mirror of
https://github.com/huggingface/candle.git
synced 2025-06-16 18:48:51 +00:00
8d1a57c9a0
* chore: update flash attention kernels * fmt * remove unused kernels * force f32 * correct stride
160 lines
7.4 KiB
C++
160 lines
7.4 KiB
C++
/******************************************************************************
|
|
* Copyright (c) 2023, Tri Dao.
|
|
******************************************************************************/
|
|
|
|
#pragma once
|
|
|
|
#include "cute/algorithm/copy.hpp"
|
|
|
|
#include "cutlass/cutlass.h"
|
|
#include "cutlass/layout/layout.h"
|
|
#include <cutlass/numeric_types.h>
|
|
|
|
using namespace cute;
|
|
|
|
template<int kHeadDim_, int kBlockM_, int kBlockN_, int kNWarps_, typename elem_type=cutlass::half_t>
|
|
struct Flash_kernel_traits_sm90 {
|
|
|
|
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 800
|
|
using Element = elem_type;
|
|
static constexpr bool Has_cp_async = true;
|
|
#else
|
|
using Element = cutlass::half_t;
|
|
static constexpr bool Has_cp_async = false;
|
|
#endif
|
|
|
|
using ElementAccum = float;
|
|
using index_t = uint32_t;
|
|
|
|
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 800
|
|
using MMA_Atom_Arch = std::conditional_t<
|
|
std::is_same_v<elem_type, cutlass::half_t>,
|
|
MMA_Atom<SM80_16x8x16_F32F16F16F32_TN>,
|
|
MMA_Atom<SM80_16x8x16_F32BF16BF16F32_TN>
|
|
>;
|
|
using ValLayoutMNK = Layout<Shape<_1, _2, _1>>;
|
|
#else
|
|
using MMA_Atom_Arch = MMA_Atom<SM75_16x8x8_F32F16F16F32_TN>;
|
|
using ValLayoutMNK = Layout<Shape<_1, _2, _2>>;
|
|
#endif
|
|
|
|
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 750
|
|
using SmemCopyAtom = Copy_Atom<SM75_U32x4_LDSM_N, elem_type>;
|
|
using SmemCopyAtomTransposed = Copy_Atom<SM75_U16x8_LDSM_T, elem_type>;
|
|
#else
|
|
using SmemCopyAtom = Copy_Atom<DefaultCopy, elem_type>;
|
|
using SmemCopyAtomTransposed = Copy_Atom<DefaultCopy, elem_type>;
|
|
#endif
|
|
};
|
|
|
|
template<int kHeadDim_, int kBlockM_, int kBlockN_, int kNWarps_, bool Is_Q_in_regs_=false, bool Share_Q_K_smem_=false, typename elem_type=cutlass::half_t,
|
|
typename Base=Flash_kernel_traits_sm90<kHeadDim_, kBlockM_, kBlockN_, kNWarps_, elem_type> >
|
|
struct Flash_fwd_kernel_traits : public Base {
|
|
using Element = typename Base::Element;
|
|
using ElementAccum = typename Base::ElementAccum;
|
|
using index_t = typename Base::index_t;
|
|
static constexpr bool Has_cp_async = Base::Has_cp_async;
|
|
using SmemCopyAtom = typename Base::SmemCopyAtom;
|
|
using SmemCopyAtomTransposed = typename Base::SmemCopyAtomTransposed;
|
|
|
|
static constexpr bool Share_Q_K_smem = Share_Q_K_smem_;
|
|
static constexpr bool Is_Q_in_regs = Is_Q_in_regs_ || Share_Q_K_smem;
|
|
|
|
// The number of threads.
|
|
static constexpr int kNWarps = kNWarps_;
|
|
static constexpr int kNThreads = kNWarps * 32;
|
|
|
|
static constexpr int kBlockM = kBlockM_;
|
|
static constexpr int kBlockN = kBlockN_;
|
|
static constexpr int kHeadDim = kHeadDim_;
|
|
static_assert(kHeadDim % 32 == 0);
|
|
static constexpr int kBlockKSmem = kHeadDim % 64 == 0 ? 64 : 32;
|
|
static constexpr int kBlockKGmem = kHeadDim % 128 == 0 ? 128 : (kHeadDim % 64 == 0 ? 64 : 32);
|
|
static constexpr int kSwizzle = kBlockKSmem == 32 ? 2 : 3;
|
|
|
|
using TiledMma = TiledMMA<
|
|
typename Base::MMA_Atom_Arch,
|
|
Layout<Shape<Int<kNWarps>,_1,_1>>, // 4x1x1 or 8x1x1 thread group
|
|
typename Base::ValLayoutMNK>; // 1x2x1 or 1x2x2 value group for 16x16x16 MMA and LDSM
|
|
|
|
using SmemLayoutAtomQ = decltype(
|
|
composition(Swizzle<kSwizzle, 3, 3>{},
|
|
// This has to be kBlockKSmem, using kHeadDim gives wrong results for d=128
|
|
Layout<Shape<_8, Int<kBlockKSmem>>,
|
|
Stride<Int<kBlockKSmem>, _1>>{}));
|
|
using SmemLayoutQ = decltype(tile_to_shape(
|
|
SmemLayoutAtomQ{},
|
|
Shape<Int<kBlockM>, Int<kHeadDim>>{}));
|
|
|
|
using SmemLayoutKV = decltype(tile_to_shape(
|
|
SmemLayoutAtomQ{},
|
|
Shape<Int<kBlockN>, Int<kHeadDim>>{}));
|
|
|
|
using SmemLayoutAtomVtransposed = decltype(
|
|
composition(Swizzle<kSwizzle, 3, 3>{},
|
|
// This has to be kBlockN and not 8, otherwise we get wrong results for d=128
|
|
Layout<Shape<Int<kBlockKSmem>, Int<kBlockN>>,
|
|
Stride<_1, Int<kBlockKSmem>>>{}));
|
|
using SmemLayoutVtransposed = decltype(tile_to_shape(
|
|
SmemLayoutAtomVtransposed{},
|
|
Shape<Int<kHeadDim>, Int<kBlockN>>{}));
|
|
// Maybe the VtransposeNoSwizzle just needs to have the right shape
|
|
// And the strides don't matter?
