtomicXor_system(unsigned int *address, unsigned int val);
+
+extern __device__ __device_builtin__
+unsigned long long __ullAtomicXor_block(unsigned long long *address, unsigned long long val);
+
+extern __device__ __device_builtin__
+unsigned long long __ullAtomicXor_system(unsigned long long *address, unsigned long long val);
+}
+#endif /* __CUDA_ARCH__ */
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__ double atomicAdd(double *address, double val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicAdd_block(int *address, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicAdd_system(int *address, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicAdd_block(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicAdd_system(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicAdd_block(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicAdd_system(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+float atomicAdd_block(float *address, float val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+float atomicAdd_system(float *address, float val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+double atomicAdd_block(double *address, double val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+double atomicAdd_system(double *address, double val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicSub_block(int *address, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicSub_system(int *address, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicSub_block(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicSub_system(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicExch_block(int *address, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicExch_system(int *address, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicExch_block(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicExch_system(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicExch_block(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicExch_system(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+float atomicExch_block(float *address, float val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+float atomicExch_system(float *address, float val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicMin_block(int *address, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicMin_system(int *address, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicMin_block(long long *address, long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicMin_system(long long *address, long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicMin_block(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicMin_system(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicMin_block(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicMin_system(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicMax_block(int *address, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicMax_system(int *address, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicMax_block(long long *address, long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicMax_system(long long *address, long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicMax_block(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicMax_system(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicMax_block(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicMax_system(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicInc_block(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicInc_system(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicDec_block(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicDec_system(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicCAS_block(int *address, int compare, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicCAS_system(int *address, int compare, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicCAS_block(unsigned int *address, unsigned int compare,
+                             unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicCAS_system(unsigned int *address, unsigned int compare,
+                              unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long int atomicCAS_block(unsigned long long int *address,
+                                       unsigned long long int compare,
+                                       unsigned long long int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long int atomicCAS_system(unsigned long long int *address,
+                                        unsigned long long int compare,
+                                        unsigned long long int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicAnd_block(int *address, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicAnd_system(int *address, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicAnd_block(long long *address, long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicAnd_system(long long *address, long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicAnd_block(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicAnd_system(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicAnd_block(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicAnd_system(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicOr_block(int *address, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicOr_system(int *address, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicOr_block(long long *address, long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicOr_system(long long *address, long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicOr_block(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicOr_system(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicOr_block(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicOr_system(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicXor_block(int *address, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicXor_system(int *address, int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicXor_block(long long *address, long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicXor_system(long long *address, long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicXor_block(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicXor_system(unsigned int *address, unsigned int val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicXor_block(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicXor_system(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
+
+#endif /* !__CUDA_ARCH__ || __CUDA_ARCH__ >= 600 */
+
+#endif /* __cplusplus && __CUDACC__ */
+
+#undef __SM_60_ATOMIC_FUNCTIONS_DECL__
+#undef __DEF_IF_HOST
+
+#if !defined(__CUDACC_RTC__) && defined(__CUDA_ARCH__)
+#include "sm_60_atomic_functions.hpp"
+#endif /* !__CUDACC_RTC__  && defined(__CUDA_ARCH__)  */
+
+#endif /* !__SM_60_ATOMIC_FUNCTIONS_H__ */
+

