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Diffstat (limited to 'src/core/CL/cl_kernels/nhwc/direct_convolution.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/nhwc/direct_convolution.cl | 295 |
1 files changed, 295 insertions, 0 deletions
diff --git a/src/core/CL/cl_kernels/nhwc/direct_convolution.cl b/src/core/CL/cl_kernels/nhwc/direct_convolution.cl new file mode 100644 index 0000000000..81ceeb8846 --- /dev/null +++ b/src/core/CL/cl_kernels/nhwc/direct_convolution.cl @@ -0,0 +1,295 @@ +/* + * 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 "helpers_asymm.h" +#include "tile_helpers.h" + +//! @cond Doxygen_Suppress +/** OpenCL kernel to compute the direct convolution. + * + * @note Data layout supported: NHWC + * @note Data type supported: F32/F16/QASYMM8/QASYMM8_SIGNED + * @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 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 spatial dimensions of the source tensor must be passed at compile time using -DSRC_WIDTH and -DSRC_HEIGHT (e.g. -DSRC_WIDTH=96, -DSRC_HEIGHT=64) + * @note The spatial dimensions of the destination tensor must be passed at compile time using -DDST_WIDTH and -DDST_HEIGHT (e.g. -DDST_WIDTH=96, -DDST_HEIGHT=64) + * @note The channels of the source tensor must be passed at compile time using -DSRC_CHANNELS (e.g. -DSRC_CHANNELS=64) + * @note The channels of the destination tensor must be passed at compile time using -DDST_CHANNELS (e.g. -DDDST_CHANNELS=64) + * @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*height) 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 number of K0 inner accumulations must be passed at compile time using -DK0 (e.g. -DK0=2) + * @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_N0 (e.g. -DPARTIAL_N0=1) + * @note The zero value must be passed at compile time using -DZERO_VALUE (e.g. -DZERO_VALUE=0) + * @note Only the following configurations of M0, N0 and K0 are currently supported: + * - M0 = 1, 2, 3, 4, 5, 6, 7, and 8 + * - N0 = 2, 3, 4, 8, 16 + * - K0 = 2, 3, 4, 8, 16 (only 4, 8 and 16 if WEI_TENSOR_TYPE=IMAGE) + * + *@note In case of QASYMM8/QASYMM8_SIGNED, the following extra information must be passed at compile time: + * - -DIS_QUANTIZED + * - The destination quantization multiplier e.g. -DDST_MULTIPLIER=1234 + * - The destination quantization shift e.g. -DDST_SHIFT=4 + * - The destination offset e.g. -DDST_OFFSET=4 + * - The source offset e.g. -DSRC_OFFSET=4 + * - The weights offset e.g. -DWEI_OFFSET=4 + * - The quantized zero value e.g. -DZERO_VALUE=4 + * + * @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/QASYMM8 + * @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 weights matrix + * @param[in] bia_ptr (Optional) Pointer to the bias tensor Supported data type: same as @p src_ptr (if F32/F16) or S32 (if QASYMM8/QASYMM8_SIGNED) + * @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 