Commit ef5e60f6 authored by illsilin's avatar illsilin
Browse files

Merge branch 'develop' into gfx950

parents 2cc0fa26 5e93fa9e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/ops/common/tensor_layout.hpp"
#include "ck_tile/ops/fused_moe/pipeline/fused_moegemm_pipeline_flatmm_policy.hpp"
namespace ck_tile {
/*
This pipeline deal with a gemm(actually 2 gemm) with one very small(token), one very big(weight)
we need to design the pipeline such that all waves along gemm-N dim (gemm-m only 1 wave)
<----- gemm-N ------>
+----+----+----+----+
| w0 | w1 | w2 | w3 | gemm-m
+----+----+----+----+
*/
template <typename Problem_, typename Policy_ = FusedMoeGemmPipelineFlatmmPolicy>
struct FusedMoeGemmPipeline_FlatmmUk
{
using Problem = remove_cvref_t<Problem_>;
using Policy = remove_cvref_t<Policy_>;
using BlockShape = typename Problem::BlockShape; // this is FusedMoeGemmShape
using ADataType = typename Problem::ADataType;
using GDataType = typename Problem::GDataType;
using DDataType = typename Problem::DDataType;
using AccDataType = typename Problem::AccDataType;
using ODataType = typename Problem::ODataType;
using AScaleDataType = typename Problem::AScaleDataType;
using GScaleDataType = typename Problem::GScaleDataType;
using DScaleDataType = typename Problem::DScaleDataType;
using YSmoothScaleDataType = typename Problem::YSmoothScaleDataType;
using TopkWeightDataType = typename Problem::TopkWeightDataType;
using IndexDataType = typename Problem::IndexDataType;
using YDataType = typename Problem::YDataType;
using Traits = typename Problem::Traits;
static constexpr bool IsGateOnly = Traits::IsGateOnly;
static constexpr bool UseSmoothQuant = Traits::UseSmoothQuant;
static constexpr bool PadHiddenSize = Traits::PadHiddenSize;
static constexpr bool PadIntermediateSize = Traits::PadIntermediateSize;
static constexpr index_t kAlignmentA = Policy::template GetAlignment_A<Problem>();
static constexpr index_t kAlignmentG = Policy::template GetAlignment_G<Problem>();
static constexpr index_t kAlignmentD = Policy::template GetAlignment_D<Problem>();
static constexpr index_t kAlignmentO = Policy::template GetAlignment_O<Problem>();
static constexpr index_t SLD_A = static_cast<index_t>(FusedMoeGemmPipelineSequencerEnum::SLD_A);
static constexpr index_t GLD_A = static_cast<index_t>(FusedMoeGemmPipelineSequencerEnum::GLD_A);
static constexpr index_t GLD_B = static_cast<index_t>(FusedMoeGemmPipelineSequencerEnum::GLD_B);
static constexpr index_t GST_O = static_cast<index_t>(FusedMoeGemmPipelineSequencerEnum::GST_O);
static constexpr index_t kBlockPerCu = []() {
if constexpr(Problem::kBlockPerCu != -1)
return Problem::kBlockPerCu;
else
{
// minimize occupancy
return 2;
}
}();
static constexpr const char* name = "flatmm_uk";
CK_TILE_HOST_DEVICE static constexpr ck_tile::index_t GetSmemSize()
{
constexpr index_t smem_0 = Policy::template GetUK_0<Problem>().GetSmemSize();
constexpr index_t smem_1 = Policy::template GetUK_1<Problem>().GetSmemSize();
constexpr index_t smem_bridge =
BlockShape::Block_M0 * BlockShape::Block_N0 * sizeof(YDataType);
return max(smem_0, max(smem_1, smem_bridge));
}
// this is the thread-offset along row/col
CK_TILE_HOST_DEVICE static auto GetACoord()
{
constexpr auto a_dist = Policy::template MakeGlobalTileDistribution_A<Problem>();
const auto a_coord = a_dist.calculate_index();
return a_coord;
}
// this is the thread-offset along row/col
CK_TILE_HOST_DEVICE static auto GetOCoord()
{
constexpr auto o_dist = Policy::template MakeOGlobalTileDistribution<Problem>();
const auto o_coord = o_dist.calculate_index();
return o_coord;
}
CK_TILE_DEVICE constexpr auto GetNumRowCoords_A()
{
constexpr index_t KLans = BlockShape::Block_K0 / kAlignmentA;
constexpr index_t MLans = BlockShape::BlockSize / KLans;
constexpr index_t MRepeat = BlockShape::Block_M0 / MLans;
return MRepeat;
}
// TODO: properlly support scatter/gather
CK_TILE_DEVICE auto GetRowCoords_A(index_t base_offset)
{
constexpr index_t KLans = BlockShape::Block_K0 / kAlignmentA;
constexpr index_t MLans = BlockShape::BlockSize / KLans;
constexpr index_t MRepeat = BlockShape::Block_M0 / MLans;
auto base_coord = threadIdx.x / KLans + base_offset;
array<index_t, MRepeat> coords;
static_for<0, MRepeat, 1>{}([&](auto i) { coords.at(i) = base_coord + i * MLans; });
return coords;
}
template <typename ROW_COORDS>
CK_TILE_DEVICE auto GetRowID(const ROW_COORDS coords, const IndexDataType* sorted_token_ids_ptr)
{
constexpr index_t n_size = coords.size();
array<index_t, n_size> row_ids;
static_for<0, n_size, 1>{}([&](auto i) {
row_ids.at(i) = sorted_token_ids_ptr[coords[i]]; // base_coord + i * MLans;
});
return row_ids;
}
template <typename ROW_COORDS>
CK_TILE_DEVICE auto GetWeightScale(const ROW_COORDS coords,
const TopkWeightDataType* sorted_weight_ptr)
{
constexpr index_t n_size = coords.size();
array<TopkWeightDataType, n_size> w;
static_for<0, n_size, 1>{}([&](auto i) {
w.at(i) = sorted_weight_ptr[coords[i]]; // base_coord + i * MLans;
});
return w;
}
// TODO: this row id is before shuffle atomic, need use acc distribution
CK_TILE_DEVICE auto GetRowCoords_O(index_t base_offset)
{
constexpr index_t MLanes = BlockShape::Warp_M1;
constexpr index_t Repeat_M = BlockShape::Repeat_M1;
auto base_coord = threadIdx.x % MLanes + base_offset;
array<index_t, Repeat_M> coords;
static_for<0, Repeat_M, 1>{}([&](auto i) { coords.at(i) = base_coord + i * MLanes; });
return coords;
}
template <typename Karg>
CK_TILE_DEVICE auto operator()(const Karg& kargs,
CK_TILE_LDS_ADDR void* smem,
index_t sorted_tile_id,
index_t intermediate_tile_id)
{
constexpr index_t hidden_radio_0 = IsGateOnly ? 1 : 2;
ck_tile::index_t shared_intermediate_size_0 = kargs.intermediate_size;
ck_tile::index_t shared_intermediate_size_1 = kargs.intermediate_size / hidden_radio_0;
index_t nr_0 = shared_intermediate_size_0 / BlockShape::Warp_N0; // divide N in W
index_t kr_0 = kargs.hidden_size / BlockShape::Warp_K0; // divide K in W
index_t nr_1 = kargs.hidden_size / BlockShape::Warp_N1;
index_t kr_1 = shared_intermediate_size_1 / BlockShape::Warp_K1;
const IndexDataType expert_id = __builtin_amdgcn_readfirstlane(
reinterpret_cast<const IndexDataType*>(kargs.sorted_expert_ids_ptr)[sorted_tile_id]);
index_t expert_stride_0 = shared_intermediate_size_0 * kargs.hidden_size;
index_t expert_stride_1 = shared_intermediate_size_1 * kargs.hidden_size;
// nr*kr*w
index_t interm_idx_nr0 = __builtin_amdgcn_readfirstlane(
intermediate_tile_id *
BlockShape::Block_Nr0); // intermediate_tile_id * Block_N / (N in W)
index_t interm_idx_kr1 = __builtin_amdgcn_readfirstlane(
intermediate_tile_id *
BlockShape::Block_Kr1); // intermediate_tile_id * Block_N / (N in W)
auto row_coords_a = GetRowCoords_A(sorted_tile_id * BlockShape::Block_M0);
auto row_ids_a = GetRowID(
row_coords_a, reinterpret_cast<const IndexDataType*>(kargs.sorted_token_ids_ptr));
auto a_coords = generate_tuple(
[&](auto i) {
return row_ids_a[i] * kargs.stride_token +
threadIdx.x % (BlockShape::Block_K0 / kAlignmentA) * kAlignmentA;
},
number<row_ids_a.size()>{});
auto a_res =
make_wave_buffer_resource(reinterpret_cast<const ADataType*>(kargs.a_ptr),
kargs.num_tokens * kargs.stride_token * sizeof(ADataType));
auto g_win = [&]() {
const GDataType* g_ptr = reinterpret_cast<const GDataType*>(kargs.g_ptr) +
static_cast<long_index_t>(expert_id) * expert_stride_0 +
interm_idx_nr0 * kr_0 * BlockShape::Block_W0;
auto g_view_ = make_naive_tensor_view<address_space_enum::global>(
g_ptr,
make_tuple(nr_0, kr_0, number<BlockShape::Block_W0>{}),
make_tuple(kr_0 * BlockShape::Block_W0, number<BlockShape::Block_W0>{}, 1),
number<kAlignmentG>{},
number<1>{});
auto g_window_ = make_tile_window_linear_raw(
g_view_,