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/sm_60_atomic_functions.hpp

@@ -0,0 +1,527 @@
+/*
+ * Copyright 1993-2014 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__SM_60_ATOMIC_FUNCTIONS_HPP__)
+#define __SM_60_ATOMIC_FUNCTIONS_HPP__
+
+#if defined(__CUDACC_RTC__)
+#define __SM_60_ATOMIC_FUNCTIONS_DECL__ __device__
+#else /* __CUDACC_RTC__ */
+#define __SM_60_ATOMIC_FUNCTIONS_DECL__ static __inline__ __device__
+#endif /* __CUDACC_RTC__ */
+
+#if defined(__cplusplus) && defined(__CUDACC__)
+
+#if defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 600
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+#include "cuda_runtime_api.h"
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__ double atomicAdd(double *address, double val)
+{
+  return __dAtomicAdd(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicAdd_block(int *address, int val)
+{
+  return __iAtomicAdd_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicAdd_system(int *address, int val)
+{
+  return __iAtomicAdd_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicAdd_block(unsigned int *address, unsigned int val)
+{
+  return __uAtomicAdd_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicAdd_system(unsigned int *address, unsigned int val)
+{
+  return __uAtomicAdd_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicAdd_block(unsigned long long *address, unsigned long long val)
+{
+  return __ullAtomicAdd_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicAdd_system(unsigned long long *address, unsigned long long val)
+{
+  return __ullAtomicAdd_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+float atomicAdd_block(float *address, float val)
+{
+  return __fAtomicAdd_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+float atomicAdd_system(float *address, float val)
+{
+  return __fAtomicAdd_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+double atomicAdd_block(double *address, double val)
+{
+  return __dAtomicAdd_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+double atomicAdd_system(double *address, double val)
+{
+  return __dAtomicAdd_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicSub_block(int *address, int val)
+{
+  return __iAtomicAdd_block(address, (unsigned int)-(int)val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicSub_system(int *address, int val)
+{
+  return __iAtomicAdd_system(address, (unsigned int)-(int)val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicSub_block(unsigned int *address, unsigned int val)
+{
+  return __uAtomicAdd_block(address, (unsigned int)-(int)val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicSub_system(unsigned int *address, unsigned int val)
+{
+  return __uAtomicAdd_system(address, (unsigned int)-(int)val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicExch_block(int *address, int val)
+{
+  return __iAtomicExch_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicExch_system(int *address, int val)
+{
+  return __iAtomicExch_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicExch_block(unsigned int *address, unsigned int val)
+{
+  return __uAtomicExch_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicExch_system(unsigned int *address, unsigned int val)
+{
+  return __uAtomicExch_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicExch_block(unsigned long long *address, unsigned long long val)
+{
+  return __ullAtomicExch_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicExch_system(unsigned long long *address, unsigned long long val)
+{
+  return __ullAtomicExch_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+float atomicExch_block(float *address, float val)
+{
+  return __fAtomicExch_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+float atomicExch_system(float *address, float val)
+{
+  return __fAtomicExch_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicMin_block(int *address, int val)
+{
+  return __iAtomicMin_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicMin_system(int *address, int val)
+{
+  return __iAtomicMin_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicMin_block(long long *address, long long val)
+{
+  return __illAtomicMin_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicMin_system(long long *address, long long val)
+{
+  return __illAtomicMin_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicMin_block(unsigned int *address, unsigned int val)
+{
+  return __uAtomicMin_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicMin_system(unsigned int *address, unsigned int val)
+{
+  return __uAtomicMin_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicMin_block(unsigned long long *address, unsigned long long val)
+{
+  return __ullAtomicMin_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicMin_system(unsigned long long *address, unsigned long long val)
+{
+  return __ullAtomicMin_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicMax_block(int *address, int val)
+{
+  return __iAtomicMax_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicMax_system(int *address, int val)
+{
+  return __iAtomicMax_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicMax_block(long long *address, long long val)
+{
+  return __illAtomicMax_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicMax_system(long long *address, long long val)
+{
+  return __illAtomicMax_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicMax_block(unsigned int *address, unsigned int val)
+{
+  return __uAtomicMax_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicMax_system(unsigned int *address, unsigned int val)
+{
+  return __uAtomicMax_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicMax_block(unsigned long long *address, unsigned long long val)
+{
+  return __ullAtomicMax_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicMax_system(unsigned long long *address, unsigned long long val)
+{
+  return __ullAtomicMax_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicInc_block(unsigned int *address, unsigned int val)
+{
+  return __uAtomicInc_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicInc_system(unsigned int *address, unsigned int val)
+{
+  return __uAtomicInc_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicDec_block(unsigned int *address, unsigned int val)
+{
+  return __uAtomicDec_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicDec_system(unsigned int *address, unsigned int val)
+{
+  return __uAtomicDec_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicCAS_block(int *address, int compare, int val)
+{
+  return __iAtomicCAS_block(address, compare, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicCAS_system(int *address, int compare, int val)
+{
+  return __iAtomicCAS_system(address, compare, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicCAS_block(unsigned int *address, unsigned int compare,
+                             unsigned int val)
+{
+  return __uAtomicCAS_block(address, compare, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicCAS_system(unsigned int *address, unsigned int compare,
+                              unsigned int val)
+{
+  return __uAtomicCAS_system(address, compare, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long int atomicCAS_block(unsigned long long int *address,
+                                       unsigned long long int compare,
+                                       unsigned long long int val)
+{
+  return __ullAtomicCAS_block(address, compare, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long int atomicCAS_system(unsigned long long int *address,
+                                        unsigned long long int compare,
+                                        unsigned long long int val)
+{
+  return __ullAtomicCAS_system(address, compare, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicAnd_block(int *address, int val)
+{
+  return __iAtomicAnd_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicAnd_system(int *address, int val)
+{
+  return __iAtomicAnd_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicAnd_block(long long *address, long long val)
+{
+  return __llAtomicAnd_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicAnd_system(long long *address, long long val)
+{
+  return __llAtomicAnd_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicAnd_block(unsigned int *address, unsigned int val)
+{
+  return __uAtomicAnd_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicAnd_system(unsigned int *address, unsigned int val)
+{
+  return __uAtomicAnd_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicAnd_block(unsigned long long *address, unsigned long long val)
+{
+  return __ullAtomicAnd_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicAnd_system(unsigned long long *address, unsigned long long val)
+{
+  return __ullAtomicAnd_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicOr_block(int *address, int val)
+{
+  return __iAtomicOr_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicOr_system(int *address, int val)
+{
+  return __iAtomicOr_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicOr_block(long long *address, long long val)
+{
+  return __llAtomicOr_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicOr_system(long long *address, long long val)
+{
+  return __llAtomicOr_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicOr_block(unsigned int *address, unsigned int val)
+{
+  return __uAtomicOr_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicOr_system(unsigned int *address, unsigned int val)
+{
+  return __uAtomicOr_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicOr_block(unsigned long long *address, unsigned long long val)
+{
+  return __ullAtomicOr_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicOr_system(unsigned long long *address, unsigned long long val)
+{
+  return __ullAtomicOr_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicXor_block(int *address, int val)
+{
+  return __iAtomicXor_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+int atomicXor_system(int *address, int val)
+{
+  return __iAtomicXor_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicXor_block(long long *address, long long val)
+{
+  return __llAtomicXor_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+long long atomicXor_system(long long *address, long long val)
+{
+  return __llAtomicXor_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicXor_block(unsigned int *address, unsigned int val)
+{
+  return __uAtomicXor_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned int atomicXor_system(unsigned int *address, unsigned int val)
+{
+  return __uAtomicXor_system(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicXor_block(unsigned long long *address, unsigned long long val)
+{
+  return __ullAtomicXor_block(address, val);
+}
+
+__SM_60_ATOMIC_FUNCTIONS_DECL__
+unsigned long long atomicXor_system(unsigned long long *address, unsigned long long val)
+{
+  return __ullAtomicXor_system(address, val);
+}
+
+#endif /* !__CUDA_ARCH__ || __CUDA_ARCH__ >= 600 */
+
+#endif /* __cplusplus && __CUDACC__ */
+
+#undef __SM_60_ATOMIC_FUNCTIONS_DECL__
+
+#endif /* !__SM_60_ATOMIC_FUNCTIONS_HPP__ */
+