direct_convolution_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) +) +{ + // All the 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 _ISRC_WIDTH SRC_WIDTH +#define _ISRC_HEIGHT SRC_HEIGHT +#define _ISRC_CHANNELS SRC_CHANNELS +#define _IDST_WIDTH DST_WIDTH +#define _IDST_HEIGHT DST_HEIGHT +#define _IDST_CHANNELS DST_CHANNELS +#define _IY_MULTIPLIER (_IWEI_WIDTH * _IWEI_HEIGHT) + + // If quantized, the output tile has to be quantized first before being stored to global memory +#if defined(IS_QUANTIZED) +#define _IOUTPUT_TILE cq +#else // defined(IS_QUANTIZED) +#define _IOUTPUT_TILE c +#endif // defined(IS_QUANTIZED) + + const int cout = GET_SPATIAL_IDX(0, N0, PARTIAL_N0); // OFM + const int mout = GET_SPATIAL_IDX(1, M0, 0); // WIDTH x HEIGHT + const int bout = GET_SPATIAL_IDX(2, 1, 0); // BATCH SIZE IDX + + // .v = access the whole vector (OpenCL vector) + // .s[x] = access the vector element at position x (scalar access) + TILE(int, 1, M0, xi); + TILE(int, 1, M0, yi); + + // Convert the linear index to coordinate + LOOP_UNROLLING(int, i, 0, 1, M0, + { + xi[0].s[i] = ((mout + i) % _IDST_WIDTH) * STRIDE_X; + yi[0].s[i] = ((mout + i) / _IDST_WIDTH) * STRIDE_Y; + xi[0].s[i] -= PAD_LEFT; + yi[0].s[i] -= PAD_TOP; + }) + + // Initialize the accumulators + TILE(ACC_DATA_TYPE, M0, N0, c); + + LOOP_UNROLLING(int, i, 0, 1, M0, + { + c[i].v = 0; + }) + + for(int i = 0; i < (_IWEI_WIDTH * _IWEI_HEIGHT); ++i) + { + int xk = i % _IWEI_WIDTH; + int yk = i / _IWEI_WIDTH; + + TILE(int, 1, M0, my); + + LOOP_UNROLLING(int, i, 0, 1, M0, + { + int x_s = xi[0].s[i] + xk; + int y_s = yi[0].s[i] + yk; + my[0].s[i] = x_s + y_s *_ISRC_WIDTH; + my[0].s[i] = my[0].s[i] + bout * (int)(_ISRC_WIDTH * _ISRC_HEIGHT); + my[0].s[i] = select(-1, my[0].s[i], x_s >= 0); + my[0].s[i] = select(-1, my[0].s[i], x_s < _ISRC_WIDTH); + my[0].s[i] = select(-1, my[0].s[i], y_s >= 0); + my[0].s[i] = select(-1, my[0].s[i], y_s < _ISRC_HEIGHT); + }) + + int ck = 0; + for(; ck <= (_ISRC_CHANNELS - K0); ck += K0) + { + TILE(SRC_DATA_TYPE, M0, K0, a); + TILE(WEI_DATA_TYPE, N0, K0, b); + + // Initialize tiles + LOOP_UNROLLING(int, i, 0, 1, M0, + { + a[i].v = ZERO_VALUE; + }) + + LOOP_UNROLLING(int, i, 0, 1, N0, + { + b[i].v = ZERO_VALUE; + }) + + // Load tile from the src tensor + T_LOAD2D_INDIRECT(SRC_DATA_TYPE, M0, K0, SRC_TENSOR_TYPE, src, ck, src_stride_y, my, a); + + // Load tile from the weights tensor + T_LOAD(WEI_DATA_TYPE, N0, K0, WEI_TENSOR_TYPE, wei, ck, cout * _IY_MULTIPLIER + i, _IY_MULTIPLIER, wei_stride_y, b); + + // Compute the matrix multiplication between two tiles + T_MMUL(SRC_DATA_TYPE, WEI_DATA_TYPE, ACC_DATA_TYPE, M0, N0, K0, NT, T, a, b, c); + + // Apply the offset correction (correction usually needed for asymmetric quantized computation) + // The computation is not performed if both SRC_OFFSET and WEI_OFFSET are zero + T_OFFSET_CORRECTION(ACC_DATA_TYPE, M0, N0, K0, SRC_OFFSET, WEI_OFFSET, a, b, c); + } + + // This #if