sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
e5f3271a722164fce9cd67967eb6d11cebece9b973839a7118169fbfd05b39eb | CUDA | 5,716 | 188 | // Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
// This file is modified from https://github.com/pytorch/pytorch/blob/master/modules/detectron/sigmoid_focal_loss_op.cu
// Cheng-Yang Fu
// cyfu@cs.unc.edu
#include <ATen/ATen.h>
#include <ATen/cuda/CUDAContext.h>
#include <THC/THC.h>
#include <... |
6147b55210d1384fd3d5c8e81293e81bceaf239fd93be4b595f31bb5bb58b11f | CUDA | 5,731 | 189 | // Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
// This file is modified from https://github.com/pytorch/pytorch/blob/master/modules/detectron/sigmoid_focal_loss_op.cu
// Cheng-Yang Fu
// cyfu@cs.unc.edu
#include <ATen/ATen.h>
#include <ATen/cuda/CUDAContext.h>
#include <THC/THC.h>
#include <... |
f9dbf2837cf51210ed36b78a5c233179a6bc5660cc688f2fba5c04817422ece6 | CUDA | 6,195 | 195 | // Copyright 2022 Huawei Technologies Co., Ltd
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or ... |
cd1c4270951d245f7ef6d59f02fea566316e9fe7ae0bf6316fdc84feb8d6dcc1 | CUDA | 6,639 | 210 | // **************************************************************************
// nm_cut.cu
// -------------------
//
// Device code for acceleration of the nm/cut pair style
//
// __________________________________________________________________________
// ... |
e36435006b9126866f5daf89f27868cba9d080695189752db4e1e95839a529fa | CUDA | 6,786 | 220 | // **************************************************************************
// coul_cut_soft.cu
// -------------------
//
// Device code for acceleration of the coul/cut/soft pair style
//
// _________________________________________________________________... |
3106db8ca3765017cc20b48db20d7cb6f8e09d7e3077d56074ea5d3a0490f6c8 | CUDA | 6,854 | 144 | #include "carafe_cuda_kernel.cuh"
#include "parrots_cuda_helper.hpp"
void CARAFEForwardCUDAKernelLauncher(
const DArrayLite features, const DArrayLite masks, DArrayLite rfeatures,
DArrayLite routput, DArrayLite rmasks, DArrayLite output,
const int kernel_size, const int group_size, const int scale_factor,
... |
17459b6682ed3c6422019a4fb0a487f2759197e92a574aa3deffe4603ecbb38f | CUDA | 6,868 | 213 | // **************************************************************************
// lj_cut_soft.cu
// -------------------
//
// Device code for acceleration of the lj/cut/soft pair style
//
// _____________________________________________________________________... |
0f384dbbbb946b211fb3a61caeb6679e95aa92701f400422379b895a9f4533c1 | CUDA | 6,956 | 215 | // **************************************************************************
// lj_class2_soft.cu
// -------------------
//
// Device code for acceleration of the lj/class2/soft pair style
//
// _______________________________________________________________... |
520589b5fdf6b835e908a6c5827a88a91ccad6fe484dce87aeee021e08438187 | CUDA | 7,134 | 222 | // **************************************************************************
// morse_soft.cu
// -------------------
//
// Device code for acceleration of the morse/soft pair style
//
// _______________________________________________________________________... |
382b234c39712494753eceaa3d72874edad9aa7a743c27d192b1cdf630bc7ae0 | CUDA | 7,436 | 237 | // **************************************************************************
// coul_wolf.cu
// -------------------
//
// Device code for acceleration of the coul/wolf pair style
//
// _________________________________________________________________________... |
2e91b62ca5b6ce5058a7ee20a998ce58af012a1f0be6daa4dae457fbf480c18d | CUDA | 7,509 | 233 | // **************************************************************************
// coul_diel.cu
// -------------------
//
// Device code for acceleration of the coul/diel pair style
//
// _________________________________________________________________________... |
103b9563afcdded0cad43c52219c4a399d7f38b9be5bdf4ebbc99c2c63d62602 | CUDA | 7,566 | 228 | // **************************************************************************
// coul_slater_cut.cu
// -------------------
//
// Device code for acceleration of the coul/slater/cut pair style
//
// _____________________________________________________________... |
2ab1eee7d3f20e7c4091330ca7088d3503031238fdeab5a34bff7e8c5e0eb521 | CUDA | 7,732 | 167 | #ifdef __cplusplus
extern "C" {
#endif
#include <stdio.h>
#include <math.h>
#include <float.h>
#include "roi_align_kernel.h"
#define CUDA_1D_KERNEL_LOOP(i, n) \
for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < n; \
i += blockDim.x * gridDim.x)