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/sm_61_intrinsics.hpp

@@ -0,0 +1,161 @@
+/*
+ * Copyright 2016 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__SM_61_INTRINSICS_HPP__)
+#define __SM_61_INTRINSICS_HPP__
+
+#if defined(__CUDACC_RTC__)
+#define __SM_61_INTRINSICS_DECL__ __device__
+#else /* !__CUDACC_RTC__ */
+#define __SM_61_INTRINSICS_DECL__ static __device__ __inline__
+#endif /* __CUDACC_RTC__ */
+
+#if defined(__cplusplus) && defined(__CUDACC__)
+
+#if defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 610
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+#include "cuda_runtime_api.h"
+
+/*******************************************************************************
+*                                                                              *
+*  Below are implementations of SM-6.1 intrinsics which are included as        *
+*  source (instead of being built in to the compiler)                          *
+*                                                                              *
+*******************************************************************************/
+
+// 4a
+__SM_61_INTRINSICS_DECL__ int __dp4a(int srcA, int srcB, int c) {
+    int ret;
+    asm volatile ("dp4a.s32.s32 %0, %1, %2, %3;" : "=r"(ret) : "r"(srcA), "r"(srcB), "r"(c));
+    return ret;
+}
+
+__SM_61_INTRINSICS_DECL__ unsigned int __dp4a(unsigned int srcA, unsigned int srcB, unsigned int c) {
+    unsigned int ret;
+    asm volatile ("dp4a.u32.u32 %0, %1, %2, %3;" : "=r"(ret) : "r"(srcA), "r"(srcB), "r"(c));
+    return ret;
+}
+
+__SM_61_INTRINSICS_DECL__ int __dp4a(char4 srcA, char4 srcB, int c) {
+    int ret;
+    asm volatile ("dp4a.s32.s32 %0, %1, %2, %3;" : "=r"(ret) : "r"(*(int *)&srcA), "r"(*(int *)&srcB), "r"(c));
+    return ret;
+}
+
+__SM_61_INTRINSICS_DECL__ unsigned int __dp4a(uchar4 srcA, uchar4 srcB, unsigned int c) {
+    unsigned int ret;
+    asm volatile ("dp4a.u32.u32 %0, %1, %2, %3;" : "=r"(ret) : "r"(*(unsigned int *)&srcA), "r"(*(unsigned int *)&srcB), "r"(c));
+    return ret;
+}
+
+// 2a.lo
+__SM_61_INTRINSICS_DECL__ int __dp2a_lo(int srcA, int srcB, int c) {
+    int ret;
+    asm volatile ("dp2a.lo.s32.s32 %0, %1, %2, %3;" : "=r"(ret) : "r"(srcA), "r"(srcB), "r"(c));
+    return ret;
+}
+
+__SM_61_INTRINSICS_DECL__ unsigned int __dp2a_lo(unsigned int srcA, unsigned int srcB, unsigned int c) {
+    unsigned int ret;
+    asm volatile ("dp2a.lo.u32.u32 %0, %1, %2, %3;" : "=r"(ret) : "r"(srcA), "r"(srcB), "r"(c));
+    return ret;
+}
+
+__SM_61_INTRINSICS_DECL__ int __dp2a_lo(short2 srcA, char4 srcB, int c) {
+    int ret;
+    asm volatile ("dp2a.lo.s32.s32 %0, %1, %2, %3;" : "=r"(ret) : "r"(*(int *)&srcA), "r"(*(int *)&srcB), "r"(c));
+    return ret;
+}
+
+__SM_61_INTRINSICS_DECL__ unsigned int __dp2a_lo(ushort2 srcA, uchar4 srcB, unsigned int c) {
+    unsigned int ret;
+    asm volatile ("dp2a.lo.u32.u32 %0, %1, %2, %3;" : "=r"(ret) : "r"(*(unsigned int *)&srcA), "r"(*(unsigned int *)&srcB), "r"(c));
+    return ret;
+}
+
+// 2a.hi
+__SM_61_INTRINSICS_DECL__ int __dp2a_hi(int srcA, int srcB, int c) {
+    int ret;
+    asm volatile ("dp2a.hi.s32.s32 %0, %1, %2, %3;" : "=r"(ret) : "r"(srcA), "r"(srcB), "r"(c));
+    return ret;
+}
+
+__SM_61_INTRINSICS_DECL__ unsigned int __dp2a_hi(unsigned int srcA, unsigned int srcB, unsigned int c) {
+    unsigned int ret;
+    asm volatile ("dp2a.hi.u32.u32 %0, %1, %2, %3;" : "=r"(ret) : "r"(srcA), "r"(srcB), "r"(c));
+    return ret;
+}
+
+__SM_61_INTRINSICS_DECL__ int __dp2a_hi(short2 srcA, char4 srcB, int c) {
+    int ret;
+    asm volatile ("dp2a.hi.s32.s32 %0, %1, %2, %3;" : "=r"(ret) : "r"(*(int *)&srcA), "r"(*(int *)&srcB), "r"(c));
+    return ret;
+}
+
+__SM_61_INTRINSICS_DECL__ unsigned int __dp2a_hi(ushort2 srcA, uchar4 srcB, unsigned int c) {
+    unsigned int ret;
+    asm volatile ("dp2a.hi.u32.u32 %0, %1, %2, %3;" : "=r"(ret) : "r"(*(unsigned int *)&srcA), "r"(*(unsigned int *)&srcB), "r"(c));
+    return ret;
+}
+
+
+#endif /* _NVHPC_CUDA || !__CUDA_ARCH__ || __CUDA_ARCH__ >= 610 */
+
+#endif /* __cplusplus && __CUDACC__ */
+
+#undef __SM_61_INTRINSICS_DECL__
+
+#endif /* !__SM_61_INTRINSICS_HPP__ */
+

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/surface_functions.h

@@ -0,0 +1,124 @@
+/*
+ * Copyright 1993-2022 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__SURFACE_FUNCTIONS_H__)
+#define __SURFACE_FUNCTIONS_H__
+
+
+#if defined(__cplusplus) && defined(__CUDACC__)
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+#include "cuda_runtime_api.h"
+#include "cuda_surface_types.h"
+
+#if defined(_WIN32)
+# define __DEPRECATED__ __declspec(deprecated)
+#else
+# define __DEPRECATED__  __attribute__((deprecated))
+#endif
+
+template <typename T> struct __nv_surf_trait {  typedef void * cast_type; };
+
+template<> struct __nv_surf_trait<char> {  typedef char * cast_type; };
+template<> struct __nv_surf_trait<signed char> {  typedef signed char * cast_type; };
+template<> struct __nv_surf_trait<unsigned char> {  typedef unsigned char * cast_type; };
+template<> struct __nv_surf_trait<char1> {  typedef char1 * cast_type; };
+template<> struct __nv_surf_trait<uchar1> {  typedef uchar1 * cast_type; };
+template<> struct __nv_surf_trait<char2> {  typedef char2 * cast_type; };
+template<> struct __nv_surf_trait<uchar2> {  typedef uchar2 * cast_type; };
+template<> struct __nv_surf_trait<char4> {  typedef char4 * cast_type; };
+template<> struct __nv_surf_trait<uchar4> {  typedef uchar4 * cast_type; };
+template<> struct __nv_surf_trait<short> {  typedef short * cast_type; };
+template<> struct __nv_surf_trait<unsigned short> {  typedef unsigned short * cast_type; };
+template<> struct __nv_surf_trait<short1> {  typedef short1 * cast_type; };
+template<> struct __nv_surf_trait<ushort1> {  typedef ushort1 * cast_type; };
+template<> struct __nv_surf_trait<short2> {  typedef short2 * cast_type; };
+template<> struct __nv_surf_trait<ushort2> {  typedef ushort2 * cast_type; };
+template<> struct __nv_surf_trait<short4> {  typedef short4 * cast_type; };
+template<> struct __nv_surf_trait<ushort4> {  typedef ushort4 * cast_type; };
+template<> struct __nv_surf_trait<int> {  typedef int * cast_type; };
+template<> struct __nv_surf_trait<unsigned int> {  typedef unsigned int * cast_type; };
+template<> struct __nv_surf_trait<int1> {  typedef int1 * cast_type; };
+template<> struct __nv_surf_trait<uint1> {  typedef uint1 * cast_type; };
+template<> struct __nv_surf_trait<int2> {  typedef int2 * cast_type; };
+template<> struct __nv_surf_trait<uint2> {  typedef uint2 * cast_type; };
+template<> struct __nv_surf_trait<int4> {  typedef int4 * cast_type; };
+template<> struct __nv_surf_trait<uint4> {  typedef uint4 * cast_type; };
+template<> struct __nv_surf_trait<long long> {  typedef long long * cast_type; };
+template<> struct __nv_surf_trait<unsigned long long> {  typedef unsigned long long * cast_type; };
+template<> struct __nv_surf_trait<longlong1> {  typedef longlong1 * cast_type; };
+template<> struct __nv_surf_trait<ulonglong1> {  typedef ulonglong1 * cast_type; };
+template<> struct __nv_surf_trait<longlong2> {  typedef longlong2 * cast_type; };
+template<> struct __nv_surf_trait<ulonglong2> {  typedef ulonglong2 * cast_type; };
+#if !defined(__LP64__)
+template<> struct __nv_surf_trait<long> {  typedef int * cast_type; };
+template<> struct __nv_surf_trait<unsigned long> {  typedef unsigned int * cast_type; };
+template<> struct __nv_surf_trait<long1> {  typedef int1 * cast_type; };
+template<> struct __nv_surf_trait<ulong1> {  typedef uint1 * cast_type; };
+template<> struct __nv_surf_trait<long2> {  typedef int2 * cast_type; };
+template<> struct __nv_surf_trait<ulong2> {  typedef uint2 * cast_type; };
+template<> struct __nv_surf_trait<long4> {  typedef uint4 * cast_type; };
+template<> struct __nv_surf_trait<ulong4> {  typedef int4 * cast_type; };
+#endif
+template<> struct __nv_surf_trait<float> {  typedef float * cast_type; };
+template<> struct __nv_surf_trait<float1> {  typedef float1 * cast_type; };
+template<> struct __nv_surf_trait<float2> {  typedef float2 * cast_type; };
+template<> struct __nv_surf_trait<float4> {  typedef float4 * cast_type; };
+
+
+#undef __DEPRECATED__
+
+
+#endif /* __cplusplus && __CUDACC__ */
+#endif /* !__SURFACE_FUNCTIONS_H__ */

