/* Copyright (c) 2018 PaddlePaddle Authors. 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. */ #include "paddle/fluid/operators/math/jit_kernel.h" #include #include "paddle/fluid/operators/math/jit_kernel_macro.h" #include "paddle/fluid/operators/math/jit_kernel_refer.h" #include "paddle/fluid/platform/enforce.h" #ifdef PADDLE_WITH_XBYAK #include "paddle/fluid/operators/math/jit_code.h" #endif #ifdef PADDLE_WITH_MKLML #include "paddle/fluid/platform/dynload/mklml.h" #endif namespace paddle { namespace operators { namespace math { namespace jitkernel { namespace jit = platform::jit; #ifdef PADDLE_WITH_MKLML template void VMulMKL(const T* x, const T* y, T* z, int n); template <> void VMulMKL(const float* x, const float* y, float* z, int n) { platform::dynload::vsMul(n, x, y, z); } template <> void VMulMKL(const double* x, const double* y, double* z, int n) { platform::dynload::vdMul(n, x, y, z); } template void VAddMKL(const T* x, const T* y, T* z, int n); template <> void VAddMKL(const float* x, const float* y, float* z, int n) { platform::dynload::vsAdd(n, x, y, z); } template <> void VAddMKL(const double* x, const double* y, double* z, int n) { platform::dynload::vdAdd(n, x, y, z); } template void VScalMKL(const T* a, const T* x, T* y, int n); template <> void VScalMKL(const float* a, const float* x, float* y, int n) { if (x == y) { platform::dynload::cblas_sscal(n, *a, y, 1); } else { refer::VScal(a, x, y, n); } } template <> void VScalMKL(const double* a, const double* x, double* y, int n) { if (x == y) { platform::dynload::cblas_dscal(n, *a, y, 1); } else { refer::VScal(a, x, y, n); } } #endif /* VMUL JitKernel */ template class VMulKernelImpl : public VMulKernel { public: JITKERNEL_DECLARE_STATIC_FUNC; explicit VMulKernelImpl(int d) : VMulKernel() { #ifdef PADDLE_WITH_XBYAK if (useJIT(d)) { // roughly estimate the size of code size_t sz = 96 + d / YMM_FLOAT_BLOCK * 4 * 8; jitcode_.reset(new gen::VXXJitCode(d, gen::operand_type::mul, 0, false, sz > 4096 ? sz : 4096)); this->Compute = jitcode_->getCode(); return; } #endif #ifdef PADDLE_WITH_MKLML if (useMKL(d)) { this->Compute = VMulMKL; return; } #endif this->Compute = refer::VMul; } #ifdef PADDLE_WITH_XBYAK private: std::unique_ptr jitcode_{nullptr}; #endif }; #ifdef PADDLE_WITH_XBYAK template <> bool VMulKernelImpl::useJIT(int d) { return gen::VXXJitCode::init(d); } #endif #ifdef PADDLE_WITH_MKLML template <> bool VMulKernelImpl::useMKL(int d) { return jit::MayIUse(jit::avx512f) && d > 512; } template <> bool VMulKernelImpl::useMKL(int d) { return true; } #endif /* VAdd JitKernel */ template class VAddKernelImpl : public VAddKernel { public: JITKERNEL_DECLARE_STATIC_FUNC; explicit VAddKernelImpl(int d) : VAddKernel() { #ifdef PADDLE_WITH_XBYAK if (useJIT(d)) { size_t sz = 96 + d / YMM_FLOAT_BLOCK * 4 * 8; jitcode_.reset(new gen::VXXJitCode(d, gen::operand_type::add, 0, false, sz > 4096 ? sz : 4096)); this->Compute = jitcode_->getCode(); return; } #endif #ifdef PADDLE_WITH_MKLML if (useMKL(d)) { this->Compute = VAddMKL; return; } #endif this->Compute = refer::VAdd; } #ifdef PADDLE_WITH_XBYAK private: std::unique_ptr jitcode_{nullptr}; #endif }; #ifdef PADDLE_WITH_XBYAK template <> bool VAddKernelImpl::useJIT(int d) { return gen::VXXJitCode::init(d); } #endif #ifdef PADDLE_WITH_MKLML template <> bool VAddKernelImpl::useMKL(int d) { return d > 512; } template <> bool VAddKernelImpl::useMKL(int d) { return true; } #endif /* VAddRelu JitKernel */ template class