__global__ void RO... |
eedb9d29f54045955ebe324463eb406c99f126e24e6f47a13720173d8ae3034d | CUDA | 7,842 | 232 | // **************************************************************************
// lj_cut_soft_gapsys.cu
// -------------------
//
// Device code for acceleration of the lj/cut/soft/gapsys pair style
//
// _______________________________________________________... |
2be462353a4c4ab1aafabb70756b50b24e50447ed8eeb4942dbf05524878c365 | CUDA | 7,843 | 202 | // Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
#include <ATen/ATen.h>
#include <ATen/cuda/CUDAContext.h>
#include <THC/THC.h>
#include <THC/THCAtomics.cuh>
#include <THC/THCDeviceUtils.cuh>
// TODO make it in a common file
#define CUDA_1D_KERNEL_LOOP(i, n) \
for... |
7f6459fbf8961d46f151ec09160291a566a06947e49d8302677e013fc9040a4e | CUDA | 7,855 | 202 | // Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
#include <ATen/ATen.h>
#include <ATen/cuda/CUDAContext.h>
#include <THC/THC.h>
#include <THC/THCAtomics.cuh>
#include <THC/THCDeviceUtils.cuh>
// TODO make it in a common file
#define CUDA_1D_KERNEL_LOOP(i, n) \
for... |
791259dc23ff3949a3a9d8ed0be8cf21a707659ad4498d40128d0410d4f21aaa | CUDA | 7,913 | 246 | // **************************************************************************
// coul_wolf_cs.cu
// -------------------
//
// Device code for acceleration of the coul/wolf/cs pair style
//
// ___________________________________________________________________... |
659c1b6698155819c19f16528519b6eddddedf5ed426037f35e71865a1a24b2a | CUDA | 8,095 | 241 | // **************************************************************************
// coul_long_soft.cu
// -------------------
//
// Device code for acceleration of the coul/long/soft pair style
//
// _______________________________________________________________... |
2627077e050f3ba5bdebf7adc93bc09a968e2da89a46e7d0d57f326479564b33 | CUDA | 8,104 | 237 | // **************************************************************************
// lj_class2_soft_gapsys.cu
// -------------------
//
// Device code for acceleration of the lj/class2/soft/gapsys pair style
//
// _________________________________________________... |
883692188c898029e11f38a6a8f905a4dbb7f50d9666df0d40c036ad85adb85d | CUDA | 8,117 | 238 | // **************************************************************************
// nm_cut_split.cu
// -------------------
//
// Device code for acceleration of the nm/cut/split pair style
//
// ___________________________________________________________________... |
f9a0e5a4095f2d2e7ffe4f95f744d733480983986258f318c39f585f276a0166 | CUDA | 8,122 | 239 | // **************************************************************************
// coul_cut_soft_gapsys.cu
// -------------------
//
// Device code for acceleration of the coul/cut/soft/gapsys pair style
//
// ___________________________________________________... |
593986abcd9d2f57075a266b81d470b8b0dc34d22127b4cdde76c0c52ceaba76 | CUDA | 8,495 | 263 | // **************************************************************************
// lj_class2_coul_cut.cu
// -------------------
//
// Device code for acceleration of the lj/class2/coul/cut pair style
//
// _______________________________________________________... |
8770f3e133f335abeade96d37bfa08889576d7c173b69d397348343085e84938 | CUDA | 8,670 | 295 | // Copyright 2022 Huawei Technologies Co., Ltd
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or ... |
58b68650a5b54174cf0c4cf0be84e6da86d83857a725feecb845b637998b716b | CUDA | 8,768 | 263 | // **************************************************************************
// nm_cut_coul_cut.cu
// -------------------
//
// Device code for acceleration of the nm/cut/coul/cut pair style
//
// _____________________________________________________________... |
7c3e876761a745702bedb80794076bc15ba123dcd0f213e63cd900cce88c8c3d | CUDA | 8,908 | 276 | // **************************************************************************
// lj_coul_soft.cu
// -------------------
// Trung Nguyen (U Chicago)
//
// Device code for acceleration of the lj/coul/cut/soft pair style
//
// ___________... |
826602addb5bd5bc454ff6e40ae0827d677b6e703c14d35766cdb24748c13dff | CUDA | 8,928 | 179 | #include "carafe_cuda_kernel.cuh"
#include "pytorch_cuda_helper.hpp"
void CARAFEForwardCUDAKernelLauncher(const Tensor features, const Tensor masks,
Tensor rfeatures, Tensor routput,
Tensor rmasks, Tensor output,
... |
b1dd3b18c7732cbbe8f0a23f1e62ea6cc657366d45bb884d16b8e744239d3e26 | CUDA | 8,953 | 272 | // Copyright (c) 2019, NVIDIA Corporation. All rights reserved.
//
// This work is made available under the Nvidia Source Code License-NC.