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/surface_indirect_functions.h

@@ -0,0 +1,243 @@
+/*
+ * Copyright 1993-2022 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+
+#ifndef __SURFACE_INDIRECT_FUNCTIONS_H__
+#define __SURFACE_INDIRECT_FUNCTIONS_H__
+
+#if defined(__cplusplus) && defined(__CUDACC__)
+
+#include "cuda_runtime_api.h"
+
+template<typename T> struct __nv_isurf_trait { };
+template<> struct __nv_isurf_trait<char> { typedef void type; };
+template<> struct __nv_isurf_trait<signed char> { typedef void type; };
+template<> struct __nv_isurf_trait<char1> { typedef void type; };
+template<> struct __nv_isurf_trait<unsigned char> { typedef void type; };
+template<> struct __nv_isurf_trait<uchar1> { typedef void type; };
+template<> struct __nv_isurf_trait<short> { typedef void type; };
+template<> struct __nv_isurf_trait<short1> { typedef void type; };
+template<> struct __nv_isurf_trait<unsigned short> { typedef void type; };
+template<> struct __nv_isurf_trait<ushort1> { typedef void type; };
+template<> struct __nv_isurf_trait<int> { typedef void type; };
+template<> struct __nv_isurf_trait<int1> { typedef void type; };
+template<> struct __nv_isurf_trait<unsigned int> { typedef void type; };
+template<> struct __nv_isurf_trait<uint1> { typedef void type; };
+template<> struct __nv_isurf_trait<long long> { typedef void type; };
+template<> struct __nv_isurf_trait<longlong1> { typedef void type; };
+template<> struct __nv_isurf_trait<unsigned long long> { typedef void type; };
+template<> struct __nv_isurf_trait<ulonglong1> { typedef void type; };
+template<> struct __nv_isurf_trait<float> { typedef void type; };
+template<> struct __nv_isurf_trait<float1> { typedef void type; };
+
+template<> struct __nv_isurf_trait<char2> { typedef void type; };
+template<> struct __nv_isurf_trait<uchar2> { typedef void type; };
+template<> struct __nv_isurf_trait<short2> { typedef void type; };
+template<> struct __nv_isurf_trait<ushort2> { typedef void type; };
+template<> struct __nv_isurf_trait<int2> { typedef void type; };
+template<> struct __nv_isurf_trait<uint2> { typedef void type; };
+template<> struct __nv_isurf_trait<longlong2> { typedef void type; };
+template<> struct __nv_isurf_trait<ulonglong2> { typedef void type; };
+template<> struct __nv_isurf_trait<float2> { typedef void type; };
+
+template<> struct __nv_isurf_trait<char4> { typedef void type; };
+template<> struct __nv_isurf_trait<uchar4> { typedef void type; };
+template<> struct __nv_isurf_trait<short4> { typedef void type; };
+template<> struct __nv_isurf_trait<ushort4> { typedef void type; };
+template<> struct __nv_isurf_trait<int4> { typedef void type; };
+template<> struct __nv_isurf_trait<uint4> { typedef void type; };
+template<> struct __nv_isurf_trait<float4> { typedef void type; };
+
+
+template <typename T>
+static __device__ typename __nv_isurf_trait<T>::type  surf1Dread(T *ptr, cudaSurfaceObject_t obj, int x, cudaSurfaceBoundaryMode mode = cudaBoundaryModeTrap)
+{
+  __nv_tex_surf_handler("__isurf1Dread", ptr, obj, x, mode);
+}
+
+template <class T>
+static __device__ T surf1Dread(cudaSurfaceObject_t surfObject, int x, cudaSurfaceBoundaryMode boundaryMode = cudaBoundaryModeTrap)
+{
+   T ret;
+   surf1Dread(&ret, surfObject, x, boundaryMode);
+   return ret;
+}
+
+template <typename T>
+static __device__ typename __nv_isurf_trait<T>::type  surf2Dread(T *ptr, cudaSurfaceObject_t obj, int x, int y, cudaSurfaceBoundaryMode mode = cudaBoundaryModeTrap)
+{
+  __nv_tex_surf_handler("__isurf2Dread", ptr, obj, x, y, mode);
+}
+
+template <class T>
+static __device__ T surf2Dread(cudaSurfaceObject_t surfObject, int x, int y, cudaSurfaceBoundaryMode boundaryMode = cudaBoundaryModeTrap)
+{
+   T ret;
+   surf2Dread(&ret, surfObject, x, y, boundaryMode);
+   return ret;
+}
+
+
+template <typename T>
+static __device__ typename  __nv_isurf_trait<T>::type  surf3Dread(T *ptr, cudaSurfaceObject_t obj, int x, int y, int z, cudaSurfaceBoundaryMode mode = cudaBoundaryModeTrap)
+{
+  __nv_tex_surf_handler("__isurf3Dread", ptr, obj, x, y, z, mode);
+}
+
+template <class T>
+static __device__ T surf3Dread(cudaSurfaceObject_t surfObject, int x, int y, int z, cudaSurfaceBoundaryMode boundaryMode = cudaBoundaryModeTrap)
+{
+   T ret;
+   surf3Dread(&ret, surfObject, x, y, z, boundaryMode);
+   return ret;
+}
+