directive should be removed in case of dynamic tensor support +#if defined(LEFTOVER_LOOP) + // Left-over accumulations + for(; ck < _ISRC_CHANNELS; ++ck) + { + TILE(SRC_DATA_TYPE, M0, 1, a); + TILE(WEI_DATA_TYPE, N0, 1, b); + + // Initialize tiles + LOOP_UNROLLING(int, i, 0, 1, M0, + { + a[i].v = ZERO_VALUE; + }) + + LOOP_UNROLLING(int, i, 0, 1, N0, + { + b[i].v = ZERO_VALUE; + }) + + // Load tile from the src tensor + T_LOAD2D_INDIRECT(SRC_DATA_TYPE, M0, 1, SRC_TENSOR_TYPE, src, ck, src_stride_y, my, a); + + // Load tile from the weights tensor + // The T_LOAD for the left-over elements can only use BUFFER because we load one element per iteration + T_LOAD(WEI_DATA_TYPE, N0, 1, BUFFER, wei, ck, cout * _IY_MULTIPLIER + i, _IY_MULTIPLIER, wei_stride_y, b); + + // Compute the matrix multiplication between two tiles + T_MMUL(SRC_DATA_TYPE, WEI_DATA_TYPE, ACC_DATA_TYPE, M0, N0, 1, NT, T, a, b, c); + + // Apply the offset correction (operation usually needed for asymmetric quantized computation) + // The computation is not performed if both SRC_OFFSET and WEI_OFFSET are zero + T_OFFSET_CORRECTION(ACC_DATA_TYPE, M0, N0, 1, SRC_OFFSET, WEI_OFFSET, a, b, c); + } +#endif // defined(LEFTOVER_LOOP) + } + + // Offset correction required for the quantized asymmetric computation + // The computation is not performed if both SRC_OFFSET and WEI_OFFSET are zero + T_ADD_CONSTANT(ACC_DATA_TYPE, M0, N0, c, (_IWEI_WIDTH * _IWEI_HEIGHT * _ISRC_CHANNELS * SRC_OFFSET * WEI_OFFSET), c); + +#if defined(HAS_BIAS) + TILE(BIA_DATA_TYPE, 1, N0, bias0); + + T_LOAD(BIA_DATA_TYPE, 1, N0, BUFFER, bia, cout, 0, 1, 0, bias0); + + // c = c + bias[broadcasted] + T_ELTWISE_BROADCAST_ADD_X(ACC_DATA_TYPE, M0, N0, c, bias0, c); + +#endif // HAS_BIAS + +#if defined(IS_QUANTIZED) + + TILE(DST_DATA_TYPE, M0, N0, cq); + + // Quantize the tile + T_QUANTIZE8_ASYMMETRIC(ACC_DATA_TYPE, DST_DATA_TYPE, M0, N0, DST_OFFSET, DST_SHIFT, DST_MULTIPLIER, c, cq); +#endif // defined(IS_QUANTIZED) + + // Apply activation + T_ACTIVATION(DST_DATA_TYPE, M0, N0, ACTIVATION_TYPE, A_VAL, B_VAL, _IOUTPUT_TILE, _IOUTPUT_TILE); + + TILE(uint, M0, 1, dst_indirect_y); + + // Calculate the destination indirect Y + LOOP_UNROLLING(int, i, 0, 1, M0, + { + dst_indirect_y[i].v = (uint)min(mout + i, (int)(_IDST_WIDTH * _IDST_HEIGHT) - 1); + dst_indirect_y[i].v += bout * (int)(_IDST_WIDTH * _IDST_HEIGHT); + }) + + bool x_cond = PARTIAL_N0 != 0 && get_global_id(0) == 0; + + // _IOUTPUT_TILE: c = fp32/fp16, cq=qasymm8 + // Store the tile in reverse order so the invalid values are overwritten with the valid ones + T_STORE_INDIRECT_WIDTH_SELECT(DST_DATA_TYPE, M0, N0, PARTIAL_N0, DST_TENSOR_TYPE, dst, cout, dst_stride_y, x_cond, _IOUTPUT_TILE, dst_indirect_y); + +#undef _IWEI_WIDTH +#undef _IWEI_HEIGHT +#undef _ISRC_WIDTH +#undef _ISRC_HEIGHT +#undef _ISRC_CHANNELS +#undef _IDST_WIDTH +#undef _IDST_HEIGHT +#undef _IDST_CHANNELS +#undef _IY_MULTIPLIER +} |