From 4b90865ab985d571f70c60583cdfb8c7a65f1670 Mon Sep 17 00:00:00 2001 From: Gian Marco Iodice Date: Thu, 18 Oct 2018 10:21:02 +0100 Subject: COMPMID-1413 - Improve the performance of GEMMLowp with 8 bit dot product on OpenCL COMPMID-1424 - Add dot product support for CLDepthwise QASYMM8 3x3 NHWC non-unit stride With this patch we are able to improve the performance of MobileNet v1-qasymm8 by 37 % Tried to use the dot product instruction in CLDepthwise QASYMM8 3x3 NHWC non-unit stride but I have not seen any benefit (maybe because we have few arithemtic operation and we do not have more load instructions). However Depthwise convolution has been improved by 30% Change-Id: Id768a99c2e53a04276707e427af5d0ec93419ada Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/155082 Tested-by: bsgcomp Reviewed-by: Georgios Pinitas --- .../runtime/CL/functions/CLGEMMConvolutionLayer.h | 51 +++++++++++--------- .../CL/functions/CLGEMMLowpMatrixMultiplyCore.h | 54 +++++++++++++--------- .../runtime/CL/functions/CLGEMMLowpOutputStage.h | 18 ++++---- 3 files changed, 67 insertions(+), 56 deletions(-) (limited to 'arm_compute/runtime/CL') diff --git a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h index 48b880174d..fbf0c08b36 100644 --- a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h +++ b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h @@ -157,43 +157,48 @@ public: private: /** Configures the appropriate matrix multiply routine * - * @param[in] input Input tensor. Data types supported: QASYMM8/F16/F32. - * @param[in] weights Weights tensor. Data type supported: Same as @p input. - * @param[in, out] output Output tensor. Data types supported: Same as @p input, - * except for input of QASYMM8 type where output should be of S32 type. - * @param[in] gemm_3d_depth (Optional) Depth of GEMM 3D (Defaults to 1) + * @param[in] input Input tensor. Data types supported: QASYMM8/F16/F32. + * @param[in] weights Weights tensor. Data type supported: Same as @p input. + * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. + * Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type. + * @param[in, out] output Output tensor. Data types supported: Same as @p input, + * except for input of QASYMM8 type where output should be of S32 type. + * @param[in] gemmlowp_output_stage GEMMLowp output stage info + * @param[in] gemm_3d_depth (Optional) Depth of GEMM 3D (Defaults to 1) */ - void configure_mm(const ICLTensor *input, const ICLTensor *weights, ICLTensor *output, int gemm_3d_depth = 1); + void configure_mm(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const GEMMLowpOutputStageInfo &gemmlowp_output_stage, int gemm_3d_depth = 1); /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMConvolutionLayer matrix multiply routines * - * @param[in] input Input tensor. Data types supported: QASYMM8/F16/F32. - * @param[in] weights Weights tensor. Data type supported: Same as @p input. - * @param[in] output Output tensor. Data types supported: Same as @p input, - * except for input of QASYMM8 type where output should be of S32 type. - * @param[in] gemm_3d_depth (Optional) Depth of GEMM 3D (Defaults to 1) - * @param[in] skip_im2col (Optional) Flag which specifies if im2col has to be skipped. i.e. 1x1 convolution with NHWC data layout. (Default to false) + * @param[in] input Input tensor. Data types supported: QASYMM8/F16/F32. + * @param[in] weights Weights tensor. Data type supported: Same as @p input. + * @param[in] output Output tensor. Data types supported: Same as @p input, + * except for input of QASYMM8 type where output should be of S32 type. + * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. + * Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type. + * @param[in] gemmlowp_output_stage GEMMLowp output stage info + * @param[in] gemm_3d_depth (Optional) Depth of GEMM 3D (Defaults to 1) + * @param[in] skip_im2col (Optional) Flag which specifies if im2col has to be skipped. i.e. 1x1 convolution with NHWC data layout. (Default to false) * * @return a status */ - static Status validate_mm(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *output, int gemm_3d_depth = 1, bool skip_im2col = false); + static Status