+template <typename T>
+static __device__ typename  __nv_isurf_trait<T>::type  surf1DLayeredread(T *ptr, cudaSurfaceObject_t obj, int x, int layer, cudaSurfaceBoundaryMode mode = cudaBoundaryModeTrap)
+{
+  __nv_tex_surf_handler("__isurf1DLayeredread", ptr, obj, x, layer, mode);
+}
+
+template <class T>
+static __device__ T surf1DLayeredread(cudaSurfaceObject_t surfObject, int x, int layer, cudaSurfaceBoundaryMode boundaryMode = cudaBoundaryModeTrap)
+{
+   T ret;
+   surf1DLayeredread(&ret, surfObject, x, layer, boundaryMode);
+   return ret;
+}
+
+template <typename T>
+static __device__  typename __nv_isurf_trait<T>::type  surf2DLayeredread(T *ptr, cudaSurfaceObject_t obj, int x, int y, int layer, cudaSurfaceBoundaryMode mode = cudaBoundaryModeTrap)
+{
+  __nv_tex_surf_handler("__isurf2DLayeredread", ptr, obj, x, y, layer, mode);
+}
+
+template <class T>
+static __device__ T surf2DLayeredread(cudaSurfaceObject_t surfObject, int x, int y, int layer, cudaSurfaceBoundaryMode boundaryMode = cudaBoundaryModeTrap)
+{
+   T ret;
+   surf2DLayeredread(&ret, surfObject, x, y, layer, boundaryMode);
+   return ret;
+}
+
+template <typename T>
+static __device__ typename __nv_isurf_trait<T>::type  surfCubemapread(T *ptr, cudaSurfaceObject_t obj, int x, int y, int face, cudaSurfaceBoundaryMode mode = cudaBoundaryModeTrap)
+{
+  __nv_tex_surf_handler("__isurfCubemapread", ptr, obj, x, y, face, mode);
+}
+
+template <class T>
+static __device__ T surfCubemapread(cudaSurfaceObject_t surfObject, int x, int y, int face, cudaSurfaceBoundaryMode boundaryMode = cudaBoundaryModeTrap)
+{
+   T ret;
+   surfCubemapread(&ret, surfObject, x, y, face, boundaryMode);
+   return ret;
+}
+
+template <typename T>
+static __device__  typename __nv_isurf_trait<T>::type  surfCubemapLayeredread(T *ptr, cudaSurfaceObject_t obj, int x, int y, int layerface, cudaSurfaceBoundaryMode mode = cudaBoundaryModeTrap)
+{
+  __nv_tex_surf_handler("__isurfCubemapLayeredread", ptr, obj, x, y, layerface, mode);
+}
+
+template <class T>
+static __device__ T surfCubemapLayeredread(cudaSurfaceObject_t surfObject, int x, int y, int layerface, cudaSurfaceBoundaryMode boundaryMode = cudaBoundaryModeTrap)
+{
+   T ret;
+   surfCubemapLayeredread(&ret, surfObject, x, y, layerface, boundaryMode);
+   return ret;
+}
+
+template <typename T>
+static __device__ typename __nv_isurf_trait<T>::type surf1Dwrite(T val, cudaSurfaceObject_t obj, int x, cudaSurfaceBoundaryMode mode = cudaBoundaryModeTrap)
+{ 
+  __nv_tex_surf_handler("__isurf1Dwrite_v2", &val, obj, x, mode);
+}
+
+template <typename T>
+static __device__ typename __nv_isurf_trait<T>::type surf2Dwrite(T val, cudaSurfaceObject_t obj, int x, int y, cudaSurfaceBoundaryMode mode = cudaBoundaryModeTrap)
+{
+  __nv_tex_surf_handler("__isurf2Dwrite_v2", &val, obj, x, y, mode);
+}
+
+template <typename T>
+static __device__ typename __nv_isurf_trait<T>::type surf3Dwrite(T val, cudaSurfaceObject_t obj, int x, int y, int z, cudaSurfaceBoundaryMode mode = cudaBoundaryModeTrap)
+{
+  __nv_tex_surf_handler("__isurf3Dwrite_v2", &val, obj, x, y, z, mode);
+}
+
+template <typename T>
+static __device__ typename __nv_isurf_trait<T>::type surf1DLayeredwrite(T val, cudaSurfaceObject_t obj, int x, int layer, cudaSurfaceBoundaryMode mode = cudaBoundaryModeTrap)
+{
+  __nv_tex_surf_handler("__isurf1DLayeredwrite_v2", &val, obj, x, layer, mode);
+}
+
+template <typename T>
+static __device__ typename __nv_isurf_trait<T>::type surf2DLayeredwrite(T val, cudaSurfaceObject_t obj, int x, int y, int layer, cudaSurfaceBoundaryMode mode = cudaBoundaryModeTrap)
+{
+  __nv_tex_surf_handler("__isurf2DLayeredwrite_v2", &val, obj, x, y, layer, mode);
+}
+
+template <typename T>
+static __device__ typename __nv_isurf_trait<T>::type surfCubemapwrite(T val, cudaSurfaceObject_t obj, int x, int y, int face, cudaSurfaceBoundaryMode mode = cudaBoundaryModeTrap)
+{
+  __nv_tex_surf_handler("__isurfCubemapwrite_v2", &val, obj, x, y, face, mode);
+}
+
+template <typename T>
+static __device__ typename __nv_isurf_trait<T>::type surfCubemapLayeredwrite(T val, cudaSurfaceObject_t obj, int x, int y, int layerface, cudaSurfaceBoundaryMode mode = cudaBoundaryModeTrap)
+{
+  __nv_tex_surf_handler("__isurfCubemapLayeredwrite_v2", &val, obj, x, y, layerface, mode);
+}
+
+#endif // __cplusplus && __CUDACC__
+
+#endif // __SURFACE_INDIRECT_FUNCTIONS_H__
+
+

