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author | SiCong Li <sicong.li@arm.com> | 2017-07-28 14:46:20 +0100 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-09-17 14:16:42 +0100 |
commit | c51b72fe34e6018a1807a2c78228da7beeee1750 (patch) | |
tree | e1c969d6a54ae2561f8d4c6c35fd2534785f09b3 /src/core/CL/cl_kernels/direct_convolution3x3.cl | |
parent | 572ade736ab344a62afa7da214cd9407fe53a281 (diff) | |
download | ComputeLibrary-c51b72fe34e6018a1807a2c78228da7beeee1750.tar.gz |
COMPMID-355 Implement CL DirectConvolution1x1
* Add FP16 to validation tests.
* Complete benchmark tests for CL and NEON Direct Convolution.
Change-Id: Ie73d8580832372db01b82b39786fd9c8be560090
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/82014
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Diffstat (limited to 'src/core/CL/cl_kernels/direct_convolution3x3.cl')
-rw-r--r-- | src/core/CL/cl_kernels/direct_convolution3x3.cl | 227 |
1 files changed, 227 insertions, 0 deletions
diff --git a/src/core/CL/cl_kernels/direct_convolution3x3.cl b/src/core/CL/cl_kernels/direct_convolution3x3.cl new file mode 100644 index 0000000000..b5524e1d4b --- /dev/null +++ b/src/core/CL/cl_kernels/direct_convolution3x3.cl @@ -0,0 +1,227 @@ +/* + * Copyright (c) 2016, 2017 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" + +#if STRIDE_X == 2 +#define CONVOLVE1x3(left_pixel_position, left_coeff, middle_coeff, right_coeff) convolution1x3_stride2(left_pixel_position, left_coeff, middle_coeff, right_coeff) +#elif STRIDE_X == 1 /* STRIDE_X == 1 */ +#define CONVOLVE1x3(left_pixel_position, left_coeff, middle_coeff, right_coeff) convolution1x3_stride1(left_pixel_position, left_coeff, middle_coeff, right_coeff) +#else /* STRIDE_X not equals 1 or 2 */ +#error "STRIDE_X larger than 2 is not supported" +#endif /* STRIDE_X == 2 */ + +/** Compute a 1D horizontal convolution of size 3 with stride as 1. + * + * @param[in] left_pixel Pointer to the left pixel. + * @param[in] left_coeff Weight of the left pixel + * @param[in] middle_coeff Weight of the middle pixel + * @param[in] right_coeff Weight of the right pixel + * + * @return a convoluted values. + */ +inline VEC_DATA_TYPE(DATA_TYPE, 8) convolution1x3_stride1(__global const DATA_TYPE *left_pixel, + const DATA_TYPE left_coeff, + const DATA_TYPE middle_coeff, + const DATA_TYPE right_coeff) +{ + VEC_DATA_TYPE(DATA_TYPE, 16) + temp = vload16(0, left_pixel); + + VEC_DATA_TYPE(DATA_TYPE, 8) + left = temp.s01234567; + VEC_DATA_TYPE(DATA_TYPE, 8) + middle = temp.s12345678; + VEC_DATA_TYPE(DATA_TYPE, 8) + right = temp.s23456789; + + return left * (VEC_DATA_TYPE(DATA_TYPE, 8))left_coeff + middle * (VEC_DATA_TYPE(DATA_TYPE, 8))middle_coeff + right * (VEC_DATA_TYPE(DATA_TYPE, 8))right_coeff; +} + +/** Compute a 1D horizontal convolution of size 3 with stride as 2. + * + * @param[in] left_pixel Pointer to the left pixel. + * @param[in] left_coeff Weight of the left pixel + * @param[in] middle_coeff Weight of the middle pixel + * @param[in] right_coeff Weight of the right pixel + * + * @return a convoluted values. + */ +inline VEC_DATA_TYPE(DATA_TYPE, 8) convolution1x3_stride2(__global const DATA_TYPE *left_pixel, + const DATA_TYPE left_coeff, + const DATA_TYPE middle_coeff, + const DATA_TYPE right_coeff) +{ + const int stride_size = 2; + + VEC_DATA_TYPE(DATA_TYPE, 16) + temp1 = vload16(0, left_pixel); + + VEC_DATA_TYPE(DATA_TYPE, 16) + temp2 = vload16(0, left_pixel + 8); + + VEC_DATA_TYPE(DATA_TYPE, 8) + left = (VEC_DATA_TYPE(DATA_TYPE, 8))(temp1.s0246, temp2.s0246); + + VEC_DATA_TYPE(DATA_TYPE, 8) + middle = (VEC_DATA_TYPE(DATA_TYPE, 8))(temp1.s1357, temp2.s1357); + + VEC_DATA_TYPE(DATA_TYPE, 8) + right = (VEC_DATA_TYPE(DATA_TYPE, 8))(temp1.s2468, temp2.s2468); + + return left * (VEC_DATA_TYPE(DATA_TYPE, 8))left_coeff + middle * (VEC_DATA_TYPE(DATA_TYPE, 8))middle_coeff + right * (VEC_DATA_TYPE(DATA_TYPE, 8))right_coeff; +} + +/** Apply a 3x3 2D convolution matrix on the input and return the result. + * + * Convolution matrix layout: + * + * [ mat0, mat1, mat2 ]\n + * [ mat3, mat4, mat5 ]\n + * [ mat6, mat7, mat8 ]\n + * + * @param[in] src A pointer to source Image structure + * @param[in] mat0 Coefficient from the convolution matrix + * @param[in] mat1 Coefficient from the convolution matrix + * @param[in] mat2 Coefficient from the convolution matrix + * @param[in] mat3 Coefficient from the convolution matrix + * @param[in] mat4 Coefficient from the convolution matrix + * @param[in] mat5 Coefficient