validate_mm(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const GEMMLowpOutputStageInfo &gemmlowp_output_stage, + int gemm_3d_depth = 1, bool skip_im2col = false); private: - CLMemoryGroup _memory_group; - CLConvolutionLayerReshapeWeights _reshape_weights; - CLIm2ColKernel _im2col_kernel; - CLGEMM _mm_gemm; - CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp; - CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFloat _gemmlowp_output_stage; - CLCol2ImKernel _col2im_kernel; - CLActivationLayer _activationlayer_function; - CLArithmeticAdditionKernel _add_bias_kernel; + CLMemoryGroup _memory_group; + CLConvolutionLayerReshapeWeights _reshape_weights; + CLIm2ColKernel _im2col_kernel; + CLGEMM _mm_gemm; + CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp; + CLCol2ImKernel _col2im_kernel; + CLActivationLayer _activationlayer_function; + CLArithmeticAdditionKernel _add_bias_kernel; const ICLTensor *_original_weights; CLTensor _im2col_output; CLTensor _weights_reshaped; CLTensor _gemm_output; - CLTensor _tmp_output; DataLayout _data_layout; diff --git a/arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h b/arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h index f404ccdf4c..82f307a773 100644 --- a/arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h +++ b/arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h @@ -27,6 +27,7 @@ #include "arm_compute/core/CL/kernels/CLGEMMInterleave4x4Kernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.h" +#include "arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionOutputStageKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpReductionKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMTranspose1xWKernel.h" #include "arm_compute/runtime/CL/CLMemoryGroup.h" @@ -45,7 +46,8 @@ class ICLTensor; * -# @ref CLGEMMLowpMatrixMultiplyKernel * -# @ref CLGEMMLowpMatrixAReductionKernel (if the offset of matrix B is not 0) * -# @ref CLGEMMLowpMatrixBReductionKernel (if the offset of matrix A is not 0) - * -# @ref CLGEMMLowpOffsetContributionKernel + * -# @ref CLGEMMLowpOffsetContributionKernel (if gemm_info.gemmlowp_output_stage == NONE) + * -# @ref CLGEMMLowpOffsetContributionOutputStageKernel (if gemm_info.gemmlowp_output_stage != NONE) * */ class CLGEMMLowpMatrixMultiplyCore : public IFunction @@ -63,54 +65,60 @@ public: CLGEMMLowpMatrixMultiplyCore &operator=(CLGEMMLowpMatrixMultiplyCore &&) = default; /** Initialise the kernel's inputs, output * - * @note GEMM_LOWP: low precision GEMM kernel + * @note GEMMLowp: low precision GEMM kernel. [A * B + C] * This kernel performs the following computations: * * -# Convert a values from QASYMM8 to int32 and add a_offset to each of them. * -# Convert b values from QASYMM8 to int32 add b_offset to each of them. * -# Compute the matrix product of the resulting a * b in int32. + * -# Quantize to uint8 if gemm_info.gemmlowp_output_stage != NONE * * @param[in] a First input tensor (Matrix A). Data type supported: QASYMM8. * @param[in] b Second input tensor (Matrix B). Data type supported: same as @p a - * @param[out] output Output tensor. Data type supported: Data type supported: S32 + * @param[in] c Third input tensor (Matrix C). It can be a nullptr. Data type supported: S32 + * @param[out] output Output tensor. Data type supported: S32 or QASYMM8 if gemm_info.gemmlowp_output_stage != NONE * @param[in] gemm_info (Optional) Specifies if the matrix A and/or matrix B have been reshaped and * if the reshape of matrix B should be executed only for the first run */ - void configure(const ICLTensor *a, const ICLTensor *b, ICLTensor *output, const GEMMInfo &gemm_info = GEMMInfo()); + void configure(const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, const GEMMInfo &gemm_info = GEMMInfo()); /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpMatrixMultiplyCore * * @param[in] a First input tensor (Matrix A). Data type supported: QASYMM8. * @param[in] b Second input tensor (Matrix B). Data type supported: same as @p a - * @param[in] output Output tensor. Data type supported: Data type supported: S32 + * @param[in] c Third input tensor (Matrix C). It can be a nullptr. Data type supported: S32 + * @param[in] output Output