make_tuple(number<BlockShape::Block_Nr0>{},
number<BlockShape::Block_Kr0>{},
number<BlockShape::Block_W0>{}),
{0, 0, 0},
Policy::template MakeGlobalTileDistribution_G<Problem>(),
sequence<0, 1, 1>{});
return g_window_;
}();
auto g_res = g_win.get_bottom_tensor_view().get_buffer_view().cached_buf_res_;
auto g_coords = generate_tuple([&](auto i) { return g_win.cached_coords_[i].get_offset(); },
number<decltype(g_win)::NumAccess_NonLinear>{});
const auto d_win = [&]() {
const DDataType* d_ptr = reinterpret_cast<const DDataType*>(kargs.d_ptr) +
static_cast<long_index_t>(expert_id) * expert_stride_1 +
interm_idx_kr1 * BlockShape::Block_W1;
// note interm_idx_nr0 is along the gemm-k dim of 2nd gemm
const auto d_view_ = make_naive_tensor_view<address_space_enum::global>(
d_ptr,
make_tuple(nr_1, kr_1, BlockShape::Block_W1),
make_tuple(kr_1 * BlockShape::Block_W1, BlockShape::Block_W1, 1),
number<kAlignmentD>{},
number<1>{});
const auto d_window_ = make_tile_window_linear_raw(
d_view_,
make_tuple(number<BlockShape::Block_Nr1>{},
number<BlockShape::Block_Kr1>{},
number<BlockShape::Block_W1>{}),
{0, 0, 0},
Policy::template MakeGlobalTileDistribution_D<Problem>(),
sequence<0, 1, 1>{});
return d_window_;
}();
auto d_res = d_win.get_bottom_tensor_view().get_buffer_view().cached_buf_res_;
// TODO: load D order is N0.K0...127, N64.K0...127, N0.K128...255, N64.K128...255
// block-k=512, block-n=128
// wg |<----- W_ ----->|
// Nr(2)*Nw(4)* Kr *Kr0(4)*Kr1(4) * [Kl(4)*Nl(16)*Kv(8)]->one issue
// y p y y p p y
// 1 2 0(imm)
auto d_coords = [&]() {
constexpr index_t Nr_ = 2;
constexpr index_t Nw_ = 4;
constexpr index_t Kr0_ = 4;
constexpr index_t Kr1_ = 4;
constexpr index_t Kl_ = 4;
constexpr index_t Nl_ = 16;
constexpr index_t Kv_ = 8;
constexpr index_t W_ = Kl_ * Nl_ * Kv_;
constexpr index_t num_offsets_ = Nr_ * Kr0_;
index_t base_os_ = (threadIdx.x % 64) * Kv_ + (threadIdx.x / 64) *
shared_intermediate_size_1 *
Nl_; // Kr0_ * Kr1_ * W_;
return generate_tuple(
[&](auto i) {
constexpr auto i_nr_ = number<i % Nr_>{};
constexpr auto i_kr0_ = number<i / Nr_>{};
return i_nr_ * shared_intermediate_size_1 * Nw_ * Nl_ + i_kr0_ * Kr1_ * W_ +
base_os_;
},
number<num_offsets_>{});
}();
auto o_coords = generate_tuple(
[&](auto i) {
return row_ids_a[i] * kargs.stride_token +
threadIdx.x % (BlockShape::Block_N1 / kAlignmentO) * kAlignmentO;
},
number<row_ids_a.size()>{});
auto o_flags =
generate_tuple([&](auto i) { return cmp_lt_to_exec(row_ids_a[i], kargs.num_tokens); },
number<row_ids_a.size()>{});
auto bridge_sst_win = [&]() {
constexpr auto desc_ = Policy::template MakeBridgeLdsStoreForUKDesc<Problem>();
constexpr auto dist_ = Policy::template GetUK_0<Problem>().MakeCBlockDist();
return make_tile_window_linear(make_tensor_view<address_space_enum::lds>(
reinterpret_cast<YDataType*>(smem), desc_),
desc_.get_lengths(),
{0, 0},
dist_);
}();
auto o_res =
make_wave_buffer_resource(reinterpret_cast<const ODataType*>(kargs.o_ptr),
kargs.num_tokens * kargs.stride_token * sizeof(ODataType));
auto row_coords_o = GetRowCoords_O(sorted_tile_id * BlockShape::Block_M0);
auto w_scale = GetWeightScale(
row_coords_o, reinterpret_cast<const TopkWeightDataType*>(kargs.sorted_weight_ptr));
auto uk_0 = Policy::template GetUK_0<Problem>();
auto acc_0 = uk_0(a_res,
a_coords,
g_res,
g_coords,
smem,
kargs.hidden_size,
BlockShape::Block_K0, // tile offset for B matrix each unroll
BlockShape::Block_Kr0 *
BlockShape::Block_W0); // tile offset for B matrix each unroll
sweep_tile(
acc_0,
[&](auto idx0, auto idx1) {
fp32x2_t v_{acc_0(idx0), acc_0(idx1)};
typename Problem::GateActivation{}(v_, v_);
acc_0(idx0) = v_.x;
acc_0(idx1) = v_.y;
},
sequence<1, 2>{});
auto y_pre = cast_tile<YDataType>(acc_0);
block_sync_lds();
store_tile(bridge_sst_win, y_pre);
block_sync_lds();
auto uk_1 = Policy::template GetUK_1<Problem>();
uk_1(d_res,
d_coords,
o_res,
o_coords,
o_flags,
smem,
kargs.hidden_size, // total n number
w_scale,
BlockShape::Block_Nr1 * kr_1 * BlockShape::Block_W1, // along N
BlockShape::Block_N1); // along N
}
};
} // namespace ck_tile
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
namespace ck_tile {
// TODO: alow 2 gemm have different type
template <typename ADataType_,
typename GDataType_,
typename DDataType_,
typename AccDataType_,
typename ODataType_,
typename AScaleDataType_,
typename GScaleDataType_,
typename DScaleDataType_,
typename YSmoothScaleDataType_,
typename TopkWeightDataType_,
typename IndexDataType_, // data type for all indexing
typename GateActivation_, // = ck_tile::element_wise::Silu,
typename BlockShape_, // shoule be FusedMoeGemmShape
typename Traits_>
struct FusedMoeGemmPipelineProblem
{
using ADataType = remove_cvref_t<ADataType_>;
using GDataType = remove_cvref_t<GDataType_>;
using DDataType = remove_cvref_t<DDataType_>;
using AccDataType = remove_cvref_t<AccDataType_>;
using ODataType = remove_cvref_t<ODataType_>;
using AScaleDataType = remove_cvref_t<AScaleDataType_>;
using GScaleDataType = remove_cvref_t<GScaleDataType_>;
using DScaleDataType = remove_cvref_t<DScaleDataType_>;
using YSmoothScaleDataType = remove_cvref_t<YSmoothScaleDataType_>;
using TopkWeightDataType = remove_cvref_t<TopkWeightDataType_>;
using IndexDataType = remove_cvref_t<IndexDataType_>;
// the input for next gemm should have same time as
using YDataType = ADataType;
using GateActivation = remove_cvref_t<GateActivation_>;
using BlockShape = remove_cvref_t<BlockShape_>;
using Traits = remove_cvref_t<Traits_>;
};
} // namespace ck_tile
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
namespace ck_tile {
enum class FusedMoeGemmWeightPermuteEnum
{
// permute_b_n0_k0_n1_k1_n2_k2 = 0, // 0,1,4,2,5,3,6
// permute_b_n0_n1_k0_k1_n2_k2 = 1, // 0,1,2,4,5,3,6
no_permute = 0,
b_nr_kr_kw_nw_kv = 1, // 0,1,3,4,2,5
b_nr_kr_waveflatten = b_nr_kr_kw_nw_kv,
};
template <bool IsGateOnly_,
bool UseSmoothQuant_,
index_t OAtomic_, // 0-no atomic, 1-atomic-pk-f16/bf16, 2-atomic-f32
FusedMoeGemmWeightPermuteEnum PermuteEnum_ =
FusedMoeGemmWeightPermuteEnum::b_nr_kr_waveflatten,
bool PadHiddenSize_ = false,
bool PadIntermediateSize_ = false>
struct FusedMoeGemmTraits
{
// Gate+Up or Gate only
static constexpr bool IsGateOnly = IsGateOnly_;
static constexpr bool UseSmoothQuant = UseSmoothQuant_;
static constexpr index_t OAtomic = OAtomic_;
static constexpr FusedMoeGemmWeightPermuteEnum PermuteEnum = PermuteEnum_;
static constexpr bool PadHiddenSize = PadHiddenSize_;
static constexpr bool PadIntermediateSize = PadIntermediateSize_;
};
// Note: this need to be a bit mask
enum class FusedMoeGemmPipelineSequencerEnum
{
SLD_A = 1 << 0, // shared load a
SLD_B = 1 << 1,
GLD_A = 1 << 2, // global load a
GLD_B = 1 << 3,
SST_A = 1 << 4, // shared store a
SST_B = 1 << 5,
GST_O = 1 << 6, // global store out
};
} // namespace ck_tile
......@@ -22,8 +22,13 @@
#include "ck_tile/ops/gemm/block/block_gemm_asmem_bsmem_creg_v1_custom_policy.hpp"
#include "ck_tile/ops/gemm/block/block_gemm_asmem_bsmem_creg_v1_default_policy.hpp"
#include "ck_tile/ops/gemm/block/block_gemm_problem.hpp"
#include "ck_tile/ops/gemm/block/block_universal_gemm_as_bs_cr.hpp"
#include "ck_tile/ops/gemm/kernel/gemm_kernel.hpp"
#include "ck_tile/ops/gemm/kernel/gemm_tile_partitioner.hpp"
#include "ck_tile/ops/gemm/kernel/grouped_gemm_kernel.hpp"
#include "ck_tile/ops/gemm/kernel/batched_gemm_kernel.hpp"
#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_ag_bg_cr_base.hpp"
#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_ag_bg_cr_comp_v3.hpp"
#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_ag_bg_cr_mem.hpp"
#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_ag_bg_cr_scheduler.hpp"
#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_agmem_bgmem_creg_v1.hpp"
......