// To view a copy of this license, visit
// https://nvlabs.github.io/stylegan2/license.html
#include <torch/types.h>
#include <ATen/ATen.h>
#include <ATen/AccumulateType.h>
#inclu... |
bccda85f1ed59a965d982e212ad78b00d630aad5438216a242187a3aa842bf3e | CUDA | 9,224 | 272 | // Copyright (c) 2019, NVIDIA Corporation. All rights reserved.
//
// This work is made available under the Nvidia Source Code License-NC.
// To view a copy of this license, visit
// https://nvlabs.github.io/stylegan2/license.html
#include <torch/types.h>
#include <ATen/ATen.h>
#include <ATen/AccumulateType.... |
1091535eea9c5030f12d5735b07882721e3bc7cee4f1d60d43bd694329cd7cdf | CUDA | 9,333 | 269 | // **************************************************************************
// lj_class2_coul_cut_soft.cu
// -------------------
//
// Device code for acceleration of the lj/class2/coul/cut/soft pair style
//
// _____________________________________________... |
46594a6d6a8dc55605405d8f814eaf482fbdafdb93d67b166dd5e0bf698fa984 | CUDA | 9,573 | 239 | // #ifdef __cplusplus
// extern "C" {
// #endif
#include <stdio.h>
#include <vector>
#include <math.h>
#include <float.h>
#include "roi_pooling_kernel.h"
#define DIVUP(m, n) ((m) / (m) + ((m) % (n) > 0))
#define CUDA_1D_KERNEL_LOOP(i, n) \
for (int i = blockIdx.x * blockDim.x + threadId... |
70b1588da9e9f545d0b56c3484aaf6b9e81ea6edd67703ce8fb067a4b6d39ecb | CUDA | 9,597 | 279 | // **************************************************************************
// nm_cut_coul_long.cu
// -------------------
//
// Device code for acceleration of the nm/cut/coul/long pair style
//
// ___________________________________________________________... |
e68232853095c63c543d0a67025eeee7b519fd02b14084658c66c7445dbe3801 | CUDA | 9,598 | 290 | // **************************************************************************
// lj_cut_coul_wolf.cu
// -------------------
//
// Device code for acceleration of the lj/cut/coul/wolf pair style
//
// ___________________________________________________________... |
e603806a4d35bf5a2266db966c7b4a5cabf59ed6b789098de416c0c863df7b6d | CUDA | 10,191 | 296 | // **************************************************************************
// lj_coul_long_soft.cu
// -------------------
// Trung Nguyen (U Chicago)
//
// Device code for acceleration of the lj/cut/coul/long/soft pair style
//
// ____... |
be4464b854530ac5561bece49a756626def961f4e9d2f672e1b1a1796674ea14 | CUDA | 10,266 | 289 | #include <vector>
#include <torch//serialize/tensor.h>
#include <ATen/ATen.h>
#include <ATen/cuda/CUDAContext.h>
#include "common.h"
#include "device_tensor.h"
namespace {
template <typename DType, typename Acctype, typename DeviceTensor3>
struct GradOp {
__device__ GradOp(Acctype m, const DeviceTensor3 i, const D... |
0b4995752704771dabd3604d04ab4e47d71164ba2db13862c1975f5b30d4ba92 | CUDA | 10,474 | 296 | // **************************************************************************
// charmmfsw_fsh.cu
// -------------------
//
// Device code for acceleration of the lj/charmmfsw/coul/charmmfsh pair style
//
// ___________________________________________________... |
58694478756f1493f46772ea0c90de1cc718c0f4d12fb134f577b2244d5e59b5 | CUDA | 10,524 | 293 | // **************************************************************************
// lj_class2_coul_long_soft.cu
// -------------------
//
// Device code for acceleration of the lj/class2/coul/long/soft pair style
//
// ___________________________________________... |
5de9e43fd46de95a8904fe01ff129bc5c811927d15de684bd52e17bb5f523bda | CUDA | 10,567 | 306 | // **************************************************************************
// born_coul_dsf.cu
// -------------------
//
// Device code for acceleration of the born/coul/dsf pair style
//
// _________________________________________________________________... |
baac721ca7929df55a626352d5ba006de199650a414bd96941219fb565d1a37a | CUDA | 10,775 | 302 | // **************************************************************************
// charmmfsw_long.cu
// -------------------
//
// Device code for acceleration of the lj/charmmfsw/coul/long pair style
//
// _______________________________________________________... |
1df1d71cdf0c9f751e5f2dadeff4839b3b59bcf4286db3e9c41af93f8d4253c1 | CUDA | 10,860 | 322 | // **************************************************************************
