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Diffstat (limited to 'src/core/CL/cl_kernels/nhwc/dwc_native_fp_nhwc.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/nhwc/dwc_native_fp_nhwc.cl | 211 |
1 files changed, 211 insertions, 0 deletions
diff --git a/src/core/CL/cl_kernels/nhwc/dwc_native_fp_nhwc.cl b/src/core/CL/cl_kernels/nhwc/dwc_native_fp_nhwc.cl new file mode 100644 index 0000000000..dcbae220b6 --- /dev/null +++ b/src/core/CL/cl_kernels/nhwc/dwc_native_fp_nhwc.cl @@ -0,0 +1,211 @@ +/* + * Copyright (c) 2021-2023 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * 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. + */ + +#include "activation_float_helpers.h" +#include "helpers.h" +#include "tile_helpers.h" +// *INDENT-OFF* +// clang-format off +#if defined(WEI_WIDTH) && defined(WEI_HEIGHT) && defined(N0) && defined(M0) && defined(DILATION_X) && defined(DILATION_Y) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(PAD_LEFT) && defined(PAD_TOP) +//! @cond Doxygen_Suppress +/** OpenCL kernel to compute the depthwise convolution for floating-point data types (F32/F16) + * + * @note Data layout supported: NHWC + * @note Data type supported: F32/F16 + * @note The accumulation data type must be passed at compile time using -DACC_DATA_TYPE (e.g. -DDATA_TYPE_PROMOTED=half) + * @note The convolution padding (left and top) must be passed at compile time using -DPAD_LEFT and -DPAD_TOP (e.g. -DPAD_LEFT=2, -DPAD_TOP=2) + * @note The convolution strides must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y (e.g. -DSTRIDE_X=2, -DSTRIDE_Y=2) + * @note The convolution dilations must be passed at compile time using -DDILATION_X and -DDILATION_Y (e.g. -DDILATION_X=2, -DDILATION_Y=2) + * @note The spatial dimensions of the weights must be passed at compile time using -DWEI_WIDTH and -DWEI_HEIGHT (e.g. -DWEI_WIDTH=9, -DWEI_HEIGHT=9) + * @note The tensor type ("BUFFER" or "IMAGE") of the source tensor must be passed at compile time using -DSRC_TENSOR_TYPE (e.g. -DSRC_TENSOR_TYPE=BUFFER) + * @note The tensor type ("BUFFER" or "IMAGE") of the weights tensor must be passed at compile time using -DWEI_TENSOR_TYPE (e.g. -DWEI_TENSOR_TYPE=BUFFER) + * @note The tensor type ("BUFFER" or "IMAGE") of the destination tensor must be passed at compile time using -DDST_TENSOR_TYPE (e.g. -DDST_TENSOR_TYPE=BUFFER) + * @note The data type of the source tensor must be passed at compile time using -DSRC_DATA_TYPE (e.g. -DSRC_DATA_TYPE=float) + * @note The data type of the weights tensor must be passed at compile time using -DWEI_DATA_TYPE (e.g. -DWEI_DATA_TYPE=float) + * @note The data type of the destination tensor must be passed at compile time using -DDST_DATA_TYPE (e.g. -DDST_DATA_TYPE=float) + * @note The data type of the accumulators must be passed at compile time using -DACC_DATA_TYPE (e.g. -DACC_DATA_TYPE=float) + * @note The number of M0 rows (width) to process must be passed at compile time using -DM0 (e.g. -DM0=2) + * @note The number of N0 output channels to process must be passed at compile time using -DN0 (e.g. -DN0=2) + * @note The size of the partial store block in the first dimension must be passed at compile time using -DPARTIAL_N0 (e.g. -DPARTIAL_N0=1) + * @note Only the following configurations of M0 and N0 are currently supported: + * - M0 = 1, 2, 3, 4, 5, .... n (M0 != 1 with STRIDE_X == 1 && DILATION_X == 1 only) + * - N0 = 2, 3, 4, 8, 16 (only 4, 8 and 16 if WEI_TENSOR_TYPE=IMAGE) + * @note The number of rows to read from the src tensor must