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Diffstat (limited to 'src/core/NEON/kernels/assembly/NEGEMMInterleavedPrepareBWrapperKernel.cpp')
| -rw-r--r-- | src/core/NEON/kernels/assembly/NEGEMMInterleavedPrepareBWrapperKernel.cpp | 170 |
1 files changed, 170 insertions, 0 deletions
diff --git a/src/core/NEON/kernels/assembly/NEGEMMInterleavedPrepareBWrapperKernel.cpp b/src/core/NEON/kernels/assembly/NEGEMMInterleavedPrepareBWrapperKernel.cpp new file mode 100644 index 0000000000..f33a14f2af --- /dev/null +++ b/src/core/NEON/kernels/assembly/NEGEMMInterleavedPrepareBWrapperKernel.cpp @@ -0,0 +1,170 @@ +/* + * Copyright (c) 2018 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 "arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedPrepareBWrapperKernel.h" + +#include "NEGEMMInterleavedStrategies.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/ITensor.h" +#include "arm_compute/core/Utils.h" +#include "arm_compute/core/Validate.h" + +namespace arm_compute +{ +namespace +{ +// Call the lambda function for each workload generated by the passed window. +template <typename To, bool use_dot, typename Lambda> +void for_each_element_in_window(const Window &window, const ITensor *b, ITensor *transformed_b, unsigned int N, unsigned int K, Lambda &&lambda) +{ + using strategy = typename Kernel<To, use_dot>::strategy; + + unsigned int offset_transformed_b = transformed_b->info()->offset_first_element_in_bytes(); + execute_window_loop(window, [&](const Coordinates & coordinates) + { + const unsigned int x0 = coordinates.x(); + const unsigned int k0 = coordinates.y(); + const unsigned int multi = coordinates.z(); + + const unsigned int offset_b = b->info()->offset_element_in_bytes(Coordinates(0, 0, multi)); + const unsigned int xmax = std::min(x0 + window.x().step(), N); + const unsigned int kmax = std::min(k0 + window.y().step(), K); + + /* Figure out the size of each block. */ + unsigned int x_size = (xmax - x0); + unsigned int k_size = (kmax - k0); + + /* Round sizes up as needed. */ + x_size = ceil_to_multiple(x_size, strategy::out_width()); + k_size = ceil_to_multiple(k_size, strategy::k_unroll()); + + lambda(PrepareBWorkload(offset_b, offset_transformed_b, x0, xmax, k0, kmax)); + + //Each workload represents one block: + offset_transformed_b += (x_size * k_size * sizeof(To)); + }); +} + +// Calculate the size of transformed_b: +template <typename To, bool use_dot> +unsigned int get_B_pretransposed_array_size(unsigned int N, unsigned int K, const BlockSizes &bs) +{ + using strategy = typename Kernel<To, use_dot>::strategy; + + // How many full blocks do N / K contain ? + size_t num_full_k = K / bs.k_block; + size_t num_full_x = N / bs.x_block; + + ARM_COMPUTE_ERROR_ON(bs.x_block % strategy::out_width() != 0); + ARM_COMPUTE_ERROR_ON(bs.k_block % strategy::k_unroll() != 0); + + size_t normal_x_size = bs.x_block; + size_t normal_k_size = bs.k_block; + + // Round up the leftovers to be a multiple of the strategy processing size: + size_t left_over_x_size = ceil_to_multiple(N % bs.x_block, strategy::out_width()); + size_t left_over_k_size = ceil_to_multiple(K % bs.k_block, strategy::k_unroll()); + + // Calculate the total size of the buffer: + size_t total = num_full_k * normal_k_size * (num_full_x * normal_x_size + left_over_x_size); + total += left_over_k_size * (left_over_x_size + num_full_x * normal_x_size); + total *= sizeof(To); + return total; +} + +} // namespace + +template <typename To, bool use_dot> +BlockSizes NEGEMMInterleavedPrepareBWrapperKernelTemplate<To, use_dot>::block_sizes() const +{ + return _block_sizes; +} + +template <typename To, bool use_dot> +void NEGEMMInterleavedPrepareBWrapperKernelTemplate<To, use_dot>::configure(const ITensor *b, ITensor *transformed_b, bool transpose_b, const CPUInfo &ci, const INEGEMMWrapperKernel::Params ¶ms) +{ + using strategy = typename Kernel<To, use_dot>::strategy; + + const unsigned int multis = b->info()->tensor_shape().z(); + _Nsize = b->info()->tensor_shape().x(); + _Ksize = b->info()->tensor_shape().y(); + _b = b; + _transformed_b = transformed_b; + _transpose_b = transpose_b; + + _block_sizes = calculate_block_sizes<strategy>(ci, params.M, params.N, params.K); + + auto_init_if_empty(*transformed_b->info(), b->info()->clone()->set_tensor_shape(TensorShape{ get_B_pretransposed_array_size<To, use_dot>(_Nsize, _Ksize, _block_sizes) })); + + Window window; + window.set(Window::DimX, Window::Dimension(0, ceil_to_multiple(_Nsize, _block_sizes.x_block), _block_sizes.x_block)); + window.set(Window::DimY, Window::Dimension(0, ceil_to_multiple(_Ksize, _block_sizes.k_block), _block_sizes.k_block)); + window.set(Window::DimZ, Window::Dimension(0, multis)); + + INEKernel::configure(window); +} + +template <typename To, bool use_dot> +void NEGEMMInterleavedPrepareBWrapperKernelTemplate<To, use_dot>::transform(const PrepareBWorkload &wl, const ThreadInfo &info) +{ + using strategy = typename Kernel<To, use_dot>::strategy; + + strategy strat(info.cpu_info); + strat.transforms.PrepareB(reinterpret_cast<To *>(_transformed_b->buffer() + wl._offset_transformed_b), + reinterpret_cast<To *>(_b->buffer() + wl._offset_b), + _b->info()->strides_in_bytes().y() / sizeof(To), + wl._x0, wl._xmax, wl._k0, wl._kmax, _transpose_b); +} + +template <typename To, bool use_dot> +void NEGEMMInterleavedPrepareBWrapperKernelTemplate<To, use_dot>::create_workloads(std::vector<PrepareBWorkload> &workloads) +{ + for_each_element_in_window<To, use_dot>(window(), _b, _transformed_b, _Nsize, _Ksize, [&workloads](PrepareBWorkload && wl) + { + workloads.push_back(std::move(wl)); + }); +} + +template <typename To, bool use_dot> +void NEGEMMInterleavedPrepareBWrapperKernelTemplate<To, use_dot>::run(const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(window, INEKernel::window()); + for_each_element_in_window<To, use_dot>(window, _b, _transformed_b, _Nsize, _Ksize, [&](PrepareBWorkload && wl) + { + this->transform(wl, info); + }); +} + +template class NEGEMMInterleavedPrepareBWrapperKernelTemplate<float>; +#ifdef __aarch64__ +template class NEGEMMInterleavedPrepareBWrapperKernelTemplate<uint8_t>; +template class NEGEMMInterleavedPrepareBWrapperKernelTemplate<int8_t>; +template class NEGEMMInterleavedPrepareBWrapperKernelTemplate<uint8_t, true>; +template class NEGEMMInterleavedPrepareBWrapperKernelTemplate<int8_t, true>; +#endif /* __aarch64__ */ + +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +template class NEGEMMInterleavedPrepareBWrapperKernelTemplate<float16_t>; +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ +} // namespace arm_compute |