tensor-tang
6 years ago
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GitHub
commit
6057f36208
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/* Copyright (c) 2019 PaddlePaddle 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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#include "paddle/fluid/operators/jit/gen/vbroadcast.h"
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#include <memory>
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#include <vector>
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#include "paddle/fluid/operators/jit/registry.h"
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#include "paddle/fluid/platform/cpu_info.h"
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namespace paddle {
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namespace operators {
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namespace jit {
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namespace gen {
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void VBroadcastJitCode::genCode() {
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preCode();
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constexpr int block = YMM_FLOAT_BLOCK;
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constexpr int max_num_regs = 16;
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const int num_block = w_ / block;
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const int num_groups = num_block / max_num_regs;
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const size_t block_size = sizeof(float) * block;
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std::vector<int> groups(num_groups, max_num_regs);
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int rest_num_regs = num_block % max_num_regs;
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if (rest_num_regs > 0) {
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groups.push_back(rest_num_regs);
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}
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// protect param_h
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mov(reg_height, param_h);
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Label l_next_h;
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xor_(reg_h_i, reg_h_i);
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mov(reg_ptr_dst_i, param_dst);
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L(l_next_h);
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{
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mov(reg_ptr_src_i, param_src);
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for (int num_regs : groups) {
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size_t w_offset = 0;
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for (int reg_i = 0; reg_i < num_regs; ++reg_i) {
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vmovups(ymm_t(reg_i), ptr[reg_ptr_src_i + w_offset]);
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w_offset += block_size;
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}
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add(reg_ptr_src_i, num_regs * block_size);
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w_offset = 0;
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for (int reg_i = 0; reg_i < num_regs; ++reg_i) {
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vmovups(ptr[reg_ptr_dst_i + w_offset], ymm_t(reg_i));
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w_offset += block_size;
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}
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add(reg_ptr_dst_i, num_regs * block_size);
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} // end of groups
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inc(reg_h_i);
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cmp(reg_h_i, reg_height);
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jl(l_next_h, T_NEAR);
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} // end of l_next_h
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postCode();
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}
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class VBroadcastCreator : public JitCodeCreator<int64_t> {
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public:
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bool UseMe(const int64_t& w) const override {
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return platform::MayIUse(platform::avx) && w % YMM_FLOAT_BLOCK == 0;
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}
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size_t CodeSize(const int64_t& w) const override {
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return 96 + (w / YMM_FLOAT_BLOCK) * 16 * 8;
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}
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std::unique_ptr<GenBase> CreateJitCode(const int64_t& w) const override {
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PADDLE_ENFORCE_GT(w, 0);
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return make_unique<VBroadcastJitCode>(w, CodeSize(w));
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}
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};
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} // namespace gen
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} // namespace jit
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} // namespace operators
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} // namespace paddle
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namespace gen = paddle::operators::jit::gen;
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REGISTER_JITKERNEL_GEN(kVBroadcast, gen::VBroadcastCreator);
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@ -0,0 +1,53 @@
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/* Copyright (c) 2018 PaddlePaddle 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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#pragma once
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#include <string>
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#include "glog/logging.h"
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#include "paddle/fluid/operators/jit/gen/jitcode.h"
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namespace paddle {
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namespace operators {
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namespace jit {
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namespace gen {
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class VBroadcastJitCode : public JitCode {
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public:
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explicit VBroadcastJitCode(const int64_t& w, size_t code_size = 256 * 1024,
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void* code_ptr = nullptr)
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: JitCode(code_size, code_ptr), w_(w) {
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this->genCode();
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}
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DECLARE_JIT_CODE(VBroadcastJitCode);
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void genCode() override;
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private:
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int w_;
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reg64_t param_src{abi_param1};
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reg64_t param_dst{abi_param2};
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reg64_t param_h{abi_param3};
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reg64_t param_w{abi_param4};
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reg64_t reg_height{r9};
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reg64_t reg_h_i{r10};
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reg64_t reg_ptr_src_i{r11};
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reg64_t reg_ptr_dst_i{r12};
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};
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} // namespace gen
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} // namespace jit
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} // namespace operators
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} // namespace paddle
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