Files
FastDeploy/custom_ops/gpu_ops/w4afp8_gemm/kernel_traits.h
yangjianfengo1 ae7bee8122 【New Feature】W4afp8 supports per group quantization (#4987)
* w4afp8 支持per group

* code style

* fix transpose

* revert fast hardmard

---------

Co-authored-by: yuanxiaolan <yuanxiaolan01@baidu.com>
Co-authored-by: plusNew001 <95567040+plusNew001@users.noreply.github.com>
2025-11-13 19:17:27 +08:00

165 lines
6.1 KiB
C++

// Copyright (c) 2025 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 "cute/algorithm/copy.hpp"
#include "cute/atom/mma_atom.hpp"
#include "cutlass/gemm/collective/collective_builder.hpp"
#include "cutlass/cutlass.h"
#include "cutlass/layout/layout.h"
#include "cutlass/numeric_types.h"
#include "cutlass/pipeline/pipeline.hpp"
using namespace cute;
template <int kStages,
class GemmType,
class OutputType,
class SmemLayoutA,
class SmemLayoutB,
class SmemLayoutC,
class SmemLayoutScale>
struct SharedStorage {
union {
struct {
cute::array_aligned<GemmType, cute::cosize_v<SmemLayoutA>> smem_a;
cute::array_aligned<GemmType, cute::cosize_v<SmemLayoutB>> smem_b;
cute::array_aligned<float, cute::cosize_v<SmemLayoutScale>> smem_scale;
};
cute::array_aligned<OutputType, cute::cosize_v<SmemLayoutC>> smem_c;
};
struct {
typename cutlass::PipelineTmaAsync<kStages>::SharedStorage pipeline;
};
};
template <int kBlockM_,
int kBlockN_,
int kBlockK_,
int kNWarps_,
int kStages_,
int kTiles_,
int M_,
int K_,
int TokenPackSize_,
int WeightScaleGroup_,
int kClusterM_ = 1,
typename elem_type = cutlass::float_e4m3_t,
typename OutputType = cutlass::bfloat16_t>
struct Kernel_traits {
using Element = elem_type;
using ElementOutput = OutputType;
using ElementAccum = typename std::
conditional_t<WeightScaleGroup_ == K_, float, cutlass::half_t>;
static_assert(cutlass::sizeof_bits_v<Element> == 8);
static constexpr int kNWarps = kNWarps_;
static constexpr int kNThreads = kNWarps * cutlass::NumThreadsPerWarp;
static constexpr int NumProducerThreads = cutlass::NumThreadsPerWarpGroup;
static constexpr int NumMmaThreads = kNThreads - NumProducerThreads;
static_assert(kNWarps_ == 12 || kNWarps_ == 16);
static constexpr int kBlockM = kBlockM_;
static constexpr int kBlockN = kBlockN_;
static constexpr int kBlockK = kBlockK_;
static constexpr int kTiles = kTiles_;
static constexpr int TokenPackSize = TokenPackSize_;
static constexpr int M = M_;
static constexpr int K = K_;
static constexpr int WeightScaleGroup = WeightScaleGroup_;
using TileShape_MNK = Shape<Int<kBlockM>, Int<kBlockN>, Int<kBlockK>>;
static constexpr int kClusterM = kClusterM_;
using ClusterShape_MNK = Shape<Int<kClusterM>, _1, _1>;
static constexpr int kStages = kStages_;
static_assert(kStages > 1);
using AtomLayoutMNK = Layout<Shape<Int<kBlockM / 64>, _1, _1>>;
using TiledMma = decltype(cute::make_tiled_mma(
cute::GMMA::
rs_op_selector<Element, Element, ElementAccum, TileShape_MNK>(),
AtomLayoutMNK{}));
using SmemLayoutAtomA =
decltype(cutlass::gemm::collective::detail::rs_smem_selector<
GMMA::Major::K,
Element,
Int<kBlockM>,
Int<kBlockK / 2>>());
using SmemLayoutA = decltype(tile_to_shape(
SmemLayoutAtomA{},
make_shape(Int<kBlockM>{}, Int<kBlockK / 2>{}, Int<kStages>{})));
using SmemLayoutAtomB =
decltype(cutlass::gemm::collective::detail::rs_smem_selector<
GMMA::Major::K,
Element,
decltype(cute::get<1>(TileShape_MNK{})),
decltype(cute::get<2>(TileShape_MNK{}))>());
using SmemLayoutB =
decltype(tile_to_shape(SmemLayoutAtomB{},
make_shape(shape<1>(TileShape_MNK{}),
shape<2>(TileShape_MNK{}),
Int<kStages>{})));
using SmemLayoutAtomC =
decltype(cutlass::gemm::collective::detail::rs_smem_selector<
GMMA::Major::K,
ElementOutput,
decltype(cute::get<0>(TileShape_MNK{})),
decltype(cute::get<1>(TileShape_MNK{}))>());
using SmemLayoutC =
decltype(tile_to_shape(SmemLayoutAtomC{}, select<0, 1>(TileShape_MNK{})));
using SmemCopyAtomAB = Copy_Atom<cute::SM75_U32x4_LDSM_N, Element>;
using SmemCopyAtomC = Copy_Atom<cute::SM90_U32x4_STSM_N, ElementOutput>;
using SmemLayoutScale = Layout<Shape<Int<kBlockM>, Int<kStages>>>;
using SharedStorage = SharedStorage<kStages,
Element,
ElementOutput,
SmemLayoutA,
SmemLayoutB,
SmemLayoutC,
SmemLayoutScale>;
using MainloopPipeline = typename cutlass::PipelineTmaAsync<kStages>;
using PipelineState = typename cutlass::PipelineState<kStages>;
static constexpr int kNumVecElem = ceil_div(128, sizeof_bits_v<OutputType>);
static constexpr int kNumThreadsPerRow = kBlockN / kNumVecElem;
// static_assert(NumMmaThreads % kNumThreadsPerRow == 0);
static constexpr int kNumRows = NumMmaThreads / kNumThreadsPerRow;
using TiledCopyCAtom =
cute::Copy_Atom<cute::UniversalCopy<cutlass::uint128_t>, OutputType>;
using TiledCopyCThrLayout = decltype(cute::make_layout(
cute::make_shape(Int<kNumRows>{}, Int<kNumThreadsPerRow>{}),
LayoutRight{}));
using TiledCopyCValLayout = decltype(cute::make_layout(
cute::make_shape(_1{}, Int<kNumVecElem>{}), LayoutRight{}));
using TiledCopyC =
decltype(make_tiled_copy(TiledCopyCAtom{},
TiledCopyCThrLayout{}, // Thr layout
TiledCopyCValLayout{} // Val layout
));
};