// lj_coul_long_cs.cu
// -------------------
//
// Device code for acceleration of the lj/cut/coul/long/cs pair style
//
// _________________________________________________________... |
1e138f44e6085c42b5dd22d7403c467b7ec2ea98de825bb0281b80ee32f53bbc | CUDA | 11,007 | 305 | // **************************************************************************
// lj_coul_soft_gapsys.cu
// -------------------
//
// Device code for acceleration of the lj/cut/coul/cut/soft/gapsys pair style
//
// _____________________________________________... |
a3db978f329df1a6c527ae62e378a211cf47a8fb725a3b3c90a6865c5f584867 | CUDA | 11,007 | 335 | // **************************************************************************
// lj_coul_msm.cu
// -------------------
// Trung Dac Nguyen (ORNL)
//
// Device code for acceleration of the lj/cut/coul/msm pair style
//
// ______________... |
d942742069325d4745e023cdfe7966a6f62403c598bd510607a10bac32f57c01 | CUDA | 11,044 | 315 | // **************************************************************************
// born_coul_dsf_cs.cu
// -------------------
//
// Device code for acceleration of the born/coul/dsf/cs pair style
//
// ___________________________________________________________... |
5e6967fd2a22221c09e606b4d9a3e180ebdfde5602b9e6ead19cff1ac071359f | CUDA | 11,156 | 328 | // **************************************************************************
// lj_class2_coul_long_cs.cu
// -------------------
//
// Device code for acceleration of the lj/class2/coul/long/cs pair style
//
// _______________________________________________... |
db4bfb92c54a8e137ba6b8b9c31df03ec98a34563d26e651799500546bc82516 | CUDA | 11,160 | 312 | // **************************************************************************
// charmm_implicit.cu
// -------------------
//
// Device code for acceleration of the lj/charmm/coul/charmm/implicit pair style
//
// ______________________________________________... |
b7f2fbda43808587ef5559f59ac61fcf823459865c9e4fd3e705553fe379bd19 | CUDA | 11,180 | 298 | // Copyright 2022 Huawei Technologies Co., Ltd
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or ... |
dbbffdcae172954bfbde066b4ac062bf6acc14b6ee0e2eb596e5a6034e41262e | CUDA | 11,464 | 333 | // **************************************************************************
// buck_coul_long_cs.cu
// -------------------
//
// Device code for acceleration of the buck/coul/long/cs pair style
//
// _________________________________________________________... |
5ae34b1cea8f3520882b943c5f7832a5b4d944539e80e8c58b5771e5b7f480dc | CUDA | 11,558 | 310 | // **************************************************************************
// lj_class2_coul_cut_soft_gapsys.cu
// -------------------
//
// Device code for acceleration of the lj/class2/coul/cut/soft/gapsys pair style
//
// _______________________________... |
2b863328085c89d738e3d4113e493155e34f1ed2a9d403b229e98afb5d9dca2d | CUDA | 11,671 | 322 | // **************************************************************************
// charmm_coul_long_soft.cu
// -------------------
//
// Device code for acceleration of the lj/charmm/coul/long/soft pair style
//
// ______________________________________________... |
5d61888fcc2ae5270566791157b0b0b4fe8f931783f15cc77a7b2bc15eaec9e1 | CUDA | 11,711 | 369 | // Copyright (c) 2019, NVIDIA Corporation. All rights reserved.
//
// This work is made available under the Nvidia Source Code License-NC.
// To view a copy of this license, visit
// https://nvlabs.github.io/stylegan2/license.html
#include <torch/types.h>
#include <ATen/ATen.h>
#include <ATen/AccumulateType.h>
#inclu... |
a6ca93d6eac459e51095b2a427b8bb7ebb9437510daa649f3eb78ce76b2e10c4 | CUDA | 11,816 | 319 | // **************************************************************************
// lj_gromacs_coul_gromacs.cu
// -------------------
//
// Device code for acceleration of the lj/gromacs/coul/gromacs pair style
//
// _____________________________________________... |
4c43deaf12375ff43b7ecce3eff5b1bc00a7742857f3f75b497693644e0964e5 | CUDA | 12,070 | 369 | // Copyright (c) 2019, NVIDIA Corporation. All rights reserved.
//
// This work is made available under the Nvidia Source Code License-NC.
