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/* Copyright (c) Chris Choy (chrischoy@ai.stanford.edu).
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
* IN THE SOFTWARE.
*
* Please cite "4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural
* Networks", CVPR'19 (https://arxiv.org/abs/1904.08755) if you use any part
* of the code.
*/
#ifndef GPU_H_
#define GPU_H_
#include <cublas_v2.h>
#include <cuda.h>
#include <cuda_runtime.h>
#include <curand.h>
#include <cusparse.h>
#include <driver_types.h> // cuda driver types
#include <exception>
#include <iostream>
#include <vector>
#include "utils.hpp"
// AtomicAddition for double with cuda arch <= 600
#if !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 600
#else
__device__ double atomicAdd(double *address, double val) {
unsigned long long int *address_as_ull = (unsigned long long int *)address;
unsigned long long int old = *address_as_ull, assumed;
do {
assumed = old;
old = atomicCAS(address_as_ull, assumed,
__double_as_longlong(val + __longlong_as_double(assumed)));
} while (assumed != old);
return __longlong_as_double(old);
}
#endif
namespace minkowski {
//
// CUDA macros
//
// CUDA: various checks for different function calls.
#define CUDA_CHECK(condition) \
/* Code block avoids redefinition of cudaError_t error */ \
{ \
cudaError_t error = condition; \
if (error != cudaSuccess) { \
throw std::runtime_error(Formatter() \
<< " " << cudaGetErrorString(error) << " at " \
<< __FILE__ << ":" << __LINE__); \
} \
}
// CUDA: various checks for different function calls.
#ifdef DEBUG
#define CUDA_CHECK_DEBUG(condition) \
/* Code block avoids redefinition of cudaError_t error */ \
{ \
cudaError_t error = condition; \
if (error != cudaSuccess) { \
throw std::runtime_error(Formatter() \
<< " " << cudaGetErrorString(error) << " at " \
<< __FILE__ << ":" << __LINE__); \
} \
}
#else
#define CUDA_CHECK_DEBUG(...) (void)0
#endif
#define CUDA_CHECK_ARGS(condition, ...) \
/* Code block avoids redefinition of cudaError_t error */ \
{ \
cudaError_t error = condition; \
if (error != cudaSuccess) { \
Formatter formatter; \
formatter << " " << cudaGetErrorString(error) << " at "; \
formatter << __FILE__ << ":" << __LINE__; \
formatter.append(__VA_ARGS__); \
throw std::runtime_error(formatter.str()); \
} \
}
#define CUBLAS_CHECK(condition) \
{ \
cublasStatus_t status = condition; \
if (status != CUBLAS_STATUS_SUCCESS) { \
throw std::runtime_error(Formatter() \
<< minkowski::cublasGetErrorString(status) \
<< " at " << __FILE__ << ":" << __LINE__); \
} \
}
#define CUSPARSE_CHECK(call) \
{ \
cusparseStatus_t err; \
if ((err = (call)) != CUSPARSE_STATUS_SUCCESS) { \
throw std::runtime_error(Formatter() \
<< minkowski::cusparseGetErrorString(err) \
<< " at " << __FILE__ << ":" << __LINE__); \
} \
}
#define CURAND_CHECK(condition) \
{ \
curandStatus_t status = condition; \
if (status != CURAND_STATUS_SUCCESS) { \
throw std::runtime_error(Formatter() \
<< curandGetErrorString(status) << " at " \
<< __FILE__ << ":" << __LINE__); \
} \
}
// CUDA: grid stride looping
#define CUDA_KERNEL_LOOP(i, n) \
for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < (n); \
i += blockDim.x * gridDim.x)
// CUDA: check for error after kernel execution and exit loudly if there is one.
#define CUDA_POST_KERNEL_CHECK \
{ \
cudaError_t status = cudaPeekAtLastError(); \
if (status != cudaSuccess) { \
throw std::runtime_error(Formatter() \
<< " " << cudaGetErrorString(status) << " at " \
<< __FILE__ << ":" << __LINE__); \
} \
}
#define THRUST_CHECK(condition) \
try { \
condition; \
} catch (thrust::system_error e) { \
throw std::runtime_error(Formatter() \
<< "Thrust error: " << e.what() << " at " \
<< __FILE__ << ":" << __LINE__); \
}
#define THRUST_CATCH \
catch (thrust::system_error e) { \
throw std::runtime_error(Formatter() \
<< "Thrust error: " << e.what() << " at " \
<< __FILE__ << ":" << __LINE__); \
}
// CUDA: library error reporting.
const char *cublasGetErrorString(cublasStatus_t error);
// CUSparse error reporting.
const char *cusparseGetErrorString(cusparseStatus_t error);
cusparseHandle_t getCurrentCUDASparseHandle();
constexpr uint32_t CUDA_NUM_THREADS = 128;
constexpr uint32_t SHARED_BLOCK_SIZE = 32;
constexpr uint32_t MAX_GRID = 65535;
inline int GET_BLOCKS(const uint32_t N, const uint32_t THREADS) {
return std::max((N + THREADS - 1) / THREADS, uint32_t(1));
}
std::pair<size_t, size_t> get_memory_info();
} // end namespace minkowski
#endif // GPU_H_