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/ops/gemm/block/block_gemm_asmem_bsmem_creg_v1_default_policy.hpp"
#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_ag_bg_cr_scheduler.hpp"
namespace ck_tile {
// A is block window on shared memory
// B is block window on shared memory
// C is block distributed tensor
template <typename Problem_, typename Policy_ = BlockGemmASmemBSmemCRegV1DefaultPolicy>
struct BlockUniversalGemmAsBsCr
{
private:
// TODO: This should be in Policy - UniversalGemmPolicyBase ?
template <typename PipelineProblem_, typename GemmPolicy_>
struct GemmTraits_
{
using Problem = remove_cvref_t<PipelineProblem_>;
using Policy = remove_cvref_t<GemmPolicy_>;
using ADataType = remove_cvref_t<typename Problem::ADataType>;
using BDataType = remove_cvref_t<typename Problem::BDataType>;
using CDataType = remove_cvref_t<typename Problem::CDataType>;
using BlockGemmShape = remove_cvref_t<typename Problem::BlockGemmShape>;
static constexpr index_t kBlockSize = Problem::kBlockSize;
static constexpr auto Scheduler = Problem::Scheduler;
static constexpr index_t MPerBlock = BlockGemmShape::kM;
static constexpr index_t NPerBlock = BlockGemmShape::kN;
static constexpr index_t KPerBlock = BlockGemmShape::kK;
static constexpr auto config = Policy::template GetWarpGemmMWarpNWarp<Problem>();
using WarpGemm = remove_cvref_t<decltype(config.template at<0>())>;
static constexpr index_t MWarp = config.template at<1>();
static constexpr index_t NWarp = config.template at<2>();
using I0 = number<0>;
using I1 = number<1>;
static_assert(MWarp == BlockGemmShape::BlockWarps::at(I0{}),
"Error! WarpGemm's MWarp is not consisten with BlockGemmShape!");
static_assert(NWarp == BlockGemmShape::BlockWarps::at(I1{}),
"Error! WarpGemm's NWarp is not consisten with BlockGemmShape!");
static_assert(WarpGemm::kM == BlockGemmShape::WarpTile::at(I0{}),
"Error! WarpGemm's M is not consisten with BlockGemmShape!");
static_assert(WarpGemm::kN == BlockGemmShape::WarpTile::at(I1{}),
"Error! WarpGemm's N is not consisten with BlockGemmShape!");
static constexpr index_t MIterPerWarp = MPerBlock / (MWarp * WarpGemm::kM);
static constexpr index_t NIterPerWarp = NPerBlock / (NWarp * WarpGemm::kN);
static constexpr index_t KIterPerWarp = KPerBlock / WarpGemm::kK;
static_assert(MIterPerWarp * MWarp * WarpGemm::kM == MPerBlock,
"Error! Warps should cover all Block tile!");
static_assert(NIterPerWarp * NWarp * WarpGemm::kN == NPerBlock,
"Error! Warps should cover all Block tile!");
static constexpr index_t MPerBlockPerIter = MWarp * WarpGemm::kM;
static constexpr index_t NPerBlockPerIter = NWarp * WarpGemm::kN;
static constexpr index_t KPerBlockPerIter = WarpGemm::kK;
using AWarpTileDistr = remove_cvref_t<decltype(make_static_tile_distribution(
typename WarpGemm::AWarpDstrEncoding{}))>;
using BWarpTileDistr = remove_cvref_t<decltype(make_static_tile_distribution(
typename WarpGemm::BWarpDstrEncoding{}))>;
using AWarpTile =
remove_cvref_t<decltype(make_static_distributed_tensor<ADataType>(AWarpTileDistr{}))>;
using BWarpTile =
remove_cvref_t<decltype(make_static_distributed_tensor<BDataType>(BWarpTileDistr{}))>;
// TODO: Should we have two policies? Interwave & Intrawave ??
static constexpr index_t InterWaveSchedulingMacClusters = 1;
static constexpr index_t KPack = WarpGemm::kKPerThread;
static constexpr index_t KPerThread = KPerBlock / WarpGemm::kK * KPack;
static constexpr index_t KRepeat = KPerThread / KPack;
};
public:
using Traits = GemmTraits_<Problem_, Policy_>;
using ADataType = remove_cvref_t<typename Traits::ADataType>;
using BDataType = remove_cvref_t<typename Traits::BDataType>;
using CDataType = remove_cvref_t<typename Traits::CDataType>;
using WarpGemm = remove_cvref_t<typename Traits::WarpGemm>;
static constexpr index_t KIterPerWarp = Traits::KIterPerWarp;
static constexpr index_t MIterPerWarp = Traits::MIterPerWarp;
static constexpr index_t NIterPerWarp = Traits::NIterPerWarp;
static constexpr index_t MWarp = Traits::MWarp;
static constexpr index_t NWarp = Traits::NWarp;
static constexpr auto Scheduler = Traits::Scheduler;
using I0 = number<0>;
using I1 = number<1>;
private:
template <GemmPipelineScheduler Scheduler, typename GemmTraits>
struct BlockGemmImpl
{
};
template <typename GemmTraits>
struct BlockGemmImpl<GemmPipelineScheduler::Default, GemmTraits>
{
// C += A * B
template <typename CBlockTensor, typename ASmemBlockWindow, typename BSmemBlockWindow>
CK_TILE_DEVICE void operator()(CBlockTensor& c_block_tensor,
const ASmemBlockWindow& a_block_window,
const BSmemBlockWindow& b_block_window)
{
static_assert(std::is_same_v<CDataType, typename CBlockTensor::DataType>,
"The CDataType as defined in traits should be the same as correspoinding "
"C block tensor data type!");
static_assert(std::is_same_v<ADataType, typename ASmemBlockWindow::DataType> &&
std::is_same_v<BDataType, typename BSmemBlockWindow::DataType>,
"The ADataType and BDataType as defined in "
"traits should be the same as correspoinding block window data type!");
static_assert(
GemmTraits::MPerBlock == ASmemBlockWindow{}.get_window_lengths()[I0{}] &&
GemmTraits::NPerBlock == BSmemBlockWindow{}.get_window_lengths()[I0{}] &&
GemmTraits::KPerBlock == ASmemBlockWindow{}.get_window_lengths()[I1{}],
"MPerBlock, NPerBlock, KPerBlock defined in "
" BlockGemmShape are different from A/B block smem windows apropriate dims!");
const index_t iMWarp = get_warp_id() / NWarp;
const index_t iNWarp = get_warp_id() - (iMWarp * NWarp);
// TODO: refactor warp_window tile type to class member as it should be
// compile-time known information.
auto a_warp_window_tmp = make_tile_window(
a_block_window.get_bottom_tensor_view(),
make_tuple(number<WarpGemm::kM>{}, number<WarpGemm::kK>{}),
a_block_window.get_window_origin() + multi_index<2>{iMWarp * WarpGemm::kM, 0},
make_static_tile_distribution(typename WarpGemm::AWarpDstrEncoding{}));
using AWarpWindow = remove_cvref_t<decltype(a_warp_window_tmp)>;
static_assert(GemmTraits::AWarpTile::get_num_of_dimension() ==
AWarpWindow::get_num_of_dimension(),
"AWarpWindow number of dimensions must be equal to "
"AWarpTile number of dimensions!");
static_assert(GemmTraits::AWarpTile::get_lengths() ==
AWarpWindow{}.get_window_lengths(),
"AWarpWindow lengths must be equal to AWarpTile lengths!");
statically_indexed_array<
statically_indexed_array<AWarpWindow, GemmTraits::KIterPerWarp>,
MIterPerWarp>
a_warp_windows;
// construct B-warp-window
auto b_warp_window_tmp = make_tile_window(
b_block_window.get_bottom_tensor_view(),
make_tuple(number<WarpGemm::kN>{}, number<WarpGemm::kK>{}),
b_block_window.get_window_origin() + multi_index<2>{iNWarp * WarpGemm::kN, 0},
make_static_tile_distribution(typename WarpGemm::BWarpDstrEncoding{}));
using BWarpWindow = remove_cvref_t<decltype(b_warp_window_tmp)>;
static_assert(GemmTraits::BWarpTile::get_num_of_dimension() ==
BWarpWindow::get_num_of_dimension(),
"BWarpWindow number of dimensions must be equal to "
"BWarpTile number of dimensions!");
static_assert(GemmTraits::BWarpTile::get_lengths() ==
BWarpWindow{}.get_window_lengths(),
"BWarpWindow lengths must be equal to BWarpTile lengths!");
statically_indexed_array<
statically_indexed_array<BWarpWindow, GemmTraits::KIterPerWarp>,
NIterPerWarp>
b_warp_windows;
static_for<0, MIterPerWarp, 1>{}([&](auto mIter) {
static_for<0, GemmTraits::KIterPerWarp, 1>{}([&](auto kIter) {
a_warp_windows(mIter)(kIter) = a_warp_window_tmp;
// TODO: I don't have to move 0,0 window!