be passed at compile time using -DM0_A (e.g., -DM0_A=3). M0_A must be equal to WEI_WIDTH + (M0 - 1) + * @note The number of columns to read from the src tensor must be passed at compile time using -DN0_A. It can either be 1 (for DEPTH_MULTIPLIER > 1) or N0 (for DEPTH_MULTIPLIER == 1) + * + * @param[in] src_img (Not supported) Read only cl_image object for the source tensor. Included when SRC_TENSOR_TYPE=IMAGE + * @param[in] src_ptr Pointer to the source tensor. Supported data type: F16/F32 + * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes) + * @param[in] src_c The size of the channels dimension of the source tensor + * @param[in] src_w The size of the width dimension of the source tensor + * @param[in] src_h The size of the height dimension of the source tensor + * @param[in] src_n The size of the batches dimension of the source tensor + * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[out] dst_img (Not supported) Write only cl_image object for the destination tensor. Included when DST_TENSOR_TYPE=IMAGE + * @param[out] dst_ptr Pointer to the destination tensor. Supported data type: same as @p src_ptr + * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) + * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes) + * @param[in] dst_c The size of the channels dimension of the destination tensor + * @param[in] dst_w The size of the width dimension of the destination tensor + * @param[in] dst_h The size of the height dimension of the destination tensor + * @param[in] dst_n The size of the batches dimension of the destination tensor + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor + * @param[in] wei_img (Optional) Read only cl_image object for the weights tensor. Included when WEI_TENSOR_TYPE=IMAGE + * @param[in] wei_ptr Pointer to the weights tensor. Supported data type: same as @p src_ptr + * @param[in] wei_stride_y Stride of the weights tensor in Y dimension (in bytes) + * @param[in] wei_stride_z Stride of the weights tensor in Z dimension (in bytes) + * @param[in] wei_stride_w Stride of the weights tensor in W dimension (in bytes) + * @param[in] wei_c The size of the channels dimension of the weights tensor + * @param[in] wei_w The size of the width dimension of the weights tensor + * @param[in] wei_h The size of the height dimension of the weights tensor + * @param[in] wei_n The size of the batches dimension of the weights tensor + * @param[in] wei_offset_first_element_in_bytes The offset of the first element in the weigts matrix + * @param[in] bia_ptr (Optional) Pointer to the bias tensor Supported data type: same as @p src_ptr + * @param[in] bia_stride_x (Optional) Stride of the bias tensor in X dimension (in bytes) + * @param[in] bia_step_x (Optional) bia_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] bia_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix + */ +//! @endcond +__kernel void dwc_native_fp_nhwc( + TENSOR4D_RO_T(src, SRC_TENSOR_TYPE), + TENSOR4D_WO_T(dst, DST_TENSOR_TYPE), + TENSOR4D_RO_T(wei, WEI_TENSOR_TYPE) +#if defined(HAS_BIAS) + , + VECTOR_DECLARATION(bia) +#endif // defined(HAS_BIAS) +) +{ + // Only the weight tensor dimensions are passed at compile time. + // In case of dynamic tensor support, the following dimensions should be passed as function argument. +#define _IWEI_WIDTH WEI_WIDTH +#define _IWEI_HEIGHT WEI_HEIGHT +#define _IM0_A M0_A // _IWEI_WIDTH + (M0 - 1) Rows tile A (If M0 != 1, the tiles overlap of 1 element on the X dimension) +#define _IN0_A N0_A // Cols tile A. It can be either 1 (for DEPTH_MULTIPLIER > 1) or N0 (for DEPTH_MULTIPLIER == 1) +#define _IM0_B _IWEI_WIDTH // Rows tile B +#define _IN0_B N0 // Cols tile B +#define _IBOUNDARY_CHECK (!