// To view a copy of this license, visit
// https://nvlabs.github.io/stylegan2/license.html
#include <torch/types.h>
#include <ATen/ATen.h>
#include <ATen/AccumulateType.... |
7d01980f4ffe79ad18e56e218de03f8de925222add6b288b24e6f66954638157 | CUDA | 12,315 | 346 | // Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
#include <ATen/ATen.h>
#include <ATen/cuda/CUDAContext.h>
#include <THC/THC.h>
#include <THC/THCAtomics.cuh>
#include <THC/THCDeviceUtils.cuh>
// TODO make it in a common file
#define CUDA_1D_KERNEL_LOOP(i, n) \
for ... |
e8a6d2148d5719533a73ef793f69ddf1e36af54c1811cf4742227fcf32ceff56 | CUDA | 12,327 | 346 | // Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
#include <ATen/ATen.h>
#include <ATen/cuda/CUDAContext.h>
#include <THC/THC.h>
#include <THC/THCAtomics.cuh>
#include <THC/THCDeviceUtils.cuh>
// TODO make it in a common file
#define CUDA_1D_KERNEL_LOOP(i, n) \
for ... |
cf585261038616d462f0bbbb298f2c04decadd2e5c44a49cb63cb24f8d9ec178 | CUDA | 12,422 | 350 | /* @file f5c_gpuonly.cu
**
** implementation of the f5c GPU-only framework (opposed to the CPU-GPU hybrid approach in f5c.cu)
** not compiled by default
** @author: Hasindu Gamaarachchi (hasindu@unsw.edu.au)
** @@
******************************************************************************/
#include <errno.h>
#inclu... |
54915c5ededebb9eaac1052f441b2a8e95ebfb83922f7d3e0b2e62286260fa96 | CUDA | 13,126 | 286 | #include "modulated_deform_conv_cuda_kernel.cuh"
#include "pytorch_cuda_helper.hpp"
void modulated_deformable_im2col_cuda(
const Tensor data_im, const Tensor data_offset, const Tensor data_mask,
const int batch_size, const int channels, const int height_im,
const int width_im, const int height_col, const i... |
393d2163f9db8e6f49d773d93eb0f2a2eade4dd813d334f2c4bf2979af6bfe36 | CUDA | 13,251 | 292 | #include "modulated_deform_conv_cuda_kernel.cuh"
#include "parrots_cuda_helper.hpp"
void modulated_deformable_im2col_cuda(
const DArrayLite data_im, const DArrayLite data_offset,
const DArrayLite data_mask, const int batch_size, const int channels,
const int height_im, const int width_im, const int height_... |
667901a22254ce2d1128f516cec6561bdd7c685469dc5dea48bf5fcd77bf6004 | CUDA | 13,713 | 441 | // **************************************************************************
// gayberne_lj.cu
// -------------------
// W. Michael Brown (ORNL)
//
// Device code for Gay-Berne - Lennard-Jones potential acceleration
//
// ___________... |
8287c5dd9eb6188e136826bbbdeea8f508b64a2c9cfb17dec65a0b98100a545c | CUDA | 14,743 | 335 | #include <vector>
#include "cuda/dcn_v2_im2col_cuda.h"
#include <ATen/ATen.h>
#include <ATen/cuda/CUDAContext.h>
#include <THC/THC.h>
#include <THC/THCAtomics.cuh>
#include <THC/THCDeviceUtils.cuh>
extern THCState *state;
// author: Charles Shang
// https://github.com/torch/cunn/blob/master/lib/THCUNN/generic/Spati... |
0dfb206d839a4164b16b3cfd68c5c79d94e7712c83d90fd6cb14d9c4ead4a24b | CUDA | 15,597 | 431 | // **************************************************************************
// sph_lj.cu
// -------------------
// Trung Dac Nguyen (U Chicago)
//
// Device code for acceleration of the sph/lj pair style
//
// _____________________... |
39e60d22ce155b5ff4bbfaf6a42995689b3f72b9bdef258f4f4cfc790de3f417 | CUDA | 15,946 | 451 | // Copyright 2022 Huawei Technologies Co., Ltd
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or ... |
88fd8bc98cfa7b5350ae6cecf83301006d7b5aaa5d5df153dcdb97edd91df254 | CUDA | 16,026 | 365 | /*!
* Copyright (c) 2017 Microsoft
* Licensed under The MIT License [see LICENSE for details]
* \file deformable_psroi_pooling.cu
* \brief
* \author Yi Li, Guodong Zhang, Jifeng Dai
*/
/***************** Adapted by Charles Shang *********************/
// modify from https://github.com/chengdazhi/Deformable-Convolu... |
378e42903cf263742fa6bc45ab8a5c11797bdc05cef701ac115b6051465274b4 | CUDA | 16,214 | 419 | /*!