move_tile_window(a_warp_windows(mIter)(kIter),
{mIter * GemmTraits::MPerBlockPerIter,
kIter * GemmTraits::KPerBlockPerIter});
});
});
static_for<0, NIterPerWarp, 1>{}([&](auto nIter) {
static_for<0, GemmTraits::KIterPerWarp, 1>{}([&](auto kIter) {
b_warp_windows(nIter)(kIter) = b_warp_window_tmp;
move_tile_window(b_warp_windows(nIter)(kIter),
{nIter * GemmTraits::NPerBlockPerIter,
kIter * GemmTraits::KPerBlockPerIter});
});
});
using CWarpDstr = typename WarpGemm::CWarpDstr;
using CWarpTensor = typename WarpGemm::CWarpTensor;
constexpr auto c_warp_y_lengths =
to_sequence(CWarpDstr{}.get_ys_to_d_descriptor().get_lengths());
constexpr auto c_warp_y_index_zeros = uniform_sequence_gen_t<CWarpDstr::NDimY, 0>{};
// hot loop:
static_for<0, GemmTraits::KIterPerWarp, 1>{}([&](auto kIter) {
static_for<0, MIterPerWarp, 1>{}([&](auto mIter) {
const auto a_warp_tile = load_tile(a_warp_windows(mIter)(kIter));
static_for<0, NIterPerWarp, 1>{}([&](auto nIter) {
const auto b_warp_tile = load_tile(b_warp_windows(nIter)(kIter));
// read C warp tensor from C block tensor-
CWarpTensor c_warp_tensor;
c_warp_tensor.get_thread_buffer() = c_block_tensor.get_y_sliced_thread_data(
merge_sequences(sequence<mIter, nIter>{}, c_warp_y_index_zeros),
merge_sequences(sequence<1, 1>{}, c_warp_y_lengths));
// warp GEMM
WarpGemm{}(c_warp_tensor, a_warp_tile, b_warp_tile);
// write C warp tensor into C block tensor
c_block_tensor.set_y_sliced_thread_data(
merge_sequences(sequence<mIter, nIter>{}, c_warp_y_index_zeros),
merge_sequences(sequence<1, 1>{}, c_warp_y_lengths),
c_warp_tensor.get_thread_buffer());
});
});
});
}
};
template <typename GemmTraits>
struct BlockGemmImpl<GemmPipelineScheduler::Intrawave, GemmTraits>
{
statically_indexed_array<
statically_indexed_array<typename GemmTraits::AWarpTile, KIterPerWarp>,
MIterPerWarp>
a_warp_tiles_;
statically_indexed_array<
statically_indexed_array<typename GemmTraits::BWarpTile, KIterPerWarp>,
NIterPerWarp>
b_warp_tiles_;
template <typename ASmemBlockWindow, typename BSmemBlockWindow>
CK_TILE_DEVICE void LocalPrefetch(const ASmemBlockWindow& a_block_window,
const BSmemBlockWindow& b_block_window)
{
static_assert(
GemmTraits::MPerBlock == ASmemBlockWindow{}.get_window_lengths()[I0{}] &&
GemmTraits::NPerBlock == BSmemBlockWindow{}.get_window_lengths()[I0{}] &&
GemmTraits::KPerBlock == ASmemBlockWindow{}.get_window_lengths()[I1{}],
"MPerBlock, NPerBlock, KPerBlock defined in "
" BlockGemmShape are different from A/B block smem windows apropriate dims!");
static_assert(std::is_same_v<ADataType, typename ASmemBlockWindow::DataType> &&
std::is_same_v<BDataType, typename BSmemBlockWindow::DataType>,
"The ADataType and BDataType as defined in "
"traits should be the same as correspoinding block window data type!");
const index_t iMWarp = get_warp_id() / NWarp;
const index_t iNWarp = get_warp_id() - (iMWarp * NWarp);
// TODO: refactor warp_window tile type to class member as it should be
// compile-time known information.
auto a_warp_window_tmp = make_tile_window(
a_block_window.get_bottom_tensor_view(),
make_tuple(number<WarpGemm::kM>{}, number<WarpGemm::kK>{}),
a_block_window.get_window_origin() + multi_index<2>{iMWarp * WarpGemm::kM, 0},
make_static_tile_distribution(typename WarpGemm::AWarpDstrEncoding{}));
using AWarpWindow = remove_cvref_t<decltype(a_warp_window_tmp)>;
static_assert(GemmTraits::AWarpTile::get_num_of_dimension() ==
AWarpWindow::get_num_of_dimension(),
"AWarpWindow number of dimensions must be equal to "
"AWarpTile number of dimensions!");
static_assert(GemmTraits::AWarpTile::get_lengths() ==
AWarpWindow{}.get_window_lengths(),
"AWarpWindow lengths must be equal to AWarpTile lengths!");
statically_indexed_array<statically_indexed_array<AWarpWindow, KIterPerWarp>,
MIterPerWarp>
a_warp_windows;
// construct B-warp-window
auto b_warp_window_tmp = make_tile_window(
b_block_window.get_bottom_tensor_view(),
make_tuple(number<WarpGemm::kN>{}, number<WarpGemm::kK>{}),
b_block_window.get_window_origin() + multi_index<2>{iNWarp * WarpGemm::kN, 0},
make_static_tile_distribution(typename WarpGemm::BWarpDstrEncoding{}));
using BWarpWindow = remove_cvref_t<decltype(b_warp_window_tmp)>;
static_assert(GemmTraits::BWarpTile::get_num_of_dimension() ==
BWarpWindow::get_num_of_dimension(),
"BWarpWindow number of dimensions must be equal to "
"BWarpTile number of dimensions!");
static_assert(GemmTraits::BWarpTile::get_lengths() ==
BWarpWindow{}.get_window_lengths(),
"BWarpWindow lengths must be equal to BWarpTile lengths!");
statically_indexed_array<statically_indexed_array<BWarpWindow, KIterPerWarp>,
NIterPerWarp>
b_warp_windows;
static_for<0, MIterPerWarp, 1>{}([&](auto mIter) {
static_for<0, KIterPerWarp, 1>{}([&](auto kIter) {
a_warp_windows(mIter)(kIter) = a_warp_window_tmp;
// TODO: I don't have to move 0,0 window!
move_tile_window(a_warp_windows(mIter)(kIter),
{mIter * GemmTraits::MPerBlockPerIter,
kIter * GemmTraits::KPerBlockPerIter});
});
});
static_for<0, NIterPerWarp, 1>{}([&](auto nIter) {
static_for<0, KIterPerWarp, 1>{}([&](auto kIter) {
b_warp_windows(nIter)(kIter) = b_warp_window_tmp;
move_tile_window(b_warp_windows(nIter)(kIter),
{nIter * GemmTraits::NPerBlockPerIter,
kIter * GemmTraits::KPerBlockPerIter});
});
});
static_for<0, KIterPerWarp, 1>{}([&](auto kIter) {
static_for<0, MIterPerWarp, 1>{}([&](auto mIter) {
// read A warp tensor from A block window
load_tile(a_warp_tiles_(mIter)(kIter), a_warp_windows(mIter)(kIter));
});
static_for<0, NIterPerWarp, 1>{}([&](auto nIter) {
// read B warp tensor from B Block window
load_tile(b_warp_tiles_(nIter)(kIter), b_warp_windows(nIter)(kIter));
});
});
}
// C += A * B
template <typename CBlockTensor, typename ASmemBlockWindow, typename BSmemBlockWindow>
CK_TILE_DEVICE void operator()(CBlockTensor& c_block_tensor,
[[maybe_unused]] const ASmemBlockWindow& a_block_window,
[[maybe_unused]] const BSmemBlockWindow& b_block_window)
{
static_assert(std::is_same_v<CDataType, typename CBlockTensor::DataType>,
"The CDataType as defined in traits should be the same as correspoinding "
"C block tensor data type!");
using CWarpDstr = typename WarpGemm::CWarpDstr;
using CWarpTensor = typename WarpGemm::CWarpTensor;
constexpr auto c_warp_y_lengths =
to_sequence(CWarpDstr{}.get_ys_to_d_descriptor().get_lengths());
constexpr auto c_warp_y_index_zeros = uniform_sequence_gen_t<CWarpDstr::NDimY, 0>{};
// hot loop:
static_for<0, KIterPerWarp, 1>{}([&](auto kIter) {
static_for<0, MIterPerWarp, 1>{}([&](auto mIter) {
static_for<0, NIterPerWarp, 1>{}([&](auto nIter) {
// read C warp tensor from C block tensor-
CWarpTensor c_warp_tensor;
c_warp_tensor.get_thread_buffer() = c_block_tensor.get_y_sliced_thread_data(
merge_sequences(sequence<mIter, nIter>{}, c_warp_y_index_zeros),
merge_sequences(sequence<1, 1>{}, c_warp_y_lengths));
// warp GEMM
WarpGemm{}(c_warp_tensor,
a_warp_tiles_[mIter][kIter],
b_warp_tiles_[nIter][kIter]);
// write C warp tensor into C block tensor
c_block_tensor.set_y_sliced_thread_data(
merge_sequences(sequence<mIter, nIter>{}, c_warp_y_index_zeros),
merge_sequences(sequence<1, 1>{}, c_warp_y_lengths),
c_warp_tensor.get_thread_buffer());
});
});
});
}
};
template <typename GemmTraits>
struct BlockGemmImpl<GemmPipelineScheduler::Interwave, GemmTraits>
{
static constexpr index_t KPerThread = GemmTraits::KPerThread;
static constexpr index_t NumMacClusters = GemmTraits::InterWaveSchedulingMacClusters;
static constexpr index_t KPerInnerLoop =
ck_tile::max(KPerThread / NumMacClusters, GemmTraits::KPack);
// TODO: do we really need this?? Are there any cases when this would be >=1 ??
// Would we need InterWaveSchedulingMacClusters > 1 ???
static constexpr index_t KRepeat = KPerThread / KPerInnerLoop;
static constexpr index_t KInnerLoopIter = KPerInnerLoop / GemmTraits::KPack;
statically_indexed_array<
statically_indexed_array<typename GemmTraits::AWarpTile, KInnerLoopIter>,
MIterPerWarp>
a_warp_tiles_;
statically_indexed_array<
statically_indexed_array<typename GemmTraits::BWarpTile, KInnerLoopIter>,
NIterPerWarp>
b_warp_tiles_;
template <index_t KIdx, typename ASmemBlockWindow, typename BSmemBlockWindow>
CK_TILE_DEVICE void LocalPrefetch(const ASmemBlockWindow& a_block_window,
const BSmemBlockWindow& b_block_window)
{
static_assert(
GemmTraits::MPerBlock == ASmemBlockWindow{}.get_window_lengths()[I0{}] &&
GemmTraits::NPerBlock == BSmemBlockWindow{}.get_window_lengths()[I0{}] &&
GemmTraits::KPerBlock == ASmemBlockWindow{}.get_window_lengths()[I1{}],
"MPerBlock, NPerBlock, KPerBlock defined in "
" BlockGemmShape are different from A/B block smem windows apropriate dims!");
static_assert(std::is_same_v<ADataType, typename ASmemBlockWindow::DataType> &&
std::is_same_v<BDataType, typename BSmemBlockWindow::DataType>,
"The ADataType and BDataType as defined in "
"traits should be the same as correspoinding block window data type!");
const index_t iMWarp = get_warp_id() / NWarp;
const index_t iNWarp = get_warp_id() - (iMWarp * NWarp);
// TODO: refactor warp_window tile type to class member as it should be
// compile-time known information.
