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csrc/gpu/cutlass_kernels/fp8_gemm_fused/fuse_gemm_noact_template_3x.h
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// Copyright (c) 2024 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. | ||
#pragma once | ||
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#include "fp8_common.h" | ||
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#include "cutlass/cutlass.h" | ||
#include "cutlass/epilogue/collective/default_epilogue.hpp" | ||
#include "cutlass/epilogue/thread/linear_combination.h" | ||
#include "cutlass/gemm/dispatch_policy.hpp" | ||
#include "cutlass/gemm/collective/collective_builder.hpp" | ||
#include "cutlass/epilogue/collective/collective_builder.hpp" | ||
#include "cutlass/gemm/device/gemm_universal_adapter.h" | ||
#include "cutlass/gemm/kernel/gemm_universal.hpp" | ||
#include "cutlass/gemm/kernel/tile_scheduler.hpp" | ||
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template < | ||
typename InputType = phi::dtype::float8_e4m3fn, | ||
typename OutType = phi::dtype::float16, | ||
typename TileShape = cute::Shape<cute::_128, cute::_128, cute::_128>, | ||
typename ClusterShape = cute::Shape<cute::_2, cute::_1, cute::_1>, | ||
typename KernelSchedule = cutlass::gemm::KernelTmaWarpSpecializedPingpongFP8FastAccum, | ||
typename EpilogueSchedule = cutlass::epilogue::TmaWarpSpecialized | ||
> | ||
bool dispatch_fuse_gemm_noact_sm90(GemmEpilogueAllParams params) { | ||
using ElementA = typename std::conditional_t<std::is_same_v<InputType, phi::dtype::float8_e4m3fn>, | ||
cutlass::float_e4m3_t, | ||
cutlass::float_e5m2_t>; | ||
using ElementB = ElementA; | ||
using ElementD = typename std::conditional_t<std::is_same_v<OutType, phi::dtype::bfloat16>, | ||
cutlass::bfloat16_t, | ||
cutlass::half_t>; | ||
using ElementC = ElementD; | ||
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using LayoutA = cutlass::layout::RowMajor; | ||
using LayoutB = cutlass::layout::ColumnMajor; | ||
using LayoutC = cutlass::layout::RowMajor; | ||
using LayoutD = cutlass::layout::RowMajor; | ||
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using ElementAccumulator = float; | ||
using ElementCompute = float; | ||
using ElementScalar = float; | ||
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// 16B alignment lets us use TMA | ||
static constexpr int AlignmentA = 16 / sizeof(ElementA); | ||
static constexpr int AlignmentB = 16 / sizeof(ElementB); | ||
static constexpr int AlignmentC = 16 / sizeof(ElementC); | ||
static constexpr int AlignmentD = 16 / sizeof(ElementD); | ||
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static constexpr auto RoundStyle = cutlass::FloatRoundStyle::round_to_nearest; | ||
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using DefaultOperation = cutlass::epilogue::fusion::LinearCombination<ElementD, ElementCompute, ElementC, ElementScalar, RoundStyle>; | ||
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using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder< | ||
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp, | ||
TileShape, | ||
ClusterShape, | ||
cutlass::epilogue::collective::EpilogueTileAuto, | ||
ElementAccumulator, ElementCompute, | ||
ElementC, LayoutC, AlignmentC, | ||
ElementD, LayoutD, AlignmentD, | ||
EpilogueSchedule, | ||
DefaultOperation | ||
>::CollectiveOp; | ||
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using CollectiveMainloop = typename cutlass::gemm::collective::CollectiveBuilder< | ||
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp, | ||
ElementA, LayoutA, AlignmentA, | ||
ElementB, LayoutB, AlignmentB, | ||
ElementAccumulator, | ||
TileShape, | ||
ClusterShape, | ||
cutlass::gemm::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename CollectiveEpilogue::SharedStorage))>, | ||
KernelSchedule | ||
>::CollectiveOp; | ||
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using GemmKernel = cutlass::gemm::kernel::GemmUniversal< | ||
cute::Shape<int,int,int,int>, | ||
CollectiveMainloop, | ||
CollectiveEpilogue, | ||
cutlass::gemm::PersistentScheduler | ||
>; | ||
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using Gemm = cutlass::gemm::device::GemmUniversalAdapter<GemmKernel>; | ||
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using ProblemShapeType = typename Gemm::GemmKernel::ProblemShape; | ||
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using StrideA = typename Gemm::GemmKernel::StrideA; | ||
using StrideB = typename Gemm::GemmKernel::StrideB; | ||
using StrideC = typename Gemm::GemmKernel::StrideC; | ||
using StrideD = typename Gemm::GemmKernel::StrideD; | ||
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// | ||
// Data members | ||
// | ||
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/// Initialization | ||
StrideA stride_A{params.lda, cute::Int<1>{}, 0}; | ||
StrideB stride_B{params.ldb, cute::Int<1>{}, 0}; | ||
StrideC stride_C{0, cute::Int<1>{}, 0}; | ||
StrideD stride_D{params.ldd, cute::Int<1>{}, 0}; | ||
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auto a_ptr = reinterpret_cast<ElementA*>(const_cast<void*>(params.A)); | ||
auto b_ptr = reinterpret_cast<ElementB*>(const_cast<void*>(params.B)); | ||
auto c_ptr = reinterpret_cast<ElementC*>(const_cast<void*>(params.bias)); | ||
auto d_ptr = reinterpret_cast<ElementD*>(params.D); | ||
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ProblemShapeType problem_size = ProblemShapeType{params.M, params.N, params.K, 1}; | ||
typename Gemm::Arguments arguments{ | ||
cutlass::gemm::GemmUniversalMode::kGemm, | ||
problem_size, | ||
{a_ptr, stride_A, b_ptr, stride_B}, | ||
{{}, // epilogue.thread | ||
c_ptr, stride_C, d_ptr, stride_D} | ||
}; | ||
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arguments.epilogue.thread.alpha = params.scale; | ||
arguments.epilogue.thread.beta = 1.0f; | ||
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Gemm gemm_op; | ||
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size_t workspace_size = Gemm::get_workspace_size(arguments); | ||
phi::Allocator* allocator = paddle::GetAllocator(params.place); | ||
auto workspace = allocator->Allocate(workspace_size); | ||
cutlass::Status status = gemm_op.can_implement(arguments); | ||
status = gemm_op(arguments, workspace->ptr(), params.stream); | ||
if (status != cutlass::Status::kSuccess) { | ||
std::cerr << "Gemm::run() failed" << std::endl; | ||
return false; | ||
} | ||
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} |
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