((WEI_WIDTH == 1 && WEI_HEIGHT == 1 && PAD_LEFT == 0 && PAD_TOP == 0 && M0 == 1))) + + const int cout = GET_SPATIAL_IDX(0, N0, PARTIAL_N0); // OFM + const int xo = GET_SPATIAL_IDX(1, M0, 0); // WIDTH +#if defined(BATCHED_EXECUTION) + const int yo = GET_SPATIAL_IDX(2, 1, 0) % dst_h; // HEIGHT + const int bout = GET_SPATIAL_IDX(2, 1, 0) / dst_h; // BATCH SIZE IDX +#else // defined(BATCHED_EXECUTION) + const int yo = GET_SPATIAL_IDX(2, 1, 0); // HEIGHT + const int bout = 0; // BATCH SIZE IDX +#endif // defined(BATCHED_EXECUTION) + + int xi = xo * STRIDE_X; + int yi = yo * STRIDE_Y; + xi -= PAD_LEFT; + yi -= PAD_TOP; + + TILE(ACC_DATA_TYPE, M0, N0, c); + + // Reset accumulators + LOOP_UNROLLING(int, i, 0, 1, M0, + { + c[i].v = 0; + }) + +#if _IWEI_HEIGHT < 5 + LOOP_UNROLLING(int, yk, 0, 1, _IWEI_HEIGHT, +#else // _IWEI_HEIGHT <= 5 + for(int yk = 0; yk < _IWEI_HEIGHT; ++yk) +#endif // _IWEI_HEIGHT <= 5 + { + TILE(SRC_DATA_TYPE, _IM0_A, _IN0_A, a); + + LOOP_UNROLLING(int, i, 0, 1, _IM0_A, + { + a[i].v = 0; + }) + + // Load tile from the src tensor (TILE A) + T_LOAD_NHWC_WITH_DILATION(SRC_DATA_TYPE, 1, _IM0_A, _IN0_A, SRC_TENSOR_TYPE, src, bout, yi + yk * DILATION_Y, xi, (cout / DEPTH_MULTIPLIER), SRC_WIDTH, SRC_HEIGHT, DILATION_X, 1, _IBOUNDARY_CHECK, a); + + TILE(WEI_DATA_TYPE, _IM0_B, _IN0_B, b); + + // Load tile from the weights tensor (TILE B) + T_LOAD(WEI_DATA_TYPE, _IM0_B, _IN0_B, WEI_TENSOR_TYPE, wei, cout, yk * _IM0_B, 1, wei_stride_y, b); + + // Optimized path for STRIDE_X == 1 + // If M0 != 1, we can skip the common loads between the two applied kernels on the X (WIDTH) dimension + LOOP_UNROLLING(int, m0, 0, 1, M0, + { + LOOP_UNROLLING(int, xk, 0, 1, _IWEI_WIDTH, + { +#if GPU_ARCH == GPU_ARCH_MIDGARD + c[m0].v += a[xk + m0].v * b[xk].v; +#else // GPU_ARCH == GPU_ARCH_MIDGARD + c[m0].v = fma(a[xk + m0].v, b[xk].v, c[m0].v); +#endif // GPU_ARCH == GPU_ARCH_MIDGARD + }) + }) + } +#if _IWEI_HEIGHT < 5 + ) +#endif // _IWEI_HEIGHT <= 5 + +#if defined(HAS_BIAS) + TILE(BIA_DATA_TYPE, 1, N0, bias0); + + T_LOAD(BIA_DATA_TYPE, 1, N0, BUFFER, bia, cout, 0, 0, 0, bias0); + + // c = c + bias[broadcasted] + T_ELTWISE_BROADCAST_ADD_X(ACC_DATA_TYPE, M0, N0, c, bias0, c); +#endif // HAS_BIAS + + T_ACTIVATION(ACC_DATA_TYPE, M0, N0, ACTIVATION_TYPE, A_VAL, B_VAL, c, c); + + TILE(uint, M0, 1, dst_indirect_y); + + bool x_cond = PARTIAL_N0 != 0 && get_global_id(0) == 0; + + if(x_cond) + { + LOOP_UNROLLING(int, m0, 0, 1, M0, + { + int xi_out = min(xo + M0 - 1 - m0, (int)(DST_WIDTH) - 1); + VSTORE_PARTIAL(N0, PARTIAL_N0) + (c[M0 - 1 - m0].v, 0, (__global DST_DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + cout * sizeof(DST_DATA_TYPE) + (uint)xi_out * dst_stride_y + (uint)yo * dst_stride_z + (uint)bout * dst_stride_w)); + }) + } + else + { + LOOP_UNROLLING(int, m0, 0, 1, M0, + { + int xi_out = min(xo + M0 - 1 - m0, (int)(DST_WIDTH) - 1); + VSTORE(N0) + (c[M0 - 1 - m0].v, 0, (__global DST_DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + cout * sizeof(DST_DATA_TYPE) + (uint)xi_out * dst_stride_y + (uint)yo * dst_stride_z + (uint)bout * dst_stride_w)); + }) + } +} +#endif // defined(WEI_WIDTH) && defined(WEI_HEIGHT) && defined(N0) && defined(M0) && defined(DILATION_X) && defined(DILATION_Y) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(PAD_LEFT) && defined(PAD_TOP) +// *INDENT-ON* +// clang-format on |