tensor. Data type supported: S32 or QASYMM8 if gemm_info.gemmlowp_output_stage != NONE * @param[in] gemm_info (Optional) Specifies if the matrix A and/or matrix B have been reshaped and * if the reshape of matrix B should be executed only for the first run * * @return a status */ - static Status validate(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *output, const GEMMInfo &gemm_info = GEMMInfo()); + static Status validate(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, const GEMMInfo &gemm_info = GEMMInfo()); // Inherited methods overridden: void run() override; void prepare() override; private: - CLMemoryGroup _memory_group; - CLGEMMLowpMatrixMultiplyKernel _mm_kernel; - CLGEMMInterleave4x4Kernel _mtx_a_reshape_kernel; - CLGEMMTranspose1xWKernel _mtx_b_reshape_kernel; - CLGEMMLowpMatrixAReductionKernel _mtx_a_reduction_kernel; - CLGEMMLowpMatrixBReductionKernel _mtx_b_reduction_kernel; - CLGEMMLowpOffsetContributionKernel _offset_contribution_kernel; - CLTensor _vector_sum_col; - CLTensor _vector_sum_row; - CLTensor _tmp_a; - CLTensor _tmp_b; - const ICLTensor *_original_b; - int32_t _a_offset; - int32_t _b_offset; - bool _is_interleaved_transposed; - bool _reshape_b_only_on_first_run; - bool _is_prepared; + CLMemoryGroup _memory_group; + CLGEMMLowpMatrixMultiplyKernel _mm_kernel; + CLGEMMInterleave4x4Kernel _mtx_a_reshape_kernel; + CLGEMMTranspose1xWKernel _mtx_b_reshape_kernel; + CLGEMMLowpMatrixAReductionKernel _mtx_a_reduction_kernel; + CLGEMMLowpMatrixBReductionKernel _mtx_b_reduction_kernel; + CLGEMMLowpOffsetContributionKernel _offset_contribution_kernel; + CLGEMMLowpOffsetContributionOutputStageKernel _offset_contribution_output_stage_kernel; + CLTensor _vector_sum_col; + CLTensor _vector_sum_row; + CLTensor _tmp_a; + CLTensor _tmp_b; + CLTensor _mm_result_s32; + const ICLTensor *_original_b; + int32_t _a_offset; + int32_t _b_offset; + bool _is_interleaved_transposed; + bool _reshape_b_only_on_first_run; + bool _is_prepared; + bool _fuse_output_stage; }; } #endif /*__ARM_COMPUTE_CLGEMMLOWPMATRIXMULTIPLYCORE_H__ */ diff --git a/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h b/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h index 51fcbe9392..3330b40d8a 100644 --- a/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h +++ b/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h @@ -131,24 +131,22 @@ public: * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8 * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8, * Along with @p min, this value can be used to implement "rectified linear unit" activation functions - * @param[in] output_3d_depth (Optional) Depth of output in 3D (Defaults to 1) */ void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift, - int min = 0, int max = 0, unsigned int output_3d_depth = 1); + int min = 0, int max = 0); /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint * - * @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32 - * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required. - * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. - * @param[in] output Output tensor. Data type supported: Data type supported: QASYMM8 - * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8 - * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8, + * @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32 + * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required. + * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. + * @param[in] output Output tensor. Data type supported: Data type supported: QASYMM8 + * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8 + * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8, * Along with @p min, this value can be used to implement "rectified linear unit" activation functions - * @param[in] output_3d_depth (Optional) Depth of output in 3D (Defaults to 1) * * @return a status */ - static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = 0, int max = 0, unsigned int output_3d_depth = 1); + static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = 0, int max = 0); }; /** Basic function to execute CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFloat on OpenCL. -- cgit v1.2.1