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[compute/cker] Optimize BatchMatMul for x86 (#14305)
This commit adds an optimized version of the BatchMatMul kernel. The optimization targets the x86 architecture, in all other cases the code is compiled with existing reference kernel. The new kernel calls the optimized::Gemm function which uses Eigen internally. Additionally to avoid code duplication a new BatchMatMulParams struct is introduced and reused in both reference and optimized kernels. ONE-DCO-1.0-Signed-off-by: Tomasz Dolbniak <[email protected]>
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compute/cker/include/cker/operation/Helper/BatchMatMulParams.h
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,98 @@ | ||
| /* | ||
| * Copyright (c) 2024 Samsung Electronics Co., Ltd. All Rights Reserved | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); | ||
| * you may not use this file except in compliance with the License. | ||
| * You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
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| #ifndef __NNFW_CKER_HELPER_BATCH_MAT_MUL_PARAMS_H__ | ||
| #define __NNFW_CKER_HELPER_BATCH_MAT_MUL_PARAMS_H__ | ||
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| #include "cker/Shape.h" | ||
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| namespace nnfw | ||
| { | ||
| namespace cker | ||
| { | ||
| struct BatchMatMulParams | ||
| { | ||
| BatchMatMulParams(const Shape &lhs_shape, const Shape &rhs_shape) | ||
| { | ||
| const Shape extended_lhs_shape = Shape::ExtendedShape(5, lhs_shape); | ||
| const Shape extended_rhs_shape = Shape::ExtendedShape(5, rhs_shape); | ||
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| batch_dim0 = broadcast_dim(extended_lhs_shape.Dims(0), extended_rhs_shape.Dims(0)); | ||
| batch_dim1 = broadcast_dim(extended_lhs_shape.Dims(1), extended_rhs_shape.Dims(1)); | ||
| batch_dim2 = broadcast_dim(extended_lhs_shape.Dims(2), extended_rhs_shape.Dims(2)); | ||
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| lhs_ext0 = extent(extended_lhs_shape, 0); | ||
| lhs_ext1 = extent(extended_lhs_shape, 1); | ||
| lhs_ext2 = extent(extended_lhs_shape, 2); | ||
| rhs_ext0 = extent(extended_rhs_shape, 0); | ||
| rhs_ext1 = extent(extended_rhs_shape, 1); | ||
| rhs_ext2 = extent(extended_rhs_shape, 2); | ||
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| // Set params for each matrix multiply. | ||
| lhs_rows = extended_lhs_shape.Dims(3); | ||
| lhs_cols = extended_lhs_shape.Dims(4); | ||
| rhs_rows = extended_rhs_shape.Dims(3); | ||
| rhs_cols = extended_rhs_shape.Dims(4); | ||
| accum_depth = extended_lhs_shape.Dims(4); | ||
| } | ||
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| int batch_dim0; | ||
| int batch_dim1; | ||
| int batch_dim2; | ||
| int lhs_ext0; | ||
| int lhs_ext1; | ||
| int lhs_ext2; | ||
| int rhs_ext0; | ||
| int rhs_ext1; | ||
| int rhs_ext2; | ||
| int lhs_rows; | ||
| int lhs_cols; | ||
| int rhs_rows; | ||
| int rhs_cols; | ||
| int accum_depth; | ||
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| private: | ||
| // Determines which dimension is the broadcast dimension. | ||
| int32_t broadcast_dim(int32_t lhs_dim, int32_t rhs_dim) | ||
| { | ||
| if (lhs_dim == rhs_dim) | ||
| return lhs_dim; | ||
| if (lhs_dim == 1) | ||
| return rhs_dim; | ||
| assert(rhs_dim == 1); | ||
| return lhs_dim; | ||
| }; | ||
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| // Computes the "extent" for iterating on this dimension. | ||
| // If we are broadcasting, then don't advance (i.e return 0). | ||
| int extent(const Shape &shape, int x) | ||
| { | ||
| if (shape.Dims(x) == 1) | ||
| { | ||
| return 0; | ||
| } | ||
| int prod = 1; | ||
| for (int i = x + 1; i < shape.DimensionsCount(); ++i) | ||
| { | ||
| prod *= shape.Dims(i); | ||
| } | ||
| return prod; | ||
| }; | ||
| }; | ||
| } // namespace cker | ||
| } // namespace nnfw | ||
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| #endif |
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compute/cker/include/cker/operation/optimized/BatchMatMul.h
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,75 @@ | ||
| /* | ||
| * Copyright (c) 2024 Samsung Electronics Co., Ltd. All Rights Reserved | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); | ||
| * you may not use this file except in compliance with the License. | ||
| * You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
|
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| #ifndef __NNFW_CKER_OPTIMIZED_BATCH_MATMUL_H__ | ||
| #define __NNFW_CKER_OPTIMIZED_BATCH_MATMUL_H__ | ||
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| #include "cker/Shape.h" | ||
| #include "cker/operation/Helper/BatchMatMulParams.h" | ||
| #include "cker/operation/optimized/Gemm.h" | ||
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| namespace nnfw | ||
| { | ||
| namespace cker | ||
| { | ||
| namespace optimized | ||
| { | ||
| #if defined(CKER_X86_PLATFORM) | ||
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| inline void BatchMatMul(const BatchMatMulParams ¶ms, const float *lhs_data, | ||
| const float *rhs_data, float *output_data) | ||
| { | ||
| MatrixParams<float> lhs_params; | ||
| lhs_params.order = Order::kRowMajor; | ||
| lhs_params.rows = params.lhs_rows; | ||
| lhs_params.cols = params.lhs_cols; | ||
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| MatrixParams<float> rhs_params; | ||
| rhs_params.order = Order::kRowMajor; | ||
| rhs_params.rows = params.rhs_rows; | ||
| rhs_params.cols = params.rhs_cols; | ||
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| MatrixParams<float> dst_params; | ||
| dst_params.order = Order::kRowMajor; | ||
| dst_params.rows = params.lhs_rows; | ||
| dst_params.cols = params.rhs_cols; | ||
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| for (int b0 = 0; b0 < params.batch_dim0; ++b0) | ||
| { | ||
| for (int b1 = 0; b1 < params.batch_dim1; ++b1) | ||
| { | ||
| for (int b2 = 0; b2 < params.batch_dim2; ++b2) | ||
| { | ||
| const float *lhs_ptr = | ||
| lhs_data + b0 * params.lhs_ext0 + b1 * params.lhs_ext1 + b2 * params.lhs_ext2; | ||
| const float *rhs_ptr = | ||
| rhs_data + b0 * params.rhs_ext0 + b1 * params.rhs_ext1 + b2 * params.rhs_ext2; | ||
| float *out_ptr = output_data + ((b0 * params.batch_dim1 * params.batch_dim2) + | ||
| b1 * params.batch_dim2 + b2) * | ||
| params.lhs_rows * params.rhs_cols; | ||
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| optimized::Gemm(lhs_params, lhs_ptr, rhs_params, rhs_ptr, dst_params, out_ptr, | ||
| GemmParams<float, float>{}); | ||
| } | ||
| } | ||
| } | ||
| } | ||
| #endif | ||
| } // namespace optimized | ||
| } // namespace cker | ||
| } // namespace nnfw | ||
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| #endif // __NNFW_CKER_OPTIMIZED_BATCH_MATMUL_H__ |
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