* Copyright (c) 2017 Microsoft
* Licensed under The MIT License [see LICENSE for details]
* \file deformable_psroi_pooling.cu
* \brief
* \author Yi Li, Guodong Zhang, Jifeng Dai
*/
/***************** Adapted by Charles Shang *********************/
#include <cstdio>
#include <algorithm>
#include <cstring>
#inc... |
00b98505f7be461754e776ecd718f11ad663994941fd8e57ebe65ccad3f9a620 | CUDA | 17,168 | 330 | #include <stdbool.h>
#include <stdio.h>
#include "roi_crop_cuda_kernel.h"
#define real float
// Bilinear sampling is done in BHWD (coalescing is not obvious in BDHW)
// we assume BHWD format in inputImages
// we assume BHW(YX) format on grids
__device__ void getTopLeft(float x, int width, int& point, float& weight)
... |
1b02a8840a632db3f909a316ac6522c35d17945e71d7ba6a4e0aec1290177ff1 | CUDA | 17,604 | 528 | // **************************************************************************
// neighbor_gpu.cu
// -------------------
// Nitin Dhamankar (Intel)
// Peng Wang (Nvidia)
// W. Micha... |
f85cc3f07e9407ae320d37c0d381a91e59cf6bc6d1125bbfb835ee0257e23039 | CUDA | 18,200 | 443 | // **************************************************************************
// dpd.cu
// -------------------
// Trung Dac Nguyen (ORNL)
//
// Device code for acceleration of the dpd pair style
//
// ______________________________... |
244a96a5bc871e843a8fa43e7d466b5a22a2747d5d417dbddfb2a8bffc8bfea5 | CUDA | 18,211 | 419 | /*
* kcGLM_computeBlock.cu
* Computations for a GLM+derivatives (on one GPU).
*
* Package GMLM_dmc for dimensionality reduction of neural data.
*
* References
* Kenneth Latimer & David Freeedman (2021). Low-dimensional encoding of
* decisions in parietal cortex reflects long-term training history.
* ... |
790e3d09a5e28c6b2c3a33f6f54922a8702583153a272946584cd9da52e3aaf3 | CUDA | 19,107 | 469 | // **************************************************************************
// mdpd.cu
// -------------------
// Trung Dac Nguyen (ORNL)
//
// Device code for acceleration of the mdpd pair style
//
// ____________________________... |
6065d0401435b00a5e712edf44c9044fd766602982d77d799f5990cc5b15a086 | CUDA | 20,295 | 402 | #include "dcn_v2_im2col_cuda.h"
#include <cstdio>
#include <algorithm>
#include <cstring>
#include <ATen/ATen.h>
#include <ATen/cuda/CUDAContext.h>
#include <THC/THC.h>
#include <THC/THCAtomics.cuh>
#include <THC/THCDeviceUtils.cuh>
#define CUDA_KERNEL_LOOP(i, n) \
for (int i = blockIdx.x ... |
ab3ad1fbfa03d86578e343abdbf6f60be89d6d5e266dfb93a9f48823c718dd0a | CUDA | 22,024 | 515 | #include "deform_conv_cuda_kernel.cuh"
#include "parrots_cuda_helper.hpp"
void deformable_im2col(DArrayLite data_im, DArrayLite data_offset,
const int channels, const int height, const int width,
const int ksize_h, const int ksize_w, const int pad_h,
... |
45f9d9c40bb1d89f17c519f4f279b68de5d9bfaabf3a83a84849ef39ec098089 | CUDA | 22,187 | 515 | #include "deform_conv_cuda_kernel.cuh"
#include "pytorch_cuda_helper.hpp"
void deformable_im2col(Tensor data_im, Tensor data_offset, const int channels,
const int height, const int width, const int ksize_h,
const int ksize_w, const int pad_h, const int pad_w,
... |
39944e80b897c4687527de4c9a043b982cbfe0f6ad7daa67c6b31c5e4510601f | CUDA | 22,220 | 519 | // **************************************************************************
// dpd.cu
// -------------------
// Eddy BARRAUD (IFPEN/Sorbonne)
// Trung Dac Nguyen (U Chicago)
//
// Device code for acceler... |
0bd04b7804f9a38965ac3d44613dbdeceb306456a53619bf639118b729e6cd59 | CUDA | 25,599 | 506 | /*
* kcGLM_dataStructures.cu
* Holds all the data - parameters, results, regressors, computation space
* for a GLM (on one GPU).
*
* Package GMLM_dmc for dimensionality reduction of neural data.
*
* References
* Kenneth Latimer & David Freeedman (2021). Low-dimensional encoding of
* decisions in parie... |
bee509753ab9524f4066e8d23e37bd7e5d01833b8779219f35711ba27c8de738 | CUDA | 25,704 | 617 | // **************************************************************************
// edpd.cu
// -------------------
// Trung Dac Nguyen (U Chicago)
//
// Device code for acceleration of the edpd pair style
//
// _______________________... |
1fcb4b5b474d1a32e8fe77ceec7822b125c58381673b71d84763661be2b28e1a | CUDA | 26,700 | 725 | /*
* kcBase.cu
* classes for storing matrices (including stacks of matrices)
* keeps track of all the GPU stuff
*
* Package GMLM_dmc for dimensionality reduction of neural data.
