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FastDeploy/custom_ops/gpu_ops/w4afp8_gemm/kernel_traits.h
2025-08-11 19:00:18 +08:00

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// 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>
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<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 TokenPackSize_,
int TAIL_N_ = 0,
int kClusterM_ = 1,
typename elem_type=cutlass::float_e4m3_t,
typename OutputType = cutlass::bfloat16_t>
struct Kernel_traits {
using Element = elem_type;
using ElementAccum = float;
using ElementOutput = OutputType;
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 TAIL_N = TAIL_N_;
using TileShape_MNK = Shape<Int<kBlockM>, Int<kBlockN>, Int<kBlockK>>;
using TileShape_MNK_TAIL = Shape<Int<kBlockM>, Int<TAIL_N>, 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 TiledMma_TAIL = decltype(cute::make_tiled_mma(
cute::GMMA::rs_op_selector<Element, Element, ElementAccum, TileShape_MNK_TAIL>(),
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 SmemLayoutAtomB_TAIL = decltype(
cutlass::gemm::collective::detail::rs_smem_selector<
GMMA::Major::K, Element, decltype(cute::get<1>(TileShape_MNK_TAIL{})),
decltype(cute::get<2>(TileShape_MNK_TAIL{}))>());
using SmemLayoutB_TAIL = decltype(
tile_to_shape(SmemLayoutAtomB_TAIL{},
make_shape(
shape<1>(TileShape_MNK_TAIL{}),
shape<2>(TileShape_MNK_TAIL{}),
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 SharedStorage = SharedStorage<
kStages, Element, ElementOutput, SmemLayoutA, SmemLayoutB, SmemLayoutC>;
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
));
};