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Diffstat (limited to 'src/cpu/kernels/CpuGemmMatrixAdditionKernel.cpp')
| -rw-r--r-- | src/cpu/kernels/CpuGemmMatrixAdditionKernel.cpp | 200 |
1 files changed, 200 insertions, 0 deletions
diff --git a/src/cpu/kernels/CpuGemmMatrixAdditionKernel.cpp b/src/cpu/kernels/CpuGemmMatrixAdditionKernel.cpp new file mode 100644 index 0000000000..81376fb029 --- /dev/null +++ b/src/cpu/kernels/CpuGemmMatrixAdditionKernel.cpp @@ -0,0 +1,200 @@ +/* + * Copyright (c) 2016-2021 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 "src/cpu/kernels/CpuGemmMatrixAdditionKernel.h" + +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Validate.h" +#include "src/core/CPP/Validate.h" +#include "src/core/NEON/NEFixedPoint.h" +#include "src/core/helpers/AutoConfiguration.h" +#include "src/core/helpers/WindowHelpers.h" + +#include <arm_neon.h> + +namespace arm_compute +{ +namespace cpu +{ +namespace kernels +{ +namespace +{ +void matrix_addition_f32(const ITensor *src, ITensor *dst, const Window &window, float beta) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); + const float32x4_t beta_f32 = vdupq_n_f32(beta); + + constexpr int window_step_x = 16; + const auto window_start_x = static_cast<int>(window.x().start()); + const auto window_end_x = static_cast<int>(window.x().end()); + + Window win = window.collapse_if_possible(window, Window::DimZ); + win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + Iterator in(src, win); + Iterator out(dst, win); + + execute_window_loop(win, [&](const Coordinates &) + { + const auto in_ptr = reinterpret_cast<const float *>(in.ptr()); + const auto out_ptr = reinterpret_cast<float *>(out.ptr()); + + int x = window_start_x; + for(; x < (window_end_x - window_step_x); x += window_step_x) + { + float32x4x4_t alpha_ab = vld4q_f32(out_ptr + x); + const float32x4x4_t c = vld4q_f32(in_ptr + x); + + // Multiply matrix C by its weight and accumulate + alpha_ab.val[0] = vmlaq_f32(alpha_ab.val[0], c.val[0], beta_f32); + alpha_ab.val[1] = vmlaq_f32(alpha_ab.val[1], c.val[1], beta_f32); + alpha_ab.val[2] = vmlaq_f32(alpha_ab.val[2], c.val[2], beta_f32); + alpha_ab.val[3] = vmlaq_f32(alpha_ab.val[3], c.val[3], beta_f32); + + vst4q_f32(out_ptr + x, alpha_ab); + } + + // Left-over loop + for(; x < window_end_x; ++x) + { + *(out_ptr + x) += *(in_ptr + x) * beta; + } + }, + in, out); +} + +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +void matrix_addition_f16(const ITensor *src, ITensor *dst, const Window &window, float beta) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); + const float16x8_t beta_f16 = vdupq_n_f16(beta); + + constexpr int window_step_x = 16; + const auto window_start_x = static_cast<int>(window.x().start()); + const auto window_end_x = static_cast<int>(window.x().end()); + + Window win = window.collapse_if_possible(window, Window::DimZ); + win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + Iterator in(src, win); + Iterator out(dst, win); + + execute_window_loop(win, [&](const Coordinates &) + { + const auto in_ptr = reinterpret_cast<const float16_t *>(in.ptr()); + const auto out_ptr = reinterpret_cast<float16_t *>(out.ptr()); + + int x = window_start_x; + for(; x < (window_end_x - window_step_x); x += window_step_x) + { + float16x8x2_t alpha_ab = vld2q_f16(out_ptr + x); + const float16x8x2_t c = vld2q_f16(in_ptr + x); + // Multiply matrix C by its weight and accumulate + alpha_ab.val[0] = vaddq_f16(alpha_ab.val[0], vmulq_f16(c.val[0], beta_f16)); + alpha_ab.val[1] = vaddq_f16(alpha_ab.val[1], vmulq_f16(c.val[1], beta_f16)); + + vst2q_f16(out_ptr + x, alpha_ab); + } + + // Left-over loop + for(; x < window_end_x; ++x) + { + *(out_ptr + x) += *(in_ptr + x) * static_cast<float16_t>(beta); + } + }, + in, out); +} +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ + +} // namespace + +void CpuGemmMatrixAdditionKernel::configure(const ITensorInfo *src, ITensorInfo *dst, float beta) +{ + ARM_COMPUTE_UNUSED(dst); + ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); + + // Perform validation step + ARM_COMPUTE_ERROR_THROW_ON(CpuGemmMatrixAdditionKernel::validate(src, dst, beta)); + + _beta = beta; + switch(src->data_type()) + { + case DataType::F32: + _func = &matrix_addition_f32; + break; + case DataType::F16: +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC + _func = &matrix_addition_f16; + break; +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ + default: + ARM_COMPUTE_ERROR("Data type not supported"); + break; + } + + // Configure kernel window + Window win = calculate_max_window(*src, Steps()); + ICPPKernel::configure(win); +} + +Status CpuGemmMatrixAdditionKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, float beta) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst); + ARM_COMPUTE_UNUSED(beta); + + ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(src); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::F16, DataType::F32); + + if(dst->total_size() > 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(src, dst); + } + return Status{}; +} + +void CpuGemmMatrixAdditionKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_UNUSED(info); + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); + ARM_COMPUTE_ERROR_ON(tensors.empty()); + + const ITensor *src = tensors.get_const_tensor(TensorType::ACL_SRC); + ITensor *dst = tensors.get_tensor(TensorType::ACL_DST); + + if(_beta != 0.0f) + { + (*_func)(src, dst, window, _beta); + } +} + +const char *CpuGemmMatrixAdditionKernel::name() const +{ + return "CpuGemmMatrixAdditionKernel"; +} +} // namespace kernels +} // namespace cpu +} // namespace arm_compute |