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/texture_fetch_functions.h

@@ -0,0 +1,223 @@
+/*
+ * Copyright 1993-2022 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__TEXTURE_FETCH_FUNCTIONS_H__)
+#define __TEXTURE_FETCH_FUNCTIONS_H__
+
+
+#if defined(__cplusplus) && defined(__CUDACC__)
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+#include "cuda_runtime_api.h"
+#include "cuda_texture_types.h"
+
+#if defined(_WIN32)
+# define __DEPRECATED__ __declspec(deprecated)
+#else
+# define __DEPRECATED__  __attribute__((deprecated))
+#endif
+
+
+template <typename T>
+struct __nv_tex_rmet_ret { };
+
+template<> struct __nv_tex_rmet_ret<char> { typedef char type; };
+template<> struct __nv_tex_rmet_ret<signed char> { typedef signed char type; };
+template<> struct __nv_tex_rmet_ret<unsigned char> { typedef unsigned char type; };
+template<> struct __nv_tex_rmet_ret<char1> { typedef char1 type; };
+template<> struct __nv_tex_rmet_ret<uchar1> { typedef uchar1 type; };
+template<> struct __nv_tex_rmet_ret<char2> { typedef char2 type; };
+template<> struct __nv_tex_rmet_ret<uchar2> { typedef uchar2 type; };
+template<> struct __nv_tex_rmet_ret<char4> { typedef char4 type; };
+template<> struct __nv_tex_rmet_ret<uchar4> { typedef uchar4 type; };
+
+template<> struct __nv_tex_rmet_ret<short> { typedef short type; };
+template<> struct __nv_tex_rmet_ret<unsigned short> { typedef unsigned short type; };
+template<> struct __nv_tex_rmet_ret<short1> { typedef short1 type; };
+template<> struct __nv_tex_rmet_ret<ushort1> { typedef ushort1 type; };
+template<> struct __nv_tex_rmet_ret<short2> { typedef short2 type; };
+template<> struct __nv_tex_rmet_ret<ushort2> { typedef ushort2 type; };
+template<> struct __nv_tex_rmet_ret<short4> { typedef short4 type; };
+template<> struct __nv_tex_rmet_ret<ushort4> { typedef ushort4 type; };
+
+template<> struct __nv_tex_rmet_ret<int> { typedef int type; };
+template<> struct __nv_tex_rmet_ret<unsigned int> { typedef unsigned int type; };
+template<> struct __nv_tex_rmet_ret<int1> { typedef int1 type; };
+template<> struct __nv_tex_rmet_ret<uint1> { typedef uint1 type; };
+template<> struct __nv_tex_rmet_ret<int2> { typedef int2 type; };
+template<> struct __nv_tex_rmet_ret<uint2> { typedef uint2 type; };
+template<> struct __nv_tex_rmet_ret<int4> { typedef int4 type; };
+template<> struct __nv_tex_rmet_ret<uint4> { typedef uint4 type; };
+
+#if !defined(__LP64__)
+template<> struct __nv_tex_rmet_ret<long> { typedef long type; };
+template<> struct __nv_tex_rmet_ret<unsigned long> { typedef unsigned long type; };
+template<> struct __nv_tex_rmet_ret<long1> { typedef long1 type; };
+template<> struct __nv_tex_rmet_ret<ulong1> { typedef ulong1 type; };
+template<> struct __nv_tex_rmet_ret<long2> { typedef long2 type; };
+template<> struct __nv_tex_rmet_ret<ulong2> { typedef ulong2 type; };
+template<> struct __nv_tex_rmet_ret<long4> { typedef long4 type; };
+template<> struct __nv_tex_rmet_ret<ulong4> { typedef ulong4 type; };
+#endif /* !__LP64__ */
+template<> struct __nv_tex_rmet_ret<float> { typedef float type; };
+template<> struct __nv_tex_rmet_ret<float1> { typedef float1 type; };
+template<> struct __nv_tex_rmet_ret<float2> { typedef float2 type; };
+template<> struct __nv_tex_rmet_ret<float4> { typedef float4 type; };
+
+
+template <typename T> struct __nv_tex_rmet_cast { typedef T* type;  };
+#if !defined(__LP64__)
+template<> struct __nv_tex_rmet_cast<long> { typedef int *type; };
+template<> struct __nv_tex_rmet_cast<unsigned long> { typedef unsigned int *type; };
+template<> struct __nv_tex_rmet_cast<long1> { typedef int1 *type; };
+template<> struct __nv_tex_rmet_cast<ulong1> { typedef uint1 *type; };
+template<> struct __nv_tex_rmet_cast<long2> { typedef int2 *type; };
+template<> struct __nv_tex_rmet_cast<ulong2> { typedef uint2 *type; };
+template<> struct __nv_tex_rmet_cast<long4> { typedef int4 *type; };
+template<> struct __nv_tex_rmet_cast<ulong4> { typedef uint4 *type; };
+#endif /* !__LP64__ */
+
+template <typename T>
+struct __nv_tex_rmnf_ret { };
+
+template <> struct __nv_tex_rmnf_ret<char> { typedef float type; };
+template <> struct __nv_tex_rmnf_ret<signed char> { typedef float type; };
+template <> struct __nv_tex_rmnf_ret<unsigned char> { typedef float type; };
+template <> struct __nv_tex_rmnf_ret<short> { typedef float type; };
+template <> struct __nv_tex_rmnf_ret<unsigned short> { typedef float type; };
+template <> struct __nv_tex_rmnf_ret<char1> { typedef float1 type; };
+template <> struct __nv_tex_rmnf_ret<uchar1> { typedef float1 type; };
+template <> struct __nv_tex_rmnf_ret<short1> { typedef float1 type; };
+template <> struct __nv_tex_rmnf_ret<ushort1> { typedef float1 type; };
+template <> struct __nv_tex_rmnf_ret<char2> { typedef float2 type; };
+template <> struct __nv_tex_rmnf_ret<uchar2> { typedef float2 type; };
+template <> struct __nv_tex_rmnf_ret<short2> { typedef float2 type; };
+template <> struct __nv_tex_rmnf_ret<ushort2> { typedef float2 type; };
+template <> struct __nv_tex_rmnf_ret<char4> { typedef float4 type; };
+template <> struct __nv_tex_rmnf_ret<uchar4> { typedef float4 type; };
+template <> struct __nv_tex_rmnf_ret<short4> { typedef float4 type; };
+template <> struct __nv_tex_rmnf_ret<ushort4> { typedef float4 type; };
+
+
+template <typename T>
+struct __nv_tex2dgather_ret { };
+template <> struct __nv_tex2dgather_ret<char> { typedef char4 type; };
+template <> struct __nv_tex2dgather_ret<signed char> { typedef char4 type; };
+template <> struct __nv_tex2dgather_ret<char1> { typedef char4 type; };
+template <> struct __nv_tex2dgather_ret<char2> { typedef char4 type; };
+template <> struct __nv_tex2dgather_ret<char3> { typedef char4 type; };
+template <> struct __nv_tex2dgather_ret<char4> { typedef char4 type; };
+template <> struct __nv_tex2dgather_ret<unsigned char> { typedef uchar4 type; };
+template <> struct __nv_tex2dgather_ret<uchar1> { typedef uchar4 type; };
+template <> struct __nv_tex2dgather_ret<uchar2> { typedef uchar4 type; };
+template <> struct __nv_tex2dgather_ret<uchar3> { typedef uchar4 type; };
+template <> struct __nv_tex2dgather_ret<uchar4> { typedef uchar4 type; };
+
+template <> struct __nv_tex2dgather_ret<short> { typedef short4 type; };
+template <> struct __nv_tex2dgather_ret<short1> { typedef short4 type; };
+template <> struct __nv_tex2dgather_ret<short2> { typedef short4 type; };
+template <> struct __nv_tex2dgather_ret<short3> { typedef short4 type; };
+template <> struct __nv_tex2dgather_ret<short4> { typedef short4 type; };
+template <> struct __nv_tex2dgather_ret<unsigned short> { typedef ushort4 type; };
+template <> struct __nv_tex2dgather_ret<ushort1> { typedef ushort4 type; };
+template <> struct __nv_tex2dgather_ret<ushort2> { typedef ushort4 type; };
+template <> struct __nv_tex2dgather_ret<ushort3> { typedef ushort4 type; };
+template <> struct __nv_tex2dgather_ret<ushort4> { typedef ushort4 type; };
+
+template <> struct __nv_tex2dgather_ret<int> { typedef int4 type; };
+template <> struct __nv_tex2dgather_ret<int1> { typedef int4 type; };
+template <> struct __nv_tex2dgather_ret<int2> { typedef int4 type; };
+template <> struct __nv_tex2dgather_ret<int3> { typedef int4 type; };
+template <> struct __nv_tex2dgather_ret<int4> { typedef int4 type; };
+template <> struct __nv_tex2dgather_ret<unsigned int> { typedef uint4 type; };
+template <> struct __nv_tex2dgather_ret<uint1> { typedef uint4 type; };
+template <> struct __nv_tex2dgather_ret<uint2> { typedef uint4 type; };
+template <> struct __nv_tex2dgather_ret<uint3> { typedef uint4 type; };
+template <> struct __nv_tex2dgather_ret<uint4> { typedef uint4 type; };
+
+template <> struct __nv_tex2dgather_ret<float> { typedef float4 type; };
+template <> struct __nv_tex2dgather_ret<float1> { typedef float4 type; };
+template <> struct __nv_tex2dgather_ret<float2> { typedef float4 type; };
+template <> struct __nv_tex2dgather_ret<float3> { typedef float4 type; };
+template <> struct __nv_tex2dgather_ret<float4> { typedef float4 type; };
+
+
+template<typename T> struct __nv_tex2dgather_rmnf_ret { };
+template<> struct __nv_tex2dgather_rmnf_ret<char> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<signed char> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<unsigned char> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<char1> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<uchar1> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<char2> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<uchar2> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<char3> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<uchar3> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<char4> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<uchar4> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<signed short> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<unsigned short> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<short1> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<ushort1> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<short2> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<ushort2> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<short3> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<ushort3> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<short4> { typedef float4 type; };
+template<> struct __nv_tex2dgather_rmnf_ret<ushort4> { typedef float4 type; };
+
+#undef __DEPRECATED__
+
+#endif /* __cplusplus && __CUDACC__ */
+
+#endif /* !__TEXTURE_FETCH_FUNCTIONS_H__ */