auto a_warp_window_tmp = make_tile_window(
a_block_window.get_bottom_tensor_view(),
make_tuple(number<WarpGemm::kM>{}, number<WarpGemm::kK>{}),
a_block_window.get_window_origin() +
multi_index<2>{iMWarp * WarpGemm::kM, KIdx * KPerInnerLoop},
make_static_tile_distribution(typename WarpGemm::AWarpDstrEncoding{}));
using AWarpWindow = remove_cvref_t<decltype(a_warp_window_tmp)>;
static_assert(GemmTraits::AWarpTile::get_num_of_dimension() ==
AWarpWindow::get_num_of_dimension(),
"AWarpWindow number of dimensions must be equal to "
"AWarpTile number of dimensions!");
static_assert(GemmTraits::AWarpTile::get_lengths() ==
AWarpWindow{}.get_window_lengths(),
"AWarpWindow lengths must be equal to AWarpTile lengths!");
statically_indexed_array<statically_indexed_array<AWarpWindow, KInnerLoopIter>,
MIterPerWarp>
a_warp_windows;
// construct B-warp-window
auto b_warp_window_tmp = make_tile_window(
b_block_window.get_bottom_tensor_view(),
make_tuple(number<WarpGemm::kN>{}, number<WarpGemm::kK>{}),
b_block_window.get_window_origin() +
multi_index<2>{iNWarp * WarpGemm::kN, KIdx * KPerInnerLoop},
make_static_tile_distribution(typename WarpGemm::BWarpDstrEncoding{}));
using BWarpWindow = remove_cvref_t<decltype(b_warp_window_tmp)>;
static_assert(GemmTraits::BWarpTile::get_num_of_dimension() ==
BWarpWindow::get_num_of_dimension(),
"BWarpWindow number of dimensions must be equal to "
"BWarpTile number of dimensions!");
static_assert(GemmTraits::BWarpTile::get_lengths() ==
BWarpWindow{}.get_window_lengths(),
"BWarpWindow lengths must be equal to BWarpTile lengths!");
statically_indexed_array<statically_indexed_array<BWarpWindow, KInnerLoopIter>,
NIterPerWarp>
b_warp_windows;
static_for<0, MIterPerWarp, 1>{}([&](auto mIter) {
static_for<0, KInnerLoopIter, 1>{}([&](auto kIter) {
a_warp_windows(mIter)(kIter) = a_warp_window_tmp;
move_tile_window(a_warp_windows(mIter)(kIter),
{mIter * GemmTraits::MPerBlockPerIter,
kIter * GemmTraits::KPerBlockPerIter});
});
});
static_for<0, NIterPerWarp, 1>{}([&](auto nIter) {
static_for<0, KInnerLoopIter, 1>{}([&](auto kIter) {
b_warp_windows(nIter)(kIter) = b_warp_window_tmp;
move_tile_window(b_warp_windows(nIter)(kIter),
{nIter * GemmTraits::NPerBlockPerIter,
kIter * GemmTraits::KPerBlockPerIter});
});
});
// TODO check if a_warp_tiles has same desc as a_warp_window
static_for<0, KInnerLoopIter, 1>{}([&](auto kIter) {
static_for<0, MIterPerWarp, 1>{}([&](auto mIter) {
// read A warp tensor from A block window
load_tile(a_warp_tiles_(mIter)(kIter), a_warp_windows(mIter)(kIter));
});
static_for<0, NIterPerWarp, 1>{}([&](auto nIter) {
// read B warp tensor from B Block window
load_tile(b_warp_tiles_(nIter)(kIter), b_warp_windows(nIter)(kIter));
});
});
}
// C += A * B
template <typename CBlockTensor, typename ASmemBlockWindow, typename BSmemBlockWindow>
CK_TILE_DEVICE void operator()(CBlockTensor& c_block_tensor,
const ASmemBlockWindow& a_block_window,
const BSmemBlockWindow& b_block_window)
{
static_assert(std::is_same_v<CDataType, typename CBlockTensor::DataType>,
"The CDataType as defined in traits should be the same as correspoinding "
"C block tensor data type!");
using CWarpDstr = typename WarpGemm::CWarpDstr;
using CWarpTensor = typename WarpGemm::CWarpTensor;
constexpr auto c_warp_y_lengths =
to_sequence(CWarpDstr{}.get_ys_to_d_descriptor().get_lengths());
constexpr auto c_warp_y_index_zeros = uniform_sequence_gen_t<CWarpDstr::NDimY, 0>{};
// hot loop:
static_for<0, KRepeat, 1>{}([&](auto kIter) {
LocalPrefetch<kIter.value>(a_block_window, b_block_window);
__builtin_amdgcn_sched_barrier(0);
// NOTE: Synchronize threads in a workgroup at the start of each MAC
// cluster, but except the first, as we can shorten non-MAC cluster a bit
// and there's no observable negative impact. The desired effect is waves in
// a workgroup executing MAC in sync. This avoids some out-of-sync waves
// hijacking MAC resource from other workgroups and reducing the chance of
// latency hiding by waiting for the rest of the workgroup at the eventual
// sync point.
if constexpr(kIter.value != 0 || KRepeat == 1)
{
__builtin_amdgcn_s_barrier();
__builtin_amdgcn_sched_barrier(0);
}
static_for<0, KInnerLoopIter, 1>{}([&](auto kInnerIter) {
static_for<0, MIterPerWarp, 1>{}([&](auto mIter) {
static_for<0, NIterPerWarp, 1>{}([&](auto nIter) {
// read C warp tensor from C block tensor-
CWarpTensor c_warp_tensor;
c_warp_tensor.get_thread_buffer() =
c_block_tensor.get_y_sliced_thread_data(
merge_sequences(sequence<mIter, nIter>{}, c_warp_y_index_zeros),
merge_sequences(sequence<1, 1>{}, c_warp_y_lengths));
// The block_sync_lds() here performs double duty:
// A) safeguard against data hazard because barrier from
// blockwise_gemm is moved here B) reduce VMEM FIFO congestion
// by applying small delays to different wavefronts It is
// performed near the end of MAC cluster to minimize lgkmcnt
// penalty
if constexpr(kIter.value == KRepeat - 1 &&
kInnerIter.value == KInnerLoopIter - 1 &&
mIter.value == MIterPerWarp - 1 &&
nIter.value == NIterPerWarp - 1)
{
__builtin_amdgcn_sched_barrier(0);
block_sync_lds();
__builtin_amdgcn_sched_barrier(0);
}
// warp GEMM
WarpGemm{}(c_warp_tensor,
a_warp_tiles_[mIter][kInnerIter],
b_warp_tiles_[nIter][kInnerIter]);
// write C warp tensor into C block tensor
c_block_tensor.set_y_sliced_thread_data(
merge_sequences(sequence<mIter, nIter>{}, c_warp_y_index_zeros),
merge_sequences(sequence<1, 1>{}, c_warp_y_lengths),
c_warp_tensor.get_thread_buffer());
if constexpr(kInnerIter.value == 0 && mIter.value == 0 &&
nIter.value == 0)
{
__builtin_amdgcn_sched_barrier(0);
__builtin_amdgcn_s_setprio(1);
__builtin_amdgcn_sched_barrier(0);
}
});
});
});
__builtin_amdgcn_sched_barrier(0);
__builtin_amdgcn_s_setprio(0);
__builtin_amdgcn_sched_barrier(0);
});
}
};
public:
CK_TILE_DEVICE static constexpr auto MakeCBlockTile()
{
constexpr auto c_block_outer_dstr_encoding = tile_distribution_encoding<
sequence<>,
tuple<sequence<MIterPerWarp, MWarp>, sequence<NIterPerWarp, NWarp>>,
tuple<sequence<1, 2>>,
tuple<sequence<1, 1>>,
sequence<1, 2>,
sequence<0, 0>>{};
constexpr auto c_block_dstr_encode = detail::make_embed_tile_distribution_encoding(
c_block_outer_dstr_encoding, typename WarpGemm::CWarpDstrEncoding{});
constexpr auto c_block_dstr = make_static_tile_distribution(c_block_dstr_encode);
auto c_block_tensor = make_static_distributed_tensor<CDataType>(c_block_dstr);
return c_block_tensor;
}
template <typename ASmemBlockWindow, typename BSmemBlockWindow>
CK_TILE_DEVICE void LocalPrefetch(const ASmemBlockWindow& a_block_window,
const BSmemBlockWindow& b_block_window)
{
block_gemm_impl_.LocalPrefetch(a_block_window, b_block_window);
}
// C += A * B
template <typename CBlockTensor, typename ASmemBlockWindow, typename BSmemBlockWindow>
CK_TILE_DEVICE void operator()(CBlockTensor& c_block_tensor,
const ASmemBlockWindow& a_block_window,
const BSmemBlockWindow& b_block_window)
{
block_gemm_impl_(c_block_tensor, a_block_window, b_block_window);
}
// C = A * B
template <typename ASmemBlockWindow, typename BSmemBlockWindow>
CK_TILE_DEVICE auto operator()(const ASmemBlockWindow& a_block_window,
const BSmemBlockWindow& b_block_window)
{
auto c_block_tensor = MakeCBlockTile();
block_gemm_impl_(c_block_tensor, a_block_window, b_block_window);
return c_block_tensor;
}
private:
BlockGemmImpl<Scheduler, Traits> block_gemm_impl_{};
};
} // namespace ck_tile
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include <iostream>
#include <string>
#include "ck_tile/core.hpp"
#include "ck_tile/ops/common.hpp"
namespace ck_tile {
struct BatchedGemmHostArgs
{
const void* a_ptr;
const void* b_ptr;
void* c_ptr;
index_t M;
index_t N;
index_t K;
index_t stride_A;
index_t stride_B;
index_t stride_C;
index_t batch_stride_A;
index_t batch_stride_B;
