diff options
Diffstat (limited to 'src/kernels/levelx')
| -rw-r--r-- | src/kernels/levelx/xconvgemm_part1.opencl | 113 | ||||
| -rw-r--r-- | src/kernels/levelx/xconvgemm_part2.opencl | 281 |
2 files changed, 394 insertions, 0 deletions
diff --git a/src/kernels/levelx/xconvgemm_part1.opencl b/src/kernels/levelx/xconvgemm_part1.opencl new file mode 100644 index 00000000..abdb5324 --- /dev/null +++ b/src/kernels/levelx/xconvgemm_part1.opencl @@ -0,0 +1,113 @@ + +// ================================================================================================= +// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This +// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max- +// width of 100 characters per line. +// +// Author(s): +// Cedric Nugteren <www.cedricnugteren.nl> +// +// This file contains the an implementation of 3D convolution on a 4D image using GEMM kernels. It +// uses parameters from the direct GEMM kernel. This is the part with the loads from memory (1/2). +// This uses "CONVGEMM_WITH_IM2COL" as a switch to select between direct convgemm or first running +// the im2col kernel to create a 'col' temporary matrix. +// TODO: Currently only works with 'CONVGEMM_WITH_IM2COL' set +// +// ================================================================================================= + +// Enables loading of this file using the C++ pre-processor's #include (C++11 standard raw string +// literal). Comment-out this line for syntax-highlighting when developing. +R"( + +// ================================================================================================= +#if defined(ROUTINE_CONVGEMM) && !defined(CONVGEMM_WITH_IM2COL) + +// Loads global off-chip memory into thread-private register files. This function is specific for +// loading the image input tensor. This includes a bounds check. +INLINE_FUNC real GlobalToPrivateCheckedImage(const __global real* restrict imagegm, const int image_offset_batch, + const int h_id, const int w_id, const int kwg, + const int input_h, const int input_w, const int channels, + const int kernel_h, const int kernel_w, + const int pad_h, const int pad_w, + const int stride_h, const int stride_w, + const int dilation_h, const int dilation_w) { + + // Im2col indices + const int kernel_2d_index = kwg % (kernel_h * kernel_w); + const int kw_id = kernel_2d_index % kernel_w; + const int kh_id = kernel_2d_index / kernel_w; + const int c_id = kwg / (kernel_h * kernel_w); + const int h_index = -pad_h + kh_id * dilation_h + stride_h * h_id; + const int w_index = -pad_w + kw_id * dilation_w + stride_w * w_id; + + // With bounds check + real result; + if (h_index >= 0 && h_index < input_h && + w_index >= 0 && w_index < input_w) { + const int image_index = w_index + input_w * (h_index + input_h * c_id); + result = imagegm[image_index + image_offset_batch]; + } + else { + SetToZero(result); + } + return result; +} + +// Loads global off-chip memory into local (shared) memory on-chip. This function is specific for +// loading the image input tensor. This includes a bounds check. +INLINE_FUNC real GlobalToLocalCheckedImage(const __global realMD* restrict imagegm, LOCAL_PTR real* alm, + const int image_offset_batch, + const int h_id, const int w_id, const int kwg, + const int input_h, const int input_w, const int channels, + const int kernel_h, const int kernel_w, + const int pad_h, const int pad_w, + const int stride_h, const int stride_w, + const int dilation_h, const int dilation_w) { + #if MDIMCD == MDIMAD + const int la0 = get_local_id(0); + const int la1 = get_local_id(1); + #else + const int tid = get_local_id(0) + MDIMCD*get_local_id(1); + const int la0 = tid % MDIMAD; + const int la1 = tid / MDIMAD; + #endif + #pragma unroll + for (int _mia = 0; _mia < MWAD; _mia += 1) { + #pragma unroll + for (int _kia = 0; _kia < KWAD; _kia += 1) { + + // Computes the indices for the global memory + int mg = _mia + la0*MWAD; + int kg = _kia + la1*KWAD; + int idm = mg + GetGroupID0()*WGD; + int idk = kg + kwg; + + // Im2col indices + const int kernel_2d_index = idk % (kernel_h * kernel_w); + const int kw_id = kernel_2d_index % kernel_w; + const int kh_id = kernel_2d_index / kernel_w; + const int c_id = idk / (kernel_h * kernel_w); + const int h_index = -pad_h + kh_id * dilation_h + stride_h * h_id; + const int w_index = -pad_w + kw_id * dilation_w + stride_w * w_id; + + // Loads the data from global memory into the local memory + if (h_index >= 0 && h_index < input_h && + w_index >= 0 && w_index < input_w) { + const