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Diffstat (limited to 'src/core/CL/cl_kernels/nhwc/direct_convolution3d.cl')
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1 files changed, 281 insertions, 0 deletions
diff --git a/src/core/CL/cl_kernels/nhwc/direct_convolution3d.cl b/src/core/CL/cl_kernels/nhwc/direct_convolution3d.cl new file mode 100644 index 0000000000..807b990e82 --- /dev/null +++ b/src/core/CL/cl_kernels/nhwc/direct_convolution3d.cl @@ -0,0 +1,281 @@ +/* + * Copyright (c) 2021-2022 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 "helpers.h" +#include "tile_helpers.h" + +//! @cond Doxygen_Suppress +/** OpenCL kernel to compute the direct convolution 3d. + * + * @note Data layout supported: NDHWC + * @note Data type supported: F32/F16/QASYMM8/QASYMM8_SIGNED + * @note The accumulation data type must be passed at compile time using -DDATA_TYPE (e.g. -DDATA_TYPE_PROMOTED=half) + * @note The convolution padding (left, top and front) must be passed at compile time using -DPAD_LEFT, -DPAD_TOP and -DPAD_FRONT (e.g. -DPAD_LEFT=2, -DPAD_TOP=2, -DPAD_FRONT=2) + * @note The convolution strides must be passed at compile time using -DSTRIDE_X, -DSTRIDE_Y and -DSTRIDE_Z (e.g. -DSTRIDE_X=2, -DSTRIDE_Y=2, -DSTRIDE_Z=2) + * @note The spatial dimensions of the weights must be passed at compile time using -DWEI_WIDTH, -DWEI_HEIGHT and -DWEI_DEPTH (e.g. -DWEI_WIDTH=9, -DWEI_HEIGHT=9, -DWEI_DEPTH=9) + * @note The spatial dimensions of the source tensor must be passed at compile time using -DSRC_WIDTH, -DSRC_HEIGHT and -DSRC_DEPTH (e.g. -DSRC_WIDTH=96, -DSRC_HEIGHT=64, -DSRC_DEPTH=32) + * @note The spatial dimensions of the destination tensor must be passed at compile time using -DDST_WIDTH, -DDST_HEIGHT and -DDST_DEPTH (e.g. -DDST_WIDTH=96, -DDST_HEIGHT=64, -DDST_DEPTH=32) + * @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. -DDST_CHANNELS=64) + * @note The data type must be passed at compile time using -DDATA_TYPE (e.g. -DDATA_TYPE=half) + * @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, .... n + * - N0 = 2, 3, 4, 8, 16 + * - K0 = 2, 3, 4, 8, 16 + * + * @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 + * + * @note If biases are used then -DHAS_BIAS has to be passed at compile time along with its tensor type by using -DBIA_DATA_TYPE (e.g. -DBIA_DATA_TYPE=int). + * + * @param[in] src_ptr Pointer to the source tensor. Supported data type: F16/F32 + * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes) + * @param[in] src_step_w src_stride_w * number of elements along W processed per workitem(in bytes) + * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[out] dst_ptr Pointer to the destination tensor. Supported data type: same as @p src_ptr + * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) + * @param[in] dst_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes) + * @param[in] dst_step_w dst_stride_w * number of elements along W processed per workitem(in bytes) + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor + * @param[in] wei_ptr Pointer to the weights tensor. Supported data type: same as @p src_ptr + * @param[in] wei_stride_x Stride of the weights tensor in X dimension (in bytes) + * @param[in] wei_step_x wei_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] wei_stride_y Stride of the weights tensor in Y dimension (in bytes) + * @param[in] wei_step_y wei_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] wei_stride_z Stride of the weights tensor in Z dimension (in bytes) + * @param[in] wei_step_z wei_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] wei_stride_w Stride of the weights tensor in W dimension (in bytes) + * @param[in] wei_step_w wei_stride_w * number of elements along W processed per workitem(in bytes) + * @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 + * @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_convolution3d_ndhwc( + TENSOR4D(src, BUFFER), + TENSOR4D(dst, BUFFER), + TENSOR4D(wei, BUFFER) +#if defined(HAS_BIAS) + , + VECTOR_DECLARATION(bia) +#endif // defined(HAS_BIAS) +) +{ +#define _IWEI_WIDTH WEI_WIDTH +#define _IWEI_HEIGHT WEI_HEIGHT +#define _IWEI_DEPTH WEI_DEPTH +#define _ISRC_WIDTH SRC_WIDTH +#define _ISRC_HEIGHT SRC_HEIGHT +#define _ISRC_DEPTH SRC_DEPTH +#define _ISRC_CHANNELS SRC_CHANNELS +#define _IDST_WIDTH DST_WIDTH +#define _IDST_HEIGHT DST_HEIGHT +#define _IDST_DEPTH DST_DEPTH +#define _IDST_CHANNELS DST_CHANNELS +#define _IY_MULTIPLIER (_IWEI_WIDTH * _IWEI_HEIGHT * _IWEI_DEPTH) + + // 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 x DEPTH + const int bout = GET_SPATIAL_IDX(2, 1, 0); // BATCH SIZE IDX + + TILE(int, M0, 1, xi); + TILE(int, M0, 1, yi); + TILE(int, M0, 1, zi); + + // Convert the linear index to coordinate + LOOP_UNROLLING(int, i, 0, 1, M0, + { + xi[i].v = ((mout + i) % _IDST_WIDTH) * STRIDE_X; + yi[i].v = (((mout + i) / _IDST_WIDTH) % _IDST_HEIGHT) * STRIDE_Y; + zi[i].v = (((mout + i) / (_IDST_WIDTH * _IDST_HEIGHT)) % _IDST_DEPTH) * STRIDE_Z; + + xi[i].v -= PAD_LEFT; + yi[i].v -= PAD_TOP; + zi[i].v -= PAD_FRONT; + }) + + // Initialize the accumulators + TILE(ACC_DATA_TYPE, M0, N0, c); + + LOOP_UNROLLING(int, i, 0, 1, M0, + { + c[i].v = (ACC_DATA_TYPE)0; + }) + + for(int i = 0; i < _IY_MULTIPLIER; ++i) + { + int ck = 0; + int xk = i % _IWEI_WIDTH; + int yk = (i / _IWEI_WIDTH) % _IWEI_HEIGHT; + int zk = i / (_IWEI_WIDTH * _IWEI_HEIGHT); + + int k = 0; + for(; k <= (_ISRC_CHANNELS - K0); k += K0) + { + TILE(DATA_TYPE, M0, K0, a); + TILE(DATA_TYPE, N0, K0, b); + + LOOP_UNROLLING(int, i, 0, 1, M0, + { + a[i].v = ZERO_VALUE; + }) + + // Load tile from the src tensor + T_LOAD_NDHWC_INDIRECT(DATA_TYPE, M0, K0, BUFFER, src, bout, zk, yk, xk, ck, _ISRC_WIDTH, _ISRC_HEIGHT, _ISRC_DEPTH, src_stride_y, xi, yi, zi, a); + + // Load tile from the weights tensor + const int b_offs = k + (xk * _ISRC_CHANNELS) + (yk * _ISRC_CHANNELS * _IWEI_WIDTH) + (zk * _ISRC_CHANNELS * _IWEI_WIDTH * _IWEI_HEIGHT); + LOOP_UNROLLING(int, i, 0, 1, N0, + { + if((cout + i) < _IDST_CHANNELS) + { + LOOP_UNROLLING(int, j, 0, 1, K0, + { + b[i].s[j] = *(__global DATA_TYPE *)(wei_ptr + wei_offset_first_element_in_bytes + (cout + i) * sizeof(DATA_TYPE) + j * wei_stride_y + b_offs * wei_stride_y); + }) + } + }) + + // Compute the matrix multiplication between two tiles + T_MMUL(DATA_TYPE, 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); + + ck += K0; + } + +#if((_ISRC_CHANNELS % K0) != 0) + // Left-over accumulations + for(; k < _ISRC_CHANNELS; ++k) + { + TILE(DATA_TYPE, M0, 1, a); + TILE(DATA_TYPE, N0, 1, b); + + LOOP_UNROLLING(int, i, 0, 1, M0, + { + a[i].v = ZERO_VALUE; + }) + + // Load tile from the src tensor + T_LOAD_NDHWC_INDIRECT(DATA_TYPE, M0, 1, BUFFER, src, bout, zk, yk, xk, ck, _ISRC_WIDTH, _ISRC_HEIGHT, _ISRC_DEPTH, src_stride_y, xi, yi, zi, a); + + // Load tile from the weights tensor + const int b_offs = k + (xk * _ISRC_CHANNELS) + (yk * _ISRC_CHANNELS * _IWEI_WIDTH) + (zk * _ISRC_CHANNELS * _IWEI_WIDTH * _IWEI_HEIGHT); + LOOP_UNROLLING(int, i, 0, 1, N0, + { + if((cout + i) < _IDST_CHANNELS) + { + b[i].v = *(__global DATA_TYPE *)(wei_ptr + wei_offset_first_element_in_bytes + (cout + i) * sizeof(DATA_TYPE) + b_offs * wei_stride_y); + } + }) + + // // Compute the matrix multiplication between two tiles + T_MMUL(DATA_TYPE, 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); + + ++ck; + } +#endif // ((_ISRC_CHANNELS % K0) != 0) + } + + // 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 * _IWEI_DEPTH * _ISRC_CHANNELS * SRC_OFFSET * WEI_OFFSET), c); + +#if defined(HAS_BIAS) + TILE(BIA_DATA_TYPE, 1, N0, bias0); + + if((cout + N0) <= _IDST_CHANNELS) + { + bias0[0].v = VLOAD(N0)(0, (__global BIA_DATA_TYPE *)(bia_ptr + bia_offset_first_element_in_bytes + cout * sizeof(BIA_DATA_TYPE))); + } + else + { + VLOAD_PARTIAL(N0, PARTIAL_N0) + (bias0[0].v, 0, (__global BIA_DATA_TYPE *)(bia_ptr + bia_offset_first_element_in_bytes + cout * sizeof(BIA_DATA_TYPE))); + } + + // c = c + bias[broadcasted] + T_ELTWISE_BROADCAST_ADD_X(ACC_DATA_TYPE, M0, N0, c, bias0, c); + +#endif // HAS_BIAS + + 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 * _IDST_DEPTH) - 1); + dst_indirect_y[i].v += bout * (int)(_IDST_WIDTH *_IDST_HEIGHT * _IDST_DEPTH); + }) + +#if defined(IS_QUANTIZED) + TILE(DATA_TYPE, M0, N0, cq); + + // Quantize the tile + T_QUANTIZE8_ASYMMETRIC(ACC_DATA_TYPE, DATA_TYPE, M0, N0, DST_OFFSET, DST_SHIFT, DST_MULTIPLIER, c, cq); +#endif // defined(IS_QUANTIZED) + + bool x_cond = PARTIAL_N0 != 0 && get_global_id(0) == 0; + + // Store the tile in reverse order so the invalid values are overwritten with the valid ones + T_STORE_INDIRECT_WIDTH_SELECT(DATA_TYPE, M0, N0, PARTIAL_N0, BUFFER, dst, cout, dst_stride_y, x_cond, _IOUTPUT_TILE, dst_indirect_y); +}
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