index_t batch_stride_C;
index_t batch_count;
};
template <typename TilePartitioner_, typename GemmPipeline_, typename EpiloguePipeline_>
struct BatchedGemmKernel
{
using TilePartitioner = remove_cvref_t<TilePartitioner_>;
using GemmPipeline = remove_cvref_t<GemmPipeline_>;
using EpiloguePipeline = remove_cvref_t<EpiloguePipeline_>;
using ALayout = remove_cvref_t<typename GemmPipeline::ALayout>;
using BLayout = remove_cvref_t<typename GemmPipeline::BLayout>;
using CLayout = remove_cvref_t<typename GemmPipeline::CLayout>;
static constexpr index_t KernelBlockSize = GemmPipeline::BlockSize;
using ADataType = remove_cvref_t<typename GemmPipeline::ADataType>;
using BDataType = remove_cvref_t<typename GemmPipeline::BDataType>;
using CDataType = remove_cvref_t<typename EpiloguePipeline::ODataType>;
struct BatchedGemmKargs
{
const void* a_ptr;
const void* b_ptr;
void* c_ptr;
index_t M;
index_t N;
index_t K;
index_t stride_A;
index_t stride_B;
index_t stride_C;
index_t batch_stride_A;
index_t batch_stride_B;
index_t batch_stride_C;
index_t batch_count;
};
using Kargs = BatchedGemmKargs;
using Hargs = BatchedGemmHostArgs;
__host__ static constexpr auto GridSize(const Hargs& h)
{
return TilePartitioner::GridSize(h.M, h.N, h.batch_count);
}
__host__ static constexpr auto BlockSize() { return dim3(KernelBlockSize); }
CK_TILE_HOST static constexpr BatchedGemmKargs MakeKargs(const Hargs& h)
{
Kargs k;
k.a_ptr = h.a_ptr;
k.b_ptr = h.b_ptr;
k.c_ptr = h.c_ptr;
k.M = h.M;
k.N = h.N;
k.K = h.K;
k.stride_A = h.stride_A;
k.stride_B = h.stride_B;
k.stride_C = h.stride_C;
k.batch_stride_A = h.batch_stride_A;
k.batch_stride_B = h.batch_stride_B;
k.batch_stride_C = h.batch_stride_C;
k.batch_count = h.batch_count;
return k;
}
CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
{
return max(GemmPipeline::GetSmemSize(), EpiloguePipeline::GetSmemSize());
}
CK_TILE_DEVICE void operator()(Kargs kargs) const
{
const auto [i_m, i_n] = TilePartitioner{}();
const auto i_batch = __builtin_amdgcn_readfirstlane(blockIdx.z);
// options
const auto batch_stride_A = __builtin_amdgcn_readfirstlane(kargs.batch_stride_A);
const auto batch_offset_A = __builtin_amdgcn_readfirstlane(i_batch * batch_stride_A);
const ADataType* a_start = static_cast<const ADataType*>(kargs.a_ptr);
const auto batch_stride_B = __builtin_amdgcn_readfirstlane(kargs.batch_stride_B);
const auto batch_offset_B = __builtin_amdgcn_readfirstlane(i_batch * batch_stride_B);
const BDataType* b_start = static_cast<const BDataType*>(kargs.b_ptr);
// Convert pointers to tensor views
auto a_tensor_view = [&]() {
if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
{
return make_naive_tensor_view<address_space_enum::global>(
a_start + batch_offset_A,
make_tuple(kargs.M, kargs.K),
make_tuple(kargs.stride_A, 1),
number<GemmPipeline::VectorSizeA>{},
number<1>{});
}
else
{
return make_naive_tensor_view<address_space_enum::global>(
a_start + batch_offset_A,
make_tuple(kargs.M, kargs.K),
make_tuple(1, kargs.stride_A),
number<1>{},
number<1>{});
}
}();
auto b_tensor_view = [&]() {
if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::RowMajor>)
{
return make_naive_tensor_view<address_space_enum::global>(
b_start + batch_offset_B,
make_tuple(kargs.N, kargs.K),
make_tuple(1, kargs.stride_B),
number<1>{},
number<1>{});
}
else
{
return make_naive_tensor_view<address_space_enum::global>(
b_start + batch_offset_B,
make_tuple(kargs.N, kargs.K),
make_tuple(kargs.stride_B, 1),
number<GemmPipeline::VectorSizeB>{},
number<1>{});
}
}();
auto a_pad_view = [&]() {
if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
{
return pad_tensor_view(
a_tensor_view,
make_tuple(number<TilePartitioner::kM>{}, number<TilePartitioner::kK>{}),
sequence<false, GemmPipeline::kPadK>{});
}
else
{
return pad_tensor_view(
a_tensor_view,
make_tuple(number<TilePartitioner::kM>{}, number<TilePartitioner::kK>{}),
sequence<GemmPipeline::kPadM, false>{});
}
}();
// clang-format on
auto a_block_window = make_tile_window(
a_pad_view,
make_tuple(number<TilePartitioner::kM>{}, number<TilePartitioner::kK>{}),
{i_m, 0});
auto b_pad_view = [&]() {
if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::ColumnMajor>)
{
return pad_tensor_view(
b_tensor_view,
make_tuple(number<TilePartitioner::kN>{}, number<TilePartitioner::kK>{}),
sequence<false, GemmPipeline::kPadK>{});
}
else
{
return pad_tensor_view(
b_tensor_view,
make_tuple(number<TilePartitioner::kN>{}, number<TilePartitioner::kK>{}),
sequence<GemmPipeline::kPadN, false>{});
}
}();
// clang-format on
auto b_block_window = make_tile_window(
b_pad_view,
make_tuple(number<TilePartitioner::kN>{}, number<TilePartitioner::kK>{}),
{i_n, 0});
// allocate LDS
__shared__ char smem_ptr[GetSmemSize()];
const index_t num_loop = TilePartitioner::GetLoopNum(kargs.K);
// Run GEMM cooperatively by whole wokrgroup.
auto c_block_tile =
GemmPipeline{}.template operator()(a_block_window, b_block_window, num_loop, smem_ptr);
const auto batch_stride_C = __builtin_amdgcn_readfirstlane(kargs.batch_stride_C);
const auto batch_offset_C = __builtin_amdgcn_readfirstlane(i_batch * batch_stride_C);
CDataType* c_start = static_cast<CDataType*>(kargs.c_ptr);
auto c_tensor_view = [&]() {
if constexpr(std::is_same_v<CLayout, tensor_layout::gemm::RowMajor>)
{
return make_naive_tensor_view<address_space_enum::global>(
c_start + batch_offset_C,
make_tuple(kargs.M, kargs.N),
make_tuple(kargs.stride_C, 1),
number<GemmPipeline::VectorSizeC>{},
number<1>{});
}
else
{
return make_naive_tensor_view<address_space_enum::global>(
c_start + batch_offset_C,
make_tuple(kargs.M, kargs.N),
make_tuple(1, kargs.stride_C),
number<1>{},
number<1>{});
}
}();
auto c_pad_view = [&]() {
if constexpr(std::is_same_v<CLayout, tensor_layout::gemm::RowMajor>)
{
return pad_tensor_view(
c_tensor_view,
make_tuple(number<TilePartitioner::kM>{}, number<TilePartitioner::kN>{}),
sequence<false, GemmPipeline::kPadN>{});
}
else
{
return pad_tensor_view(
c_tensor_view,
make_tuple(number<TilePartitioner::kM>{}, number<TilePartitioner::kN>{}),
sequence<GemmPipeline::kPadM, false>{});
}
}();
auto c_block_window = make_tile_window(
c_pad_view,
make_tuple(number<TilePartitioner::kM>{}, number<TilePartitioner::kN>{}),
{i_m, i_n});
EpiloguePipeline{}(c_block_window, c_block_tile);
}
};
} // namespace ck_tile
......@@ -66,6 +66,79 @@ struct GemmKernel
return max(GemmPipeline::GetSmemSize(), EpiloguePipeline::GetSmemSize());
}
CK_TILE_HOST static bool IsSupportedArgument(const GemmCommonKargs& kargs)
{
if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
{
if(kargs.K % TilePartitioner::kK != 0 && GemmPipeline::kPadK == false)
{
return false;
}
if(kargs.K % GemmPipeline::VectorSizeA != 0)
{
return false;
}
}
else
{
if(kargs.M % TilePartitioner::kM != 0 && GemmPipeline::kPadM == false)
{
return false;
}
if(kargs.M % GemmPipeline::VectorSizeA != 0)
{
return false;
}
}
if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::RowMajor>)
{
if(kargs.N % TilePartitioner::kN != 0 && GemmPipeline::kPadN == false)
{
return false;
}
if(kargs.N % GemmPipeline::VectorSizeB != 0)
{
return false;
}
}
else
{
if(kargs.K % TilePartitioner::kK != 0 && GemmPipeline::kPadK == false)
{
return false;
}
if(kargs.K % GemmPipeline::VectorSizeB != 0)
{
return false;
}
}
if constexpr(std::is_same_v<CLayout, tensor_layout::gemm::RowMajor>)
{
if(kargs.N % TilePartitioner::kN != 0 && GemmPipeline::kPadN == false)
{
return false;
}
if(kargs.N % GemmPipeline::VectorSizeC != 0)
{
return false;
}
}
else
{
if(kargs.M % TilePartitioner::kM != 0 && GemmPipeline::kPadM == false)
{
return false;
}
if(kargs.M % GemmPipeline::VectorSizeC != 0)
{
return false;
}
}
return true;
}
CK_TILE_DEVICE void operator()(GemmCommonKargs kargs) const
{
const auto [i_m, i_n] = TilePartitioner{}();
......