omnilmm/lib/python3.10/site-packages/nvidia/cuda_runtime/include/vector_functions.h

@@ -0,0 +1,175 @@
+/*
+ * Copyright 1993-2014 NVIDIA Corporation.  All rights reserved.
+ *
+ * NOTICE TO LICENSEE:
+ *
+ * This source code and/or documentation ("Licensed Deliverables") are
+ * subject to NVIDIA intellectual property rights under U.S. and
+ * international Copyright laws.
+ *
+ * These Licensed Deliverables contained herein is PROPRIETARY and
+ * CONFIDENTIAL to NVIDIA and is being provided under the terms and
+ * conditions of a form of NVIDIA software license agreement by and
+ * between NVIDIA and Licensee ("License Agreement") or electronically
+ * accepted by Licensee.  Notwithstanding any terms or conditions to
+ * the contrary in the License Agreement, reproduction or disclosure
+ * of the Licensed Deliverables to any third party without the express
+ * written consent of NVIDIA is prohibited.
+ *
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
+ * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
+ * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
+ * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
+ * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
+ * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
+ * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
+ * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
+ * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
+ * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
+ * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
+ * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
+ * OF THESE LICENSED DELIVERABLES.
+ *
+ * U.S. Government End Users.  These Licensed Deliverables are a
+ * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
+ * 1995), consisting of "commercial computer software" and "commercial
+ * computer software documentation" as such terms are used in 48
+ * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
+ * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
+ * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
+ * U.S. Government End Users acquire the Licensed Deliverables with
+ * only those rights set forth herein.
+ *
+ * Any use of the Licensed Deliverables in individual and commercial
+ * software must include, in the user documentation and internal
+ * comments to the code, the above Disclaimer and U.S. Government End
+ * Users Notice.
+ */
+
+#if !defined(__VECTOR_FUNCTIONS_H__)
+#define __VECTOR_FUNCTIONS_H__
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+#include "cuda_runtime_api.h"
+
+#if defined(__CUDACC_RTC__)
+#define __VECTOR_FUNCTIONS_DECL__ __host__ __device__
+#else /* !__CUDACC_RTC__ */
+#define __VECTOR_FUNCTIONS_DECL__ static __inline__ __host__ __device__
+#endif /* __CUDACC_RTC__ */
+
+/*******************************************************************************
+*                                                                              *
+*                                                                              *
+*                                                                              *
+*******************************************************************************/
+
+__VECTOR_FUNCTIONS_DECL__ char1 make_char1(signed char x);
+
+__VECTOR_FUNCTIONS_DECL__ uchar1 make_uchar1(unsigned char x);
+
+__VECTOR_FUNCTIONS_DECL__ char2 make_char2(signed char x, signed char y);
+
+__VECTOR_FUNCTIONS_DECL__ uchar2 make_uchar2(unsigned char x, unsigned char y);
+
+__VECTOR_FUNCTIONS_DECL__ char3 make_char3(signed char x, signed char y, signed char z);
+
+__VECTOR_FUNCTIONS_DECL__ uchar3 make_uchar3(unsigned char x, unsigned char y, unsigned char z);
+
+__VECTOR_FUNCTIONS_DECL__ char4 make_char4(signed char x, signed char y, signed char z, signed char w);
+
+__VECTOR_FUNCTIONS_DECL__ uchar4 make_uchar4(unsigned char x, unsigned char y, unsigned char z, unsigned char w);
+
+__VECTOR_FUNCTIONS_DECL__ short1 make_short1(short x);
+
+__VECTOR_FUNCTIONS_DECL__ ushort1 make_ushort1(unsigned short x);
+
+__VECTOR_FUNCTIONS_DECL__ short2 make_short2(short x, short y);
+
+__VECTOR_FUNCTIONS_DECL__ ushort2 make_ushort2(unsigned short x, unsigned short y);
+
+__VECTOR_FUNCTIONS_DECL__ short3 make_short3(short x,short y, short z);
+
+__VECTOR_FUNCTIONS_DECL__ ushort3 make_ushort3(unsigned short x, unsigned short y, unsigned short z);
+
+__VECTOR_FUNCTIONS_DECL__ short4 make_short4(short x, short y, short z, short w);
+
+__VECTOR_FUNCTIONS_DECL__ ushort4 make_ushort4(unsigned short x, unsigned short y, unsigned short z, unsigned short w);
+
+__VECTOR_FUNCTIONS_DECL__ int1 make_int1(int x);
+
+__VECTOR_FUNCTIONS_DECL__ uint1 make_uint1(unsigned int x);
+