|
|
using SmemLayoutVtransposedNoSwizzle = decltype(SmemLayoutVtransposed{}.layout_fn());
|
|
|
|
using SmemLayoutAtomO = decltype(
|
|
composition(Swizzle<kSwizzle, 3, 3>{},
|
|
Layout<Shape<Int<8>, Int<kBlockKSmem>>,
|
|
Stride<Int<kBlockKSmem>, _1>>{}));
|
|
using SmemLayoutO = decltype(tile_to_shape(
|
|
SmemLayoutAtomO{},
|
|
Shape<Int<kBlockM>, Int<kHeadDim>>{}));
|
|
using SmemCopyAtomO = Copy_Atom<DefaultCopy, elem_type>;
|
|
|
|
static constexpr int kSmemQCount = size(SmemLayoutQ{});
|
|
static constexpr int kSmemKVCount = size(SmemLayoutKV{}) * 2;
|
|
static constexpr int kSmemQSize = kSmemQCount * sizeof(Element);
|
|
static constexpr int kSmemKVSize = kSmemKVCount * sizeof(Element);
|
|
static constexpr int kSmemSize = Share_Q_K_smem ? std::max(kSmemQSize, kSmemKVSize) : kSmemQSize + kSmemKVSize;
|
|
|
|
static constexpr int kGmemElemsPerLoad = sizeof(cute::uint128_t) / sizeof(Element);
|
|
static_assert(kHeadDim % kGmemElemsPerLoad == 0, "kHeadDim must be a multiple of kGmemElemsPerLoad");
|
|
// Using kBlockKSmem here is 6-10% faster than kBlockKGmem for d=128 because of bank conflicts.
|
|
// For example, for d=128, smem is split into 2 "pages", each page takes care of columns
|
|
// 0-63 and 64-127. If we have 16 threads per row for gmem read, when we write to smem,
|
|
// thread 0 - 7 will write to the first page and thread 8 - 15 will write to the second page,
|
|
// to the same banks.
|
|
static constexpr int kGmemThreadsPerRow = kBlockKSmem / kGmemElemsPerLoad;
|
|
static_assert(kNThreads % kGmemThreadsPerRow == 0, "kNThreads must be a multiple of kGmemThreadsPerRow");
|
|
using GmemLayoutAtom = Layout<Shape <Int<kNThreads / kGmemThreadsPerRow>, Int<kGmemThreadsPerRow>>,
|
|
Stride<Int<kGmemThreadsPerRow>, _1>>;
|
|
|
|
// We use CACHEGLOBAL instead of CACHEALWAYS for both Q and K/V, since we won't be reading
|
|
// from the same address by the same threadblock. This is slightly faster.
|
|
using Gmem_copy_struct = std::conditional_t<
|
|
Has_cp_async,
|
|
SM80_CP_ASYNC_CACHEGLOBAL<cute::uint128_t>,
|
|
DefaultCopy
|
|
>;
|
|
using GmemTiledCopyQKV = decltype(
|
|
make_tiled_copy(Copy_Atom<Gmem_copy_struct, elem_type>{},
|
|
GmemLayoutAtom{},
|
|
Layout<Shape<_1, _8>>{})); // Val layout, 8 vals per read
|
|
using GmemTiledCopyO = decltype(
|
|
make_tiled_copy(Copy_Atom<DefaultCopy, elem_type>{},
|
|
GmemLayoutAtom{},
|
|
Layout<Shape<_1, _8>>{})); // Val layout, 8 vals per store
|
|
static constexpr int kGmemThreadsPerRowP = kBlockN / kGmemElemsPerLoad;
|
|
static_assert(kNThreads % kGmemThreadsPerRowP == 0, "kNThreads must be a multiple of kGmemThreadsPerRowP");
|
|
using GmemLayoutAtomP = Layout<Shape <Int<kNThreads / kGmemThreadsPerRowP>, Int<kGmemThreadsPerRowP>>,
|
|
Stride<Int<kGmemThreadsPerRowP>, _1>>;
|
|
|
|
using GmemTiledCopyP = decltype(
|
|
make_tiled_copy(Copy_Atom<DefaultCopy, elem_type>{},
|
|
GmemLayoutAtomP{},
|
|
Layout<Shape<_1, _8>>{})); // Val layout, 8 vals per store
|
|
|
|
};
|
|
|
|
////////////////////////////////////////////////////////////////////////////////////////////////////
|