......@@ -35,4 +35,40 @@ struct GemmTilePartitioner
return make_tuple(iM, iN);
}
};
template <typename BlockGemmShape_>
struct GemmTile1DPartitioner
{
using BlockGemmShape = remove_cvref_t<BlockGemmShape_>;
static constexpr index_t MPerBlock = BlockGemmShape::kM;
static constexpr index_t NPerBlock = BlockGemmShape::kN;
static constexpr index_t KPerBlock = BlockGemmShape::kK;
CK_TILE_HOST static constexpr auto GridSize(index_t M, index_t N)
{
index_t GridDimX = (M + MPerBlock - 1) / MPerBlock;
index_t GridDimY = (N + NPerBlock - 1) / NPerBlock;
return dim3(GridDimX * GridDimY, 1, 1);
}
CK_TILE_HOST_DEVICE static constexpr auto GetNBlock(index_t N)
{
return integer_divide_ceil(N, NPerBlock);
}
CK_TILE_HOST_DEVICE static constexpr auto GetLoopNum(index_t K)
{
return integer_divide_ceil(K, KPerBlock);
}
CK_TILE_DEVICE auto operator()(index_t blockOffset, index_t NBlockSize)
{
index_t iM = __builtin_amdgcn_readfirstlane((blockIdx.x - blockOffset) /
GetNBlock(NBlockSize) * MPerBlock);
index_t iN = __builtin_amdgcn_readfirstlane((blockIdx.x - blockOffset) %
GetNBlock(NBlockSize) * NPerBlock);
return make_tuple(iM, iN);
}
};
} // namespace ck_tile
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include <iostream>
#include <string>
#include "ck_tile/core/numeric/math.hpp"
#include "ck_tile/core/utility/literals.hpp"
#include "ck_tile/core/utility/amd_address_space.hpp"
#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_ag_bg_cr_scheduler.hpp"
#include "ck_tile/core.hpp"
#include "ck_tile/ops/common.hpp"
#include "ck_tile/host.hpp"
namespace ck_tile {
struct GroupedGemmHostArgs
{
const void* a_ptr;
const void* b_ptr;
void* c_ptr;
index_t M;
index_t N;
index_t K;
index_t stride_A;
index_t stride_B;
index_t stride_C;
};
template <typename TilePartitioner_, typename GemmPipeline_, typename EpiloguePipeline_>
struct GroupedGemmKernel
{
using TilePartitioner = remove_cvref_t<TilePartitioner_>;
using GemmPipeline = remove_cvref_t<GemmPipeline_>;
using EpiloguePipeline = remove_cvref_t<EpiloguePipeline_>;
using ALayout = remove_cvref_t<typename GemmPipeline::ALayout>;
using BLayout = remove_cvref_t<typename GemmPipeline::BLayout>;
using CLayout = remove_cvref_t<typename GemmPipeline::CLayout>;
static constexpr index_t KernelBlockSize = GemmPipeline::BlockSize;
using ADataType = remove_cvref_t<typename GemmPipeline::ADataType>;
using BDataType = remove_cvref_t<typename GemmPipeline::BDataType>;
using CDataType = remove_cvref_t<typename EpiloguePipeline::ODataType>;
struct GemmTransKernelArg
{
GroupedGemmHostArgs group_karg;
ck_tile::index_t block_start;
ck_tile::index_t block_end;
GemmTransKernelArg() = default;
GemmTransKernelArg(GroupedGemmHostArgs&& karg, index_t bl_start, index_t bl_end)
: group_karg{karg}, block_start{bl_start}, block_end{bl_end}
{
}
};
__host__ static size_t GetWorkSpaceSize(const std::vector<GroupedGemmHostArgs>& gemm_descs)
{
return gemm_descs.size() * sizeof(GemmTransKernelArg);
}
__host__ static constexpr auto BlockSize() { return dim3(KernelBlockSize); }
using Hargs = GroupedGemmHostArgs;
__host__ static constexpr auto GridSize(const std::vector<Hargs>& gemm_descs)
{
index_t grid_size = 0;
for(const auto& it_desc : gemm_descs)
{
const auto dim3 = TilePartitioner::GridSize(it_desc.M, it_desc.N);
grid_size += dim3.x * dim3.y * 1;
}
return dim3(grid_size, 1, 1);
}
CK_TILE_HOST static auto MakeKargs(const std::vector<Hargs>& gemm_descs)
{
std::vector<GemmTransKernelArg> gemm_kernel_args_;
index_t group_count = ck_tile::type_convert<ck_tile::index_t>(gemm_descs.size());
index_t grid_size = 0;
gemm_kernel_args_.reserve(group_count);
for(std::size_t i = 0; i < gemm_descs.size(); ++i)
{
const index_t M = gemm_descs[i].M;
const index_t N = gemm_descs[i].N;
const index_t K = gemm_descs[i].K;
if(M == 0 || N == 0 || K == 0)
{
continue;
}
const index_t stride_a = gemm_descs[i].stride_A;
const index_t stride_b = gemm_descs[i].stride_B;
const index_t stride_c = gemm_descs[i].stride_C;
const auto dim3 = TilePartitioner::GridSize(M, N);
const index_t grid_size_grp = dim3.x * 1 * 1;
const index_t block_start = grid_size;
const index_t block_end = grid_size + grid_size_grp;
grid_size += grid_size_grp;
auto karg = GroupedGemmHostArgs{type_convert<const ADataType*>(gemm_descs[i].a_ptr),
type_convert<const BDataType*>(gemm_descs[i].b_ptr),
type_convert<CDataType*>(gemm_descs[i].c_ptr),
M,
N,
K,
stride_a,
stride_b,
stride_c};
gemm_kernel_args_.emplace_back(std::move(karg), block_start, block_end);
}
return gemm_kernel_args_;
}
CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
{
return max(GemmPipeline::GetSmemSize(), EpiloguePipeline::GetSmemSize());
}
CK_TILE_DEVICE void Run(const Hargs& kargs, const index_t block_start) const
{
const auto [i_m, i_n] = TilePartitioner{}(block_start, kargs.N);
// options
const ADataType* a_start = static_cast<const ADataType*>(kargs.a_ptr);
const BDataType* b_start = static_cast<const BDataType*>(kargs.b_ptr);
// Convert pointers to tensor views
auto a_tensor_view = [&]() {
if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
{
return make_naive_tensor_view<address_space_enum::global>(
a_start,
make_tuple(kargs.M, kargs.K),
make_tuple(kargs.stride_A, 1),
number<GemmPipeline::VectorSizeA>{},
number<1>{});
}
else
{
return make_naive_tensor_view<address_space_enum::global>(
a_start,
make_tuple(kargs.M, kargs.K),
make_tuple(1, kargs.stride_A),
number<1>{},
number<1>{});
}
}();
auto b_tensor_view = [&]() {
if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::RowMajor>)
{
return make_naive_tensor_view<address_space_enum::global>(
b_start,
make_tuple(kargs.N, kargs.K),
make_tuple(1, kargs.stride_B),
number<1>{},
number<1>{});
}
else
{
return make_naive_tensor_view<address_space_enum::global>(
b_start,
make_tuple(kargs.N, kargs.K),
make_tuple(kargs.stride_B, 1),
number<GemmPipeline::VectorSizeB>{},
number<1>{});
}
}();
auto a_pad_view = [&]() {
if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
{
return pad_tensor_view(a_tensor_view,
make_tuple(number<TilePartitioner::MPerBlock>{},
number<TilePartitioner::KPerBlock>{}),
sequence<false, GemmPipeline::kPadK>{});
}
else
{
return pad_tensor_view(a_tensor_view,
make_tuple(number<TilePartitioner::MPerBlock>{},
number<TilePartitioner::KPerBlock>{}),
sequence<GemmPipeline::kPadM, false>{});
}
}();
// clang-format on
auto a_block_window = make_tile_window(
a_pad_view,
make_tuple(number<TilePartitioner::MPerBlock>{}, number<TilePartitioner::KPerBlock>{}),
{i_m, 0});
auto b_pad_view = [&]() {
if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::ColumnMajor>)
{
return pad_tensor_view(b_tensor_view,
make_tuple(number<TilePartitioner::NPerBlock>{},
number<TilePartitioner::KPerBlock>{}),
sequence<false, GemmPipeline::kPadK>{});
}
else
{
return pad_tensor_view(b_tensor_view,
make_tuple(number<TilePartitioner::NPerBlock>{},
number<TilePartitioner::KPerBlock>{}),
sequence<GemmPipeline::kPadN, false>{});
}
}();
auto b_block_window = make_tile_window(
b_pad_view,
make_tuple(number<TilePartitioner::NPerBlock>{}, number<TilePartitioner::KPerBlock>{}),
{i_n, 0});
// allocate LDS
__shared__ char smem_ptr[GetSmemSize()];
const index_t num_loop = TilePartitioner::GetLoopNum(kargs.K);
// Run GEMM cooperatively by whole wokrgroup.
auto c_block_tile =
GemmPipeline{}.template operator()(a_block_window, b_block_window, num_loop, smem_ptr);
CDataType* c_start = static_cast<CDataType*>(kargs.c_ptr);
auto c_tensor_view = [&]() {
if constexpr(std::is_same_v<CLayout, tensor_layout::gemm::RowMajor>)
{
return make_naive_tensor_view<address_space_enum::global>(
c_start,
make_tuple(kargs.M, kargs.N),
make_tuple(kargs.stride_C, 1),
number<GemmPipeline::VectorSizeC>{},
number<1>{});
}
else
{
return make_naive_tensor_view<address_space_enum::global>(
c_start,
make_tuple(kargs.M, kargs.N),
make_tuple(1, kargs.stride_C),
number<1>{},
number<1>{});
}
}();
auto c_pad_view = [&]() {
if constexpr(std::is_same_v<CLayout, tensor_layout::gemm::RowMajor>)
{
return pad_tensor_view(c_tensor_view,
make_tuple(number<TilePartitioner::MPerBlock>{},
number<TilePartitioner::NPerBlock>{}),
sequence<false, GemmPipeline::kPadN>{});
}
else
{
return pad_tensor_view(c_tensor_view,
make_tuple(number<TilePartitioner::MPerBlock>{},
number<TilePartitioner::NPerBlock>{}),
sequence<GemmPipeline::kPadM, false>{});
}
}();
auto CBlockWindow_pad = make_tile_window(
c_pad_view,
make_tuple(number<TilePartitioner::MPerBlock>{}, number<TilePartitioner::NPerBlock>{}),
{i_m, i_n});
EpiloguePipeline{}(CBlockWindow_pad, c_block_tile);
}
CK_TILE_DEVICE void operator()(const void CK_CONSTANT_ADDRESS_SPACE* gemm_descs_const,
int group_count) const
{
const index_t block_id = ck_tile::get_block_1d_id();
const auto gemm_desc_ptr = reinterpret_cast<const GemmTransKernelArg*>(
cast_pointer_to_generic_address_space(gemm_descs_const));
index_t left = 0;
index_t right = group_count;
index_t group_id = index_t((left + right) / 2);
while((!(block_id >= gemm_desc_ptr[group_id].block_start &&
block_id < gemm_desc_ptr[group_id].block_end)) &&
left <= right)
{
if(block_id < gemm_desc_ptr[group_id].block_start)
{
right = group_id;
}
else
{
left = group_id;
}
group_id = index_t((left + right) / 2);
}
Run(gemm_desc_ptr[group_id].group_karg, gemm_desc_ptr[group_id].block_start);
}
};
} // namespace ck_tile
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
namespace ck_tile {
template <typename Problem, typename Policy>
struct GemmPipelineAgBgCrImplBase
{
using ADataType = remove_cvref_t<typename Problem::ADataType>;
using BDataType = remove_cvref_t<typename Problem::BDataType>;
using BlockGemmShape = remove_cvref_t<typename Problem::BlockGemmShape>;
static constexpr index_t MPerBlock = BlockGemmShape::kM;
static constexpr index_t NPerBlock = BlockGemmShape::kN;
static constexpr index_t KPerBlock = BlockGemmShape::kK;
template <typename DstBlockTile, typename SrcTileWindow>
CK_TILE_DEVICE void GlobalPrefetch(DstBlockTile& dst_block_tile,
SrcTileWindow& dram_tile_window) const
{
load_tile(dst_block_tile, dram_tile_window);
move_tile_window(dram_tile_window, {0, KPerBlock});
}
template <typename DstTileWindow, typename SrcBlockTile, typename ElementFunction>
CK_TILE_DEVICE void LocalPrefill(DstTileWindow& lds_tile_window,
const SrcBlockTile& src_block_tile,
const ElementFunction& element_func) const
{
const auto block_tile_tmp = tile_elementwise_in(element_func, src_block_tile);
store_tile(lds_tile_window, block_tile_tmp);
}
CK_TILE_DEVICE auto GetABLdsTensorViews(void* p_smem) const
{
// A tile in LDS
ADataType* p_a_lds = static_cast<ADataType*>(p_smem);
constexpr auto a_lds_block_desc = Policy::template MakeALdsBlockDescriptor<Problem>();
auto a_lds_block = make_tensor_view<address_space_enum::lds>(p_a_lds, a_lds_block_desc);
// TODO: LDS alignment should come from Policy!
