diff options
| -rw-r--r-- | src/kernels/levelx/xconvgemm_part2.opencl | 32 | ||||
| -rw-r--r-- | test/correctness/testblas.hpp | 2 |
2 files changed, 22 insertions, 12 deletions
diff --git a/src/kernels/levelx/xconvgemm_part2.opencl b/src/kernels/levelx/xconvgemm_part2.opencl index f9b78974..46a72711 100644 --- a/src/kernels/levelx/xconvgemm_part2.opencl +++ b/src/kernels/levelx/xconvgemm_part2.opencl @@ -84,7 +84,6 @@ void Xconvgemm(const int num_patches, const int num_kernels, const int patch_siz // The faster version of GEMM is not allowed on the (incomplete) borders. Therefore, this section // processes only the main parts: output blocks of WGD by WGD. - #if defined(CONVGEMM_WITH_IM2COL) // TEMP: To be implemented for other case as well if ((idm < (num_patches/WGD)*WGD) && (idn < (num_kernels/WGD)*WGD)) { // Loops over all complete workgroup tiles (K-dimension) @@ -92,12 +91,19 @@ void Xconvgemm(const int num_patches, const int num_kernels, const int patch_siz for (; kwg < (patch_size/WGD) * WGD; kwg += WGD) { // Loads data: off-chip --> local (matrix A and B) - if (num_patches % VWMD == 0 && col_offset_batch % VWMD == 0) { - GlobalToLocalDirectA(colgm, alm, num_patches, col_offset_batch, kwg, false, false); - } - else { - GlobalToLocalScalarA(colgms, alm, num_patches, col_offset_batch, kwg, false, false); - } + #if defined(CONVGEMM_WITH_IM2COL) + if (num_patches % VWMD == 0 && col_offset_batch % VWMD == 0) { + GlobalToLocalDirectA(colgm, alm, num_patches, col_offset_batch, kwg, false, false); + } + else { + GlobalToLocalScalarA(colgms, alm, num_patches, col_offset_batch, kwg, false, false); + } + #else + GlobalToLocalCheckedImage(imagegm, alm, image_offset_batch, h_id, w_id, kwg, + input_h, input_w, channels, kernel_h, kernel_w, + pad_h, pad_w, stride_h, stride_w, + dilation_h, dilation_w); + #endif if (patch_size % VWND == 0 && kernel_offset % VWND == 0) { GlobalToLocalDirectB(kernelgm, blm, patch_size, kernel_offset, kwg, true, false); } @@ -141,7 +147,14 @@ void Xconvgemm(const int num_patches, const int num_kernels, const int patch_siz // Loads data: off-chip --> private (matrix A and B) #pragma unroll for (int _mi = 0; _mi < MWID; _mi += 1) { - apd[_mi] = GlobalToPrivateDirectA(colgms, _mi, num_patches, col_offset_batch, idm, kwg, false, false); + #if defined(CONVGEMM_WITH_IM2COL) + apd[_mi] = GlobalToPrivateDirectA(colgms, _mi, num_patches, col_offset_batch, idm, kwg, false, false); + #else + apd[_mi] = GlobalToPrivateCheckedImage(imagegm, image_offset_batch, h_id, w_id, kwg, + input_h, input_w, channels, kernel_h, kernel_w, + pad_h, pad_w, stride_h, stride_w, + dilation_h, dilation_w); + #endif } #pragma unroll for (int _ni = 0; _ni < NWID; _ni += 1) { @@ -171,9 +184,6 @@ void Xconvgemm(const int num_patches, const int num_kernels, const int patch_siz // Simple but slower version for the parts on the edge (incomplete tiles in M and N-dimensions) else { - #else // TEMP, to be implemented - { // TEMP, to be implemented - #endif // TEMP, to be implemented // Loops over all complete workgroup tiles (K-dimension) int kwg = 0; for (; kwg < (patch_size/WGD) * WGD; kwg+=WGD) { diff --git a/test/correctness/testblas.hpp b/test/correctness/testblas.hpp index 0dc8584e..6c0abab6 100644 --- a/test/correctness/testblas.hpp +++ b/test/correctness/testblas.hpp @@ -139,7 +139,7 @@ template <typename T, typename U> const std::vector<size_t> TestBlas<T,U>::kBatc template <typename T, typename U> const std::vector<size_t> TestBlas<T,U>::kPadSizes = { 0, 1 }; template <typename T, typename U> const std::vector<size_t> TestBlas<T,U>::kDilationSizes = { 1, 2 }; template <typename T, typename U> const std::vector<size_t> TestBlas<T,U>::kKernelSizes = { 1, 3 }; -template <typename T, typename U> const std::vector<size_t> TestBlas<T,U>::kNumKernels = { 1, 2 }; +template <typename T, typename U> const std::vector<size_t> TestBlas<T,U>::kNumKernels = { 1, 67 }; template <typename T, typename U> const std::vector<size_t> TestBlas<T,U>::kStrideValues = { 1, 3 }; template <typename T, typename U> const std::vector<size_t> TestBlas<T,U>::kChannelValues = { 1, 4 }; |