*
* References
* Kenneth Latimer & David Freeedman (2021). Low-dimensional encoding of
* decisions in parietal cortex reflec... |
58191b97215a550ffdb129d93b768368f256d422422beec68e9fefebcf96336d | CUDA | 28,652 | 691 | // modify from
// https://github.com/chengdazhi/Deformable-Convolution-V2-PyTorch/blob/mmdetection/mmdet/ops/dcn/src/deform_conv_cuda.c
#include <ATen/ATen.h>
#include <ATen/cuda/CUDAContext.h>
#include <THC/THC.h>
#include <THC/THCDeviceUtils.cuh>
#include <vector>
#include <iostream>
#include <cmath>
void deform... |
9be00d0a9aebc8b8fec9ffd51757c38b400108ac178d5ed56a958219c016522e | CUDA | 28,658 | 749 | /* @file align.cu
**
** GPU implementation of the Adaptive banded Event Alignment algorithm
** @author: Hasindu Gamaarachchi (hasindu@unsw.edu.au)
** @@
******************************************************************************/
#include "f5c.h"
#include <assert.h>
#include "f5cmisc.cuh"
//#define DEBUG_ESTIMATE... |
a1afe552f60ef14cd5755172bc3fd3282d2611b5e3d98b6ef5b1cbb8a7795448 | CUDA | 30,576 | 791 | // **************************************************************************
// re_squared_lj.cu
// -------------------
// W. Michael Brown
//
// Device code for RE-Squared - Lennard-Jones potential acceleration
//
// ____________... |
29da22bdb7e172485135be919a3fe9f9cfd770d14fa3be1b3650984103ed3795 | CUDA | 31,410 | 691 | #include <vector>
#include <ATen/ATen.h>
#include <cuda.h>
#include <cuda_runtime.h>
#include <stdio.h>
#include <math.h>
#include <THC/THCDeviceUtils.cuh>
#include <THC/THCGeneral.h>
#include <ATen/ATen.h>
#include <ATen/AccumulateType.h>
#include <ATen/cuda/CUDAContext.h>
#include <ATen/cuda/CUDAApplyUtils.cuh>
#inc... |
beee41b13444b5bee2a802da767decf292beedf5b7c1119512e1a6823c29457e | CUDA | 41,164 | 1,058 | /* @file f5c.cu
**
** implementation of the f5c GPU framework
** @author: Hasindu Gamaarachchi (hasindu@unsw.edu.au)
** @@
******************************************************************************/
#include <errno.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <assert.h... |
da407dac2988c03d87e49c34c84ba750e366392161241aebcf5f735e684716c4 | CUDA | 42,362 | 874 | /*!
******************* BEGIN Caffe Copyright Notice and Disclaimer ****************
*
* COPYRIGHT
*
* All contributions by the University of California:
* Copyright (c) 2014-2017 The Regents of the University of California (Regents)
* All rights reserved.
*
* All other contributions:
* Copyright (c) 2014-201... |
412e6b86d5ac55a9391117d8dd9d7b02aed679b41c5132ffed9002e04b3e0590 | CUDA | 48,605 | 960 | /*
* kcGMLM_dataStructures.cu
* Holds all the data - parameters, results, regressors, computation space
* for a GMLM (on one GPU).
*
* Package GMLM_dmc for dimensionality reduction of neural data.
*
* References
* Kenneth Latimer & David Freeedman (2021). Low-dimensional encoding of
* decisions in par... |
9fe8d16d34c50df3c989f3f3ee8593a7748c590a24a79c05e75d650968e699b6 | CUDA | 90,803 | 1,673 | /*
* kcGMLM_computeBlock.cu
* Computations for a GMLM+derivatives (on one GPU).
*
* Package GMLM_dmc for dimensionality reduction of neural data.
*
* References
* Kenneth Latimer & David Freeedman (2021). Low-dimensional encoding of
* decisions in parietal cortex reflects long-term training history.
*... |
897c0c8c02705b9d4ce0a3297b4cb81e0b9c1906383f18d08a7c755378743ab9 | CUDA | 92,540 | 1,725 | /*
* kcGMLMPop_computeBlock.cu
* Computations for a GMLMPop+derivatives (on one GPU).
*
* Package GMLM_dmc for dimensionality reduction of neural data.
