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158 lines
5.5 KiB
158 lines
5.5 KiB
// Copyright 2015 The Gemmlowp Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// single_thread_gemm.h: Single-threaded GEMM implementation.
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// This is a good place to start reading code, as it shows the overall
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// structure of a GEMM and is much simpler than multi_thread_gemm.h.
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#ifndef GEMMLOWP_INTERNAL_SINGLE_THREAD_GEMM_H_
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#define GEMMLOWP_INTERNAL_SINGLE_THREAD_GEMM_H_
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#include <cassert>
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#include "../public/map.h"
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#include "allocator.h"
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#include "compute.h"
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#include "kernel.h"
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#include "pack.h"
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#include "unpack.h"
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#ifdef GEMMLOWP_PROFILING_SIZES
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#ifndef GEMMLOWP_PROFILING
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#error GEMMLOWP_PROFILING_SIZES without GEMMLOWP_PROFILING
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#endif
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#include <string>
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#include <unordered_map>
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#endif
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namespace gemmlowp {
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class SingleThreadGemmContext {
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public:
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Allocator* allocator() { return &allocator_; }
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void set_l1_bytes_to_use(int n) { l1_bytes_to_use_ = n; }
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void set_l2_bytes_to_use(int n) { l2_bytes_to_use_ = n; }
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void set_l2_rhs_factor(float n) { l2_rhs_factor_ = n; }
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int l1_bytes_to_use() const { return l1_bytes_to_use_; }
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int l2_bytes_to_use() const { return l2_bytes_to_use_; }
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float l2_rhs_factor() const { return l2_rhs_factor_; }
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protected:
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Allocator allocator_;
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// The cache configurationt to use.
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int l1_bytes_to_use_ = kDefaultL1CacheSize;
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int l2_bytes_to_use_ = kDefaultL2CacheSize;
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float l2_rhs_factor_ = kDefaultL2RhsFactor;
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};
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template <typename KernelFormat, typename InputScalar, typename OutputScalar,
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typename BitDepthParams, MapOrder LhsOrder, MapOrder RhsOrder,
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MapOrder ResultOrder, typename LhsOffset, typename RhsOffset,
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typename OutputPipelineType>
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void SingleThreadGemm(SingleThreadGemmContext* context,
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const KernelBase& kernel,
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const MatrixMap<const InputScalar, LhsOrder>& lhs,
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const MatrixMap<const InputScalar, RhsOrder>& rhs,
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MatrixMap<OutputScalar, ResultOrder>* result,
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const LhsOffset& lhs_offset, const RhsOffset& rhs_offset,
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const OutputPipelineType& output_pipeline) {
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ScopedProfilingLabel label("gemmlowp::SingleThreadGemm");
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assert(lhs.cols() == rhs.rows());
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int rows = result->rows();
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int cols = result->cols();
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int depth = lhs.cols();
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// zero sizes should have been caught earlier and early-returned.
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assert(rows > 0);
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assert(cols > 0);
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assert(depth > 0);
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// The case of rows<cols should have been caught earlier and transposed.
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assert(rows >= cols);
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Allocator* allocator = context->allocator();
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BlockParams block_params;
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block_params.Init<KernelFormat>(
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rows, cols, depth, 1, context->l1_bytes_to_use(),
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context->l2_bytes_to_use(), context->l2_rhs_factor());
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#ifdef GEMMLOWP_PROFILING_SIZES
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// Using a static map of label strings. Not reentrant at all!
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static std::unordered_map<std::uint64_t, std::string> labels_map;
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std::uint64_t sizes_hash = static_cast<std::uint64_t>(rows) ^
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(static_cast<std::uint64_t>(depth) << 16) ^
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(static_cast<std::uint64_t>(cols) << 32);
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if (!labels_map.count(sizes_hash)) {
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char label[256];
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snprintf(label, sizeof(label),
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"(rows = %d, depth = %d, cols = %d, l2_rows = %d, l2_depth = %d, "
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"l2_cols = %d, l1_rows = %d, l1_depth = %d, l1_cols = %d)",
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rows, depth, cols, block_params.l2_rows, block_params.l2_depth,
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block_params.l2_cols, block_params.l1_rows, block_params.l1_depth,
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block_params.l1_cols);
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labels_map[sizes_hash] = label;
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}
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ScopedProfilingLabel size_label(labels_map[sizes_hash].c_str());
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#endif
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PackedSideBlock<typename KernelFormat::Lhs> packed_lhs(Side::Lhs, allocator,
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block_params);
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PackedSideBlock<typename KernelFormat::Rhs> packed_rhs(Side::Rhs, allocator,
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block_params);
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PackedResult packed_result(allocator, block_params);
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allocator->Commit();
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const bool pack_rhs_once = block_params.l2_cols >= cols;
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if (pack_rhs_once) {
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PackRhs(&packed_rhs, rhs);
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}
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for (int r = 0; r < rows; r += block_params.l2_rows) {
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int rs = std::min(block_params.l2_rows, rows - r);
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PackLhs(&packed_lhs, lhs.block(r, 0, rs, depth));
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for (int c = 0; c < cols; c += block_params.l2_cols) {
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int cs = std::min(block_params.l2_cols, cols - c);
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if (!pack_rhs_once) {
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PackRhs(&packed_rhs, rhs.block(0, c, depth, cs));
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}
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Compute(kernel, block_params, &packed_result, packed_lhs, packed_rhs,
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depth);
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UnpackResult<KernelFormat>(
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result, MatrixBlockBounds(r, c, rs, cs), packed_result, depth,
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packed_lhs.sums_of_each_slice(), packed_rhs.sums_of_each_slice(),
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lhs_offset.block(r, rs), rhs_offset.block(c, cs), output_pipeline);
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}
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}
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allocator->Decommit();
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}
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} // namespace gemmlowp
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#endif // GEMMLOWP_INTERNAL_SINGLE_THREAD_GEMM_H_
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