from the convolution matrix + * @param[in] mat6 Coefficient from the convolution matrix + * @param[in] mat0 Coefficient from the convolution matrix + * @param[in] mat7 Coefficient from the convolution matrix + * @param[in] mat8 Coefficient from the convolution matrix + * + * @return convoluted values. + */ +inline VEC_DATA_TYPE(DATA_TYPE, 8) convolution3x3( + Image *src, + const DATA_TYPE mat0, const DATA_TYPE mat1, const DATA_TYPE mat2, + const DATA_TYPE mat3, const DATA_TYPE mat4, const DATA_TYPE mat5, + const DATA_TYPE mat6, const DATA_TYPE mat7, const DATA_TYPE mat8) +{ + // Output pixels + VEC_DATA_TYPE(DATA_TYPE, 8) + pixels; + + // Row 0 + pixels = CONVOLVE1x3((__global DATA_TYPE *)offset(src, 0, 0), mat0, mat1, mat2); + // Row + pixels += CONVOLVE1x3((__global DATA_TYPE *)offset(src, 0, 1), mat3, mat4, mat5); + // Row 2 + pixels += CONVOLVE1x3((__global DATA_TYPE *)offset(src, 0, 2), mat6, mat7, mat8); + + return pixels; +} + +/** This kernel performs a direct convolution to convolve the low three dimensions. + * + * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float + * @note The convolution stride x and stride y must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y: e.g. -DSTRIDE_X=1, _DSTRIDE_Y=1 + * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. + * + * @param[in] src_ptr Pointer to the source tensor. Supported data types: QS8/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_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 types: 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 Z 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_offset_first_element_in_bytes The offset of the first element in the destination tensor + * @param[out] weights_ptr Pointer to the weights tensor. Supported data types: same as @p weights_ptr + * @param[in] weights_stride_x Stride of the weights tensor in X dimension (in bytes) + * @param[in] weights_step_x weights_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] weights_stride_y Stride of the weights tensor in Y dimension (in bytes) + * @param[in] weights_step_y weights_stride_y * number of elements along y processed per workitem(in bytes) + * @param[in] weights_stride_z Stride of the weights tensor in Z dimension (in bytes) + * @param[in] weights_step_z weights_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] weights_offset_first_element_in_bytes The offset of the first element in the weights tensor + * @param[in] biases_ptr Pointer to the biases tensor. Same as @p src_ptr + * @param[in] biases_stride_x Stride of the biases tensor in X dimension (in bytes) + * @param[in] biases_step_x biases_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] biases_offset_first_element_in_bytes The offset of the first element in the biases tensor + * @param[in] weights_stride_w Stride of the weights tensor in W dimension + * @param[in] filter_depth The depth size of the filter + */ +__kernel void direct_convolution3x3( + TENSOR3D_DECLARATION(src), + TENSOR3D_DECLARATION(dst), + TENSOR3D_DECLARATION(weights), +#ifdef HAS_BIAS + VECTOR_DECLARATION(biases), +#endif /* defined(HAS_BIAS) */ + unsigned int weights_stride_w, + unsigned int filter_depth) +{ + Image src = CONVERT_TO_IMAGE_STRUCT(src); + Tensor3D weights = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(weights); + Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); + +#ifdef HAS_BIAS + Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases); +#endif /* defined(HAS_BIAS) */ + + VEC_DATA_TYPE(DATA_TYPE, 8) + pixels = 0; + + const uint z_index = get_global_id(2); + + weights.ptr += z_index * weights_stride_w; + + for(int d = 0; d < filter_depth; ++d) + { + VEC_DATA_TYPE(DATA_TYPE, 4) + weights_row1 = vload4(0, (__global DATA_TYPE *)tensor3D_offset(&weights, 0, 0, 0)); + VEC_DATA_TYPE(DATA_TYPE, 4) + weights_row2 = vload4(0, (__global DATA_TYPE *)tensor3D_offset(&weights, 0, 1, 0)); + VEC_DATA_TYPE(DATA_TYPE, 4) + weights_row3 = vload4(0, (__global DATA_TYPE *)tensor3D_offset(&weights, 0, 2, 0)); + + pixels += convolution3x3(&src, weights_row1.s0, + weights_row1.s1, + weights_row1.s2, + weights_row2.s0, + weights_row2.s1, + weights_row2.s2, + weights_row3.s0, + weights_row3.s1, + weights_row3.s2); + + src.ptr += src_stride_z; + weights.ptr += weights_stride_z; + } + +#ifdef HAS_BIAS + pixels += (VEC_DATA_TYPE(DATA_TYPE, 8)) * ((__global DATA_TYPE *)(vector_offset(&biases, z_index))); +#endif /* defined(HAS_BIAS) */ + + vstore8(pixels, 0, (__global DATA_TYPE *)dst.ptr); +} |