+__VECTOR_FUNCTIONS_DECL__ int2 make_int2(int x, int y);
+
+__VECTOR_FUNCTIONS_DECL__ uint2 make_uint2(unsigned int x, unsigned int y);
+
+__VECTOR_FUNCTIONS_DECL__ int3 make_int3(int x, int y, int z);
+
+__VECTOR_FUNCTIONS_DECL__ uint3 make_uint3(unsigned int x, unsigned int y, unsigned int z);
+
+__VECTOR_FUNCTIONS_DECL__ int4 make_int4(int x, int y, int z, int w);
+
+__VECTOR_FUNCTIONS_DECL__ uint4 make_uint4(unsigned int x, unsigned int y, unsigned int z, unsigned int w);
+
+__VECTOR_FUNCTIONS_DECL__ long1 make_long1(long int x);
+
+__VECTOR_FUNCTIONS_DECL__ ulong1 make_ulong1(unsigned long int x);
+
+__VECTOR_FUNCTIONS_DECL__ long2 make_long2(long int x, long int y);
+
+__VECTOR_FUNCTIONS_DECL__ ulong2 make_ulong2(unsigned long int x, unsigned long int y);
+
+__VECTOR_FUNCTIONS_DECL__ long3 make_long3(long int x, long int y, long int z);
+
+__VECTOR_FUNCTIONS_DECL__ ulong3 make_ulong3(unsigned long int x, unsigned long int y, unsigned long int z);
+
+__VECTOR_FUNCTIONS_DECL__ long4 make_long4(long int x, long int y, long int z, long int w);
+
+__VECTOR_FUNCTIONS_DECL__ ulong4 make_ulong4(unsigned long int x, unsigned long int y, unsigned long int z, unsigned long int w);
+
+__VECTOR_FUNCTIONS_DECL__ float1 make_float1(float x);
+
+__VECTOR_FUNCTIONS_DECL__ float2 make_float2(float x, float y);
+
+__VECTOR_FUNCTIONS_DECL__ float3 make_float3(float x, float y, float z);
+
+__VECTOR_FUNCTIONS_DECL__ float4 make_float4(float x, float y, float z, float w);
+
+__VECTOR_FUNCTIONS_DECL__ longlong1 make_longlong1(long long int x);
+
+__VECTOR_FUNCTIONS_DECL__ ulonglong1 make_ulonglong1(unsigned long long int x);
+
+__VECTOR_FUNCTIONS_DECL__ longlong2 make_longlong2(long long int x, long long int y);
+
+__VECTOR_FUNCTIONS_DECL__ ulonglong2 make_ulonglong2(unsigned long long int x, unsigned long long int y);
+
+__VECTOR_FUNCTIONS_DECL__ longlong3 make_longlong3(long long int x, long long int y, long long int z);
+
+__VECTOR_FUNCTIONS_DECL__ ulonglong3 make_ulonglong3(unsigned long long int x, unsigned long long int y, unsigned long long int z);
+
+__VECTOR_FUNCTIONS_DECL__ longlong4 make_longlong4(long long int x, long long int y, long long int z, long long int w);
+
+__VECTOR_FUNCTIONS_DECL__ ulonglong4 make_ulonglong4(unsigned long long int x, unsigned long long int y, unsigned long long int z, unsigned long long int w);
+
+__VECTOR_FUNCTIONS_DECL__ double1 make_double1(double x);
+
+__VECTOR_FUNCTIONS_DECL__ double2 make_double2(double x, double y);
+
+__VECTOR_FUNCTIONS_DECL__ double3 make_double3(double x, double y, double z);
+
+__VECTOR_FUNCTIONS_DECL__ double4 make_double4(double x, double y, double z, double w);
+
+#undef __VECTOR_FUNCTIONS_DECL__
+
+#if !defined(__CUDACC_RTC__)
+#include "vector_functions.hpp"
+#endif /* !__CUDACC_RTC__ */
+
+#endif /* !__VECTOR_FUNCTIONS_H__ */

omnilmm/lib/python3.10/site-packages/nvidia/cudnn/lib/libcudnn_ops_train.so.8

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c89d9c871d0f1d1b3d1037234a66ebb09f990e3d5324c5025d45835d7d82d462
+size 70922856

wemm/lib/python3.10/site-packages/sympy/physics/biomechanics/__init__.py

@@ -0,0 +1,53 @@
+"""Biomechanics extension for SymPy.
+
+Includes biomechanics-related constructs which allows users to extend multibody
+models created using `sympy.physics.mechanics` into biomechanical or
+musculoskeletal models involding musculotendons and activation dynamics.
+
+"""
+
+from .activation import (
+   ActivationBase,
+   FirstOrderActivationDeGroote2016,
+   ZerothOrderActivation,
+)
+from .curve import (
+   CharacteristicCurveCollection,
+   CharacteristicCurveFunction,
+   FiberForceLengthActiveDeGroote2016,
+   FiberForceLengthPassiveDeGroote2016,
+   FiberForceLengthPassiveInverseDeGroote2016,
+   FiberForceVelocityDeGroote2016,
+   FiberForceVelocityInverseDeGroote2016,
+   TendonForceLengthDeGroote2016,
+   TendonForceLengthInverseDeGroote2016,
+)
+from .musculotendon import (
+   MusculotendonBase,
+   MusculotendonDeGroote2016,
+   MusculotendonFormulation,
+)
+
+
+__all__ = [
+   # Musculotendon characteristic curve functions
+   'CharacteristicCurveCollection',
+   'CharacteristicCurveFunction',
+   'FiberForceLengthActiveDeGroote2016',
+   'FiberForceLengthPassiveDeGroote2016',
+   'FiberForceLengthPassiveInverseDeGroote2016',
+   'FiberForceVelocityDeGroote2016',
+   'FiberForceVelocityInverseDeGroote2016',
+   'TendonForceLengthDeGroote2016',
+   'TendonForceLengthInverseDeGroote2016',
+
+   # Activation dynamics classes
+   'ActivationBase',
+   'FirstOrderActivationDeGroote2016',
+   'ZerothOrderActivation',
+
+   # Musculotendon classes
+   'MusculotendonBase',
+   'MusculotendonDeGroote2016',
+   'MusculotendonFormulation',
+]