VAddReluKernelImpl : public VAddReluKernel { public: JITKERNEL_DECLARE_STATIC_FUNC; explicit VAddReluKernelImpl(int d) : VAddReluKernel() { #ifdef PADDLE_WITH_XBYAK if (useJIT(d)) { size_t sz = 96 + d / YMM_FLOAT_BLOCK * 4 * 8; jitcode_.reset(new gen::VXXJitCode(d, gen::operand_type::add, 0, true, sz > 4096 ? sz : 4096)); this->Compute = jitcode_->getCode(); return; } #endif this->Compute = refer::VAddRelu; } #ifdef PADDLE_WITH_XBYAK private: std::unique_ptr jitcode_{nullptr}; #endif }; #ifdef PADDLE_WITH_XBYAK template <> bool VAddReluKernelImpl::useJIT(int d) { return gen::VXXJitCode::init(d); } #endif /* VScal JitKernel */ template class VScalKernelImpl : public VScalKernel { public: JITKERNEL_DECLARE_STATIC_FUNC; explicit VScalKernelImpl(int d) : VScalKernel() { #ifdef PADDLE_WITH_XBYAK if (useJIT(d)) { size_t sz = 96 + d / YMM_FLOAT_BLOCK * 4 * 8; jitcode_.reset(new gen::VXXJitCode(d, gen::operand_type::mul, 1, false, sz > 4096 ? sz : 4096)); this->Compute = jitcode_->getCode(); return; } #endif #ifdef PADDLE_WITH_MKLML if (useMKL(d)) { this->Compute = VScalMKL; return; } #endif this->Compute = refer::VScal; } #ifdef PADDLE_WITH_XBYAK private: std::unique_ptr jitcode_{nullptr}; #endif }; #ifdef PADDLE_WITH_XBYAK template <> bool VScalKernelImpl::useJIT(int d) { return gen::VXXJitCode::init(d, 1); } #endif #ifdef PADDLE_WITH_MKLML template <> bool VScalKernelImpl::useMKL(int d) { return d > 512; } template <> bool VScalKernelImpl::useMKL(int d) { return true; } #endif /* VAddBias JitKernel */ template class VAddBiasKernelImpl : public VAddBiasKernel { public: JITKERNEL_DECLARE_STATIC_FUNC; explicit VAddBiasKernelImpl(int d) : VAddBiasKernel() { #ifdef PADDLE_WITH_XBYAK if (useJIT(d)) { size_t sz = 96 + d / YMM_FLOAT_BLOCK * 4 * 8; jitcode_.reset(new gen::VXXJitCode(d, gen::operand_type::add, 1, false, sz > 4096 ? sz : 4096)); this->Compute = jitcode_->getCode(); return; } #endif this->Compute = refer::VAddBias; } #ifdef PADDLE_WITH_XBYAK private: std::unique_ptr jitcode_{nullptr}; #endif }; #ifdef PADDLE_WITH_XBYAK template <> bool VAddBiasKernelImpl::useJIT(int d) { return gen::VXXJitCode::init(d, 1); } #endif /* VRelu JitKernel */ template class VReluKernelImpl : public VReluKernel { public: JITKERNEL_DECLARE_STATIC_FUNC; explicit VReluKernelImpl(int d) : VReluKernel() { #ifdef PADDLE_WITH_XBYAK if (useJIT(d)) { size_t sz = 96 /* init size */ + d / YMM_FLOAT_BLOCK * 4 /* instructions */ * 8 /* average bytes for each instruction */; jitcode_.reset(new gen::VActJitCode(d, gen::operand_type::relu, sz > 4096 ? sz : 4096)); this->Compute = jitcode_->getCode(); return; } #endif this->Compute = refer::VRelu; } #ifdef PADDLE_WITH_XBYAK private: std::unique_ptr jitcode_{nullptr}; #endif }; #ifdef PADDLE_WITH_XBYAK template <> bool VReluKernelImpl::useJIT(int d) { return gen::VActJitCode::init(d, gen::operand_type::relu); } #endif /* An empty JitKernel */ template class VIdentityKernelImpl : public VIdentityKernel { public: JITKERNEL_DECLARE_STATIC_FUNC; explicit VIdentityKernelImpl(int d) : VIdentityKernel() { this->Compute = refer::VIdentity; } }; REGISTER_JITKERNEL(vmul, VMulKernel); REGISTER_JITKERNEL(vadd, VAddKernel); REGISTER_JITKERNEL(vaddrelu, VAddReluKernel); REGISTER_JITKERNEL(vscal, VScalKernel); REGISTER_JITKERNEL(vaddbias, VAddBiasKernel); REGISTER_JITKERNEL(vrelu, VReluKernel); REGISTER_JITKERNEL(videntity, VIdentityKernel); } // namespace jitkernel } // namespace math } // namespace operators } // namespace paddle