mirror of
https://github.com/open-mmlab/mmdeploy.git
synced 2025-01-14 08:09:43 +08:00
* minor changes * support windows * fix GCC build * fix lint * reformat * fix Windows build * fix GCC build * search backend ops for onnxruntime * fix lint * fix lint * code clean-up * code clean-up * fix clang build * fix trt support * fix cmake for ncnn * fix cmake for openvino * fix SDK Python API * handle ops for other backends (ncnn, trt) * handle SDK Python API library location * robustify linkage * fix cuda * minor fix for openvino & ncnn * use CMAKE_CUDA_ARCHITECTURES if set * fix cuda preprocessor * fix misc * fix pplnn & pplcv, drop support for pplcv<0.6.0 * robustify cmake * update build.md (#2) * build dynamic modules as module library & fix demo (partially) * fix candidate path for mmdeploy_python * move "enable CUDA" to cmake config for demo * refine demo cmake * add comment * fix ubuntu build * revert docs/en/build.md * fix C API * fix lint * Windows build doc (#3) * check in docs related to mmdeploy build on windows * update build guide on windows platform * update build guide on windows platform * make path of thirdparty libraries consistent * make path consistency * correct build command for custom ops * correct build command for sdk * update sdk build instructions * update doc * correct build command * fix lint * correct build command and fix lint Co-authored-by: lvhan <lvhan@pjlab.org> * trailing whitespace (#4) * minor fix * fix sr sdk model * fix type deduction * fix cudaFree after driver shutting down * update ppl.cv installation warning (#5) * fix device allocator threshold & fix lint * update doc (#6) * update ppl.cv installation warning * missing 'git clone' Co-authored-by: chenxin <chenxin2@sensetime.com> Co-authored-by: zhangli <zhangli@sensetime.com> Co-authored-by: lvhan028 <lvhan_028@163.com> Co-authored-by: lvhan <lvhan@pjlab.org>
32 lines
874 B
Plaintext
32 lines
874 B
Plaintext
// Copyright (c) OpenMMLab. All rights reserved.
|
|
|
|
#include <cuda_runtime.h>
|
|
|
|
namespace mmdeploy {
|
|
namespace cuda {
|
|
|
|
__global__ void FillKernel(void* dst, size_t dst_size, const void* pattern, size_t pattern_size) {
|
|
size_t idx = threadIdx.x + blockIdx.x * blockDim.x;
|
|
|
|
auto p_dst = static_cast<uchar1*>(dst);
|
|
auto p_pattern = static_cast<const uchar1*>(pattern);
|
|
|
|
for (; idx < dst_size; idx += blockDim.x * gridDim.x) {
|
|
auto ptr = idx % pattern_size;
|
|
p_dst[idx] = p_pattern[ptr];
|
|
}
|
|
}
|
|
|
|
int Fill(void* dst, size_t dst_size, const void* pattern, size_t pattern_size,
|
|
cudaStream_t stream) {
|
|
const unsigned int n_threads = 256;
|
|
const unsigned int n_blocks = (dst_size + n_threads - 1) / n_threads;
|
|
|
|
FillKernel<<<n_blocks, n_threads, 0, stream>>>(dst, dst_size, pattern, pattern_size);
|
|
|
|
return 0;
|
|
}
|
|
|
|
} // namespace cuda
|
|
} // namespace mmdeploy
|