*
* References
* Kenneth Latimer & David Freeedman (2021). Low-dimensional encoding of
* decisions in parietal cortex reflects long-term training histo... |
96920ca7b4dadd3ebd2a71c35a99b4f4972a4635893c52c663ca8c75b9600564 | Java | 83 | 7 | package mbqtl.enums;
public enum AnalysisType {
CIS,
TRANS,
CISTRANS
} |
8362cd007cfe1c6d66714a5c5e7b17f60f9c5a18c5dc2c45dba1b3e1b704ce6a | Java | 97 | 6 | package ebi.spot.neo4j2owl.importer;
public enum LABELLING_MODE
{
QSL, SL_STRICT, SL_LOSE;
} |
375979e04bb00244e62adb840604145d28dc7ad354a62c15897e863557541621 | Java | 99 | 8 | package mbqtl.enums;
public enum PermutationStrategy {
MATCHED,
SEMIRANDOM,
RANDOM
}
|
ea32a12253c48cfcc93cbc87d02029c82894f32b64773ca1e89abd9a9e250236 | Java | 101 | 7 | package mbqtl.enums;
public enum MetaAnalysisMethod {
EMP,
FISHERZFIXED,
FISHERZRANDOM
} |
45988921fea86aaf23d7c0a891e00989f9a013a1f98b241a4f1165543fa6cdc5 | Java | 106 | 7 | package mbqtl.enums;
public enum StatisticalTest {
WEIGHTEDCORRELATION,
UNWEIGHTEDCORRELATION
}
|
0f583d0a192ed8f42526336916eeef22b84fc9b0428bdb9fe47d11faec810f81 | Java | 109 | 7 | package umcg.genetica.features;
/**
* Created by hwestra on 9/1/15.
*/
public class NarrowPeakFeature {
}
|
de33cdbfb454f6aead14036defabf0fccf493358648af6cfda25d3bb7cd306e4 | Java | 115 | 6 | package nl.systemsgenetics.downstreamer.runners.options;
public interface HelpProvider {
void printHelp();
}
|
78daf3fc5ee7cf5ba642428eb2ff8944cfd134e88819ce0cb267390670cb9ff3 | Java | 117 | 6 | package org.molgenis.genotype.variant;
public interface VariantLineMapper
{
GeneticVariant mapLine(String line);
}
|
b7c26de635d64e4d4a04c9743da5ed3942a158bfd968d7c85c7afb561ec66d39 | Java | 133 | 11 | package nl.systemsgenetics.geneticriskscorecalculator;
/**
*
* @author Patrick Deelen
*/
public interface PhenotypeData {
}
|
15544f966dbc0a179449980b4e8a8c285099f02958d636e5b37c2fd0b64b1019 | Java | 136 | 8 | package org.molgenis.genotype;
import java.io.Closeable;
public interface RawLineQueryResult extends Closeable, Iterable<String>
{
}
|
99d1f21542b301852c09d7dc92e3139d4d1a9529d162d426020dd5061031db3a | Java | 137 | 9 | package org.molgenis.genotype.vcf.VcfGenotypeField;
public enum VcfGenotypeFormat {
GT(),
GP(),
HP(),
DS(),
ADS()
}
|
0c911676b7a2a6f8de997499db506048e9aebaf9e6e6219acafd99e44ac168b2 | Java | 164 | 15 | package eqtlmappingpipeline.ase;
/**
*
* @author Patrick Deelen
*/
public enum MultipleTestingCorrectionMethod {
NONE,
BONFERRONI,
HOLM,
BH,
NOMINAL;
}
|
5c8b91f407e99a388e3db58748cdf10b17fc768331386e9ecceb06c6bce29f81 | Java | 168 | 8 | package edu.cmu.cs.eyetrack.io;
import java.util.List;
public interface CSVWritable {
public String[] getCSVHeader();
public List<String[]> getCSVData();
}
|
69d470376d51ed384cddc302bbbef9e79df11f5cdfea5d1483c2efb604a447bb | Java | 188 | 11 | package mbqtl.vcf.filter.genotypefilters;
import mbqtl.vcf.VCFVariant;
/**
* Created by hwestra on 2/8/16.
*/
public interface VCFGenotypeFilter {
void filter(VCFVariant variant);
}
|
ae3ef2530c644f7a9cba0727296e678a0dbe1cf1fa1bfb6f8d77368458eead80 | Java | 191 | 12 | package org.molgenis.genotype;
import java.util.List;
public interface GenotypeDataIndex
{
List<String> getSeqNames();
VariantQuery createQuery();
RawLineQuery createRawLineQuery();
}
|
fa713931b48f8f2c6a3519153238085c31101efe5fe60e2d2b5fce0a64fa2b50 | Java | 199 | 11 | package mbqtl.vcf.filter.variantfilters;
import mbqtl.vcf.VCFVariant;
/**
* Created by hwestra on 3/21/17.
*/
public interface VCFVariantFilter {
boolean passesThreshold(VCFVariant variant);
}
|
dc82c2e783b4a78f0847137edbe23147491005e1394abc34dd6c3f40a20dcef1 | Java | 209 | 8 | package edu.cmu.cs.eyetrack.analysis.score.distance;
import edu.cmu.cs.eyetrack.analysis.struct.Frame;
public abstract class DistanceFunction {
public abstract Double distance(Frame a, Frame b);
}
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.