int image_index = w_index + input_w * (h_index + input_h * c_id); + const real result = imagegm[image_index + image_offset_batch]; + alm[kg*(WGD + PADA) + mg] = result; + } + else { + SetToZero(alm[kg*(WGD + PADA) + mg]); + } + } + } +} + +#endif +// ================================================================================================= + +// End of the C++11 raw string literal +)" + +// ================================================================================================= diff --git a/src/kernels/levelx/xconvgemm_part2.opencl b/src/kernels/levelx/xconvgemm_part2.opencl new file mode 100644 index 00000000..e0ac24a0 --- /dev/null +++ b/src/kernels/levelx/xconvgemm_part2.opencl @@ -0,0 +1,281 @@ + +// ================================================================================================= +// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This +// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max- +// width of 100 characters per line. +// +// Author(s): +// Cedric Nugteren <www.cedricnugteren.nl> +// +// This file contains the an implementation of 3D convolution on a 4D image using GEMM kernels. It +// uses parameters from the direct GEMM kernel. This part contains the main kernel (2/2). +// This uses "CONVGEMM_WITH_IM2COL" as a switch to select between direct convgemm or first running +// the im2col kernel to create a 'col' temporary matrix. +// TODO: Currently only works with 'CONVGEMM_WITH_IM2COL' set +// +// ================================================================================================= + +// Enables loading of this file using the C++ pre-processor's #include (C++11 standard raw string +// literal). Comment-out this line for syntax-highlighting when developing. +R"( + +// ================================================================================================= +#if defined(ROUTINE_CONVGEMM) + +// ConvGEMM kernel +__kernel __attribute__((reqd_work_group_size(MDIMCD, NDIMCD, 1))) +void Xconvgemm(const int num_patches, const int num_kernels, const int patch_size, + const __global realND* restrict kernelgm, const int kernel_offset, + __global real* resultgm, const int result_offset, const int result_stride, +#if defined(CONVGEMM_WITH_IM2COL) + const __global realMD* restrict colgm, const int col_offset, const int col_stride) +#else + const __global realMD* restrict imagegm, const int image_offset, + const int input_h, const int input_w, const int channels, + const int kernel_h, const int kernel_w, + const int pad_h, const int pad_w, + const int stride_h, const int stride_w, + const int dilation_h, const int dilation_w, + const int output_h, const int output_w) +#endif +{ + + // Batch offsets + const int batch = get_group_id(2); + #if defined(CONVGEMM_WITH_IM2COL) + const int col_offset_batch = col_offset + col_stride * batch; + #else + const int image_offset_batch = image_offset + channels * input_h * input_w * batch; + #endif + const int result_offset_batch = result_offset + result_stride * batch; + + __local real alm[WGD * (WGD + PADA)]; + __local real blm[WGD * (WGD + PADB)]; + + // Extra pointers to scalar versions of global memory + #if defined(CONVGEMM_WITH_IM2COL) + const __global real* restrict colgms = (const __global real* restrict) colgm; + #endif + const __global real* restrict kernelgms = (const __global real* restrict) kernelgm; + + // Allocates workitem-private memory (registers) + #pragma promote_to_registers + real apd[MWID]; + #pragma promote_to_registers + real bpd[NWID]; + #pragma promote_to_registers + real cpd[NWID * MWID]; + + // Initializes the accumulation registers + #pragma unroll + for (int _mi = 0; _mi < MWID; _mi += 1) { + #pragma unroll + for (int _ni = 0; _ni < NWID; _ni += 1) { + SetToZero(cpd[_ni * MWID + _mi]); + } + } + + // Global m/n indices + const int idm = get_local_id(0) * MWID + GetGroupID0() * WGD; + const int idn = get_local_id(1) * NWID + GetGroupID1() * WGD; + #if !defined(CONVGEMM_WITH_IM2COL) + const int w_id = idm % output_w; + const int h_id = idm / output_w; + #endif + + // 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 ((idm < (num_patches/WGD)*WGD) && (idn < (num_kernels/WGD)*WGD)) { + + // Loops over all complete workgroup tiles (K-dimension) + int kwg = 0; + for (; kwg < (patch_size/WGD) * WGD; kwg += WGD) { + + // Loads data: off-chip --> local (matrix A and B) + #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); + } + else { + GlobalToLocalScalarB(kernelgms, blm, patch_size, kernel_offset, kwg, true, false); + } + barrier(CLK_LOCAL_MEM_FENCE); + + // Loops over all workitem tiles, unrolled by a factor KWID + for (int pwi = 0; pwi < WGD; pwi += KWID) { + #pragma unroll + for (int _pit = 0; _pit < KWID; _pit += 1) { + int kg = pwi + _pit; + + // Loads data: local --> private (matrix A and B) + #pragma unroll + for (int _mi = 0; _mi < MWID; _mi += 1) { + apd[_mi] = LocalToPrivateDirectA(alm, _mi, kg, false); + } + #pragma unroll + for (int _ni = 0; _ni < NWID; _ni += 1) { + bpd[_ni] = LocalToPrivateDirectB(blm, _ni, kg, true); + } + + // Performs the accumulation (Cpmd += Apmd * Bpmd) + #pragma unroll + for (int _ni = 0; _ni < NWID; _ni += 1) { + #pragma unroll + for (int _mi = 0; _mi < MWID; _mi += 1) { + MultiplyAdd(cpd[_ni * MWID + _mi], apd[_mi], bpd[_ni]); + } + } + } + } + barrier(CLK_LOCAL_MEM_FENCE); + } + + // Loop over the remaining part (incomplete tile in K-dimension) + for (; kwg < patch_size; ++kwg) { + + // Loads data: off-chip --> private (matrix A and B) + #pragma unroll + for (int _mi = 0; _mi < MWID; _mi += 1) { + #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) { + bpd[_ni] = GlobalToPrivateDirectB(kernelgms, _ni, patch_size, kernel_offset, idn, kwg, true, false); + } + + // Performs the accumulation (Cpmd += Apmd * Bpmd) + #pragma unroll + for (int _ni = 0; _ni < NWID; _ni += 1) { + #pragma unroll + for (int _mi = 0; _mi < MWID; _mi += 1) { + MultiplyAdd(cpd[_ni * MWID + _mi], apd[_mi], bpd[_ni]); + } + } + } + + // Stores a tile of results + #pragma unroll + for (int _ni = 0; _ni < NWID; _ni += 1) { + #pragma unroll + for (int _mi = 0; _mi < MWID; _mi += 1) { + StoreResultsDirect(resultgm, cpd[_ni * MWID + _mi], _mi, _ni, idm, idn, + ONE, ZERO, num_patches, result_offset_batch, false); + } + } + } + + // Simple but slower version for the parts on the edge (incomplete tiles in M and N-dimensions) + else { + // Loops over all complete workgroup tiles (K-dimension) + int kwg = 0; + for (; kwg < (patch_size/WGD) * WGD; kwg+=WGD) { + + // Loads data: off-chip --> local + #if defined(CONVGEMM_WITH_IM2COL) + GlobalToLocalCheckedA(colgms, alm, num_patches, col_offset_batch, kwg, false, false, num_patches, patch_size); + #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 + GlobalToLocalCheckedB(kernelgms, blm, patch_size, kernel_offset, kwg, true, false, num_kernels, patch_size); + barrier(CLK_LOCAL_MEM_FENCE); + + // Loops over all workitem tiles, unrolled by a factor KWID + for (int pwi = 0; pwi < WGD; pwi += KWID) { + #pragma unroll + for (int _pit = 0; _pit < KWID; _pit += 1) { + int kg = pwi + _pit; + + // Loads data: local --> private + #pragma unroll + for (int _mi = 0; _mi < MWID; _mi += 1) { + apd[_mi] = LocalToPrivateDirectA(alm, _mi, kg, false); + } + #pragma unroll + for (int _ni = 0; _ni < NWID; _ni += 1) { + bpd[_ni] = LocalToPrivateDirectB(blm, _ni, kg, true); + } + + // Performs the accumulation (C += A * B) + #pragma unroll + for (int _ni = 0; _ni < NWID; _ni += 1) { + #pragma unroll + for (int _mi = 0; _mi < MWID; _mi += 1) { + MultiplyAdd(cpd[_ni * MWID + _mi], apd[_mi], bpd[_ni]); + } + } + } + } + barrier(CLK_LOCAL_MEM_FENCE); + } + + // Loop over the remaining part (incomplete tile in K-dimension) + for (; kwg < patch_size; ++kwg) { + + // Loads data: off-chip --> private + #pragma unroll + for (int _mi = 0; _mi < MWID; _mi += 1) { + #if defined(CONVGEMM_WITH_IM2COL) + apd[_mi] = GlobalToPrivateCheckedA(colgms, _mi, num_patches, col_offset_batch, idm, kwg, false, false, num_patches); + #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) { + bpd[_ni] = GlobalToPrivateCheckedB(kernelgms, _ni, patch_size, kernel_offset, idn, kwg, true, false, num_kernels); + } + + // Performs the accumulation (C += A * B) + #pragma unroll + for (int _ni = 0; _ni < NWID; _ni += 1) { + #pragma unroll + for (int _mi = 0; _mi < MWID; _mi += 1) { + MultiplyAdd(cpd[_ni * MWID + _mi], apd[_mi], bpd[_ni]); + } + } + } + + // Stores a tile of results + #pragma unroll + for (int _ni = 0; _ni < NWID; _ni += 1) { + #pragma unroll + for (int _mi = 0; _mi < MWID; _mi += 1) { + StoreResultsChecked(resultgm, cpd[_ni * MWID + _mi], _mi, _ni, idm, idn, num_patches, num_kernels, + ONE, ZERO, num_patches, result_offset_batch, false); + } + } + } +} + +#endif +// ================================================================================================= + +// End of the C++11 raw string literal +)" + +// ================================================================================================= |