constexpr index_t a_lds_block_space_size_aligned =
integer_divide_ceil(sizeof(ADataType) * a_lds_block_desc.get_element_space_size(), 16) *
16;
// B tile in LDS
BDataType* p_b_lds = static_cast<BDataType*>(
static_cast<void*>(static_cast<char*>(p_smem) + a_lds_block_space_size_aligned));
constexpr auto b_lds_block_desc = Policy::template MakeBLdsBlockDescriptor<Problem>();
auto b_lds_block = make_tensor_view<address_space_enum::lds>(p_b_lds, b_lds_block_desc);
return make_tuple(std::move(a_lds_block), std::move(b_lds_block));
}
template <typename ADramBlockWindowTmp, typename ALdsTensorView>
CK_TILE_DEVICE auto GetAWindows(const ADramBlockWindowTmp& a_dram_block_window_tmp,
const ALdsTensorView& a_lds_block_view) const
{
// A DRAM tile window for load
auto a_copy_dram_window =
make_tile_window(a_dram_block_window_tmp.get_bottom_tensor_view(),
make_tuple(number<MPerBlock>{}, number<KPerBlock>{}),
a_dram_block_window_tmp.get_window_origin(),
Policy::template MakeADramTileDistribution<Problem>());
// A LDS tile window for store
auto a_copy_lds_window =
make_tile_window(a_lds_block_view,
make_tuple(number<MPerBlock>{}, number<KPerBlock>{}),
{0, 0},
a_copy_dram_window.get_tile_distribution());
auto a_lds_gemm_window = make_tile_window(
a_lds_block_view, make_tuple(number<MPerBlock>{}, number<KPerBlock>{}), {0, 0});
return make_tuple(std::move(a_copy_dram_window),
std::move(a_copy_lds_window),
std::move(a_lds_gemm_window));
}
template <typename BDramBlockWindowTmp, typename BLdsTensorView>
CK_TILE_DEVICE auto GetBWindows(const BDramBlockWindowTmp& b_dram_block_window_tmp,
const BLdsTensorView& b_lds_block_view) const
{
auto b_copy_dram_window =
make_tile_window(b_dram_block_window_tmp.get_bottom_tensor_view(),
make_tuple(number<NPerBlock>{}, number<KPerBlock>{}),
b_dram_block_window_tmp.get_window_origin(),
Policy::template MakeBDramTileDistribution<Problem>());
// B LDS tile window for store
auto b_copy_lds_window =
make_tile_window(b_lds_block_view,
make_tuple(number<NPerBlock>{}, number<KPerBlock>{}),
{0, 0},
b_copy_dram_window.get_tile_distribution());
auto b_lds_gemm_window = make_tile_window(
b_lds_block_view, make_tuple(number<NPerBlock>{}, number<KPerBlock>{}), {0, 0});
return make_tuple(std::move(b_copy_dram_window),
std::move(b_copy_lds_window),
std::move(b_lds_gemm_window));
}
};
} // namespace ck_tile
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_agmem_bgmem_creg_v1_default_policy.hpp"
#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_ag_bg_cr_scheduler.hpp"
#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_ag_bg_cr_base.hpp"
namespace ck_tile {
// A Tile Window: global memory
// B Tile Window: global memory
// C Distributed tensor: register
template <typename Problem>
struct BaseGemmPipelineAgBgCrCompV3
{
static constexpr index_t PrefetchStages = 2;
static constexpr index_t PrefillStages = 1;
static constexpr index_t GlobalBufferNum = 1;
CK_TILE_HOST static constexpr bool BlockHasHotloop(index_t num_loop)
{
return num_loop > PrefetchStages;
}
CK_TILE_HOST static constexpr TailNumber GetBlockLoopTailNum(index_t num_loop)
{
ignore = num_loop;
return TailNumber::Full;
}
};
// Compute optimized pipeline
// GlobalPrefetchStages: 2
// LocalPreFillStages: 1
// LocalPreFetchStages: 1
// LocalSharedMemoryBuffer: 1
template <typename Problem, typename Policy = GemmPipelineAGmemBGmemCRegV1DefaultPolicy>
struct GemmPipelineAgBgCrCompV3 : public BaseGemmPipelineAgBgCrCompV3<Problem>
{
using Base = BaseGemmPipelineAgBgCrCompV3<Problem>;
using PipelineImplBase = GemmPipelineAgBgCrImplBase<Problem, Policy>;
using ADataType = remove_cvref_t<typename Problem::ADataType>;
using BDataType = remove_cvref_t<typename Problem::BDataType>;
using CDataType = remove_cvref_t<typename Problem::CDataType>;
using BlockGemmShape = remove_cvref_t<typename Problem::BlockGemmShape>;
using ALayout = remove_cvref_t<typename Problem::ALayout>;
using BLayout = remove_cvref_t<typename Problem::BLayout>;
using CLayout = remove_cvref_t<typename Problem::CLayout>;
using BlockGemm = remove_cvref_t<decltype(Policy::template GetBlockGemm<Problem>())>;
using I0 = number<0>;
using I1 = number<1>;
using I2 = number<2>;
static constexpr index_t BlockSize = Problem::kBlockSize;
static constexpr index_t MPerBlock = BlockGemmShape::kM;
static constexpr index_t NPerBlock = BlockGemmShape::kN;
static constexpr index_t KPerBlock = BlockGemmShape::kK;
static constexpr index_t VectorSizeA = Problem::VectorSizeA;
static constexpr index_t VectorSizeB = Problem::VectorSizeB;
static constexpr index_t VectorSizeC = Problem::VectorSizeC;
static constexpr bool kPadM = Problem::kPadM;
static constexpr bool kPadN = Problem::kPadN;
static constexpr bool kPadK = Problem::kPadK;
// Where is the right place for HasHotLoop and TailNum ???
static constexpr bool HasHotLoop = Problem::HasHotLoop;
static constexpr auto TailNum = Problem::TailNum;
static constexpr auto Scheduler = Problem::Scheduler;
using Base::PrefetchStages;
CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
{
return Policy::template GetSmemSize<Problem>();
}
template <GemmPipelineScheduler Scheduler>
struct PipelineImpl : public PipelineImplBase
{
};
template <>
struct PipelineImpl<GemmPipelineScheduler::Intrawave> : public PipelineImplBase
{
using Base = PipelineImplBase;
CK_TILE_DEVICE static constexpr auto HotLoopScheduler()
{
constexpr index_t MPerXDL = BlockGemmShape::WarpTile::at(I0{});
constexpr index_t NPerXDL = BlockGemmShape::WarpTile::at(I1{});
constexpr index_t KPerXDL = BlockGemmShape::WarpTile::at(I2{});
constexpr index_t WaveSize = 64;
constexpr index_t WaveNumM = BlockGemmShape::BlockWarps::at(I0{});
constexpr index_t WaveNumN = BlockGemmShape::BlockWarps::at(I1{});
constexpr index_t A_LDS_Read_Width = KPerXDL;
constexpr index_t B_LDS_Read_Width = KPerXDL;
constexpr index_t A_Buffer_Load_Inst_Num =
MPerBlock * KPerBlock / (BlockSize * VectorSizeA);
constexpr index_t B_Buffer_Load_Inst_Num =
NPerBlock * KPerBlock / (BlockSize * VectorSizeB);
constexpr index_t A_LDS_Write_Inst_Num = MPerBlock * KPerBlock / (BlockSize * KPerXDL);
constexpr index_t B_LDS_Write_Inst_Num = NPerBlock * KPerBlock / (BlockSize * KPerXDL);
constexpr index_t A_LDS_Read_Inst_Num =
WaveNumN * MPerBlock * KPerBlock / (BlockSize * KPerXDL);
constexpr index_t B_LDS_Read_Inst_Num =
WaveNumM * MPerBlock * KPerBlock / (BlockSize * KPerXDL);
constexpr index_t C_MFMA_Inst_Num = MPerBlock * NPerBlock * KPerBlock /
(BlockSize / WaveSize) /
(MPerXDL * NPerXDL * KPerXDL);
// A/B split schedule
// compiler is likely to use ds_read2 when instruction width smaller than 16bytes
constexpr auto num_ds_read_inst_a = A_LDS_Read_Width * sizeof(ADataType) == 16
? A_LDS_Read_Inst_Num
: A_LDS_Read_Inst_Num / 2;
constexpr auto num_ds_read_inst_b = B_LDS_Read_Width * sizeof(BDataType) == 16
? B_LDS_Read_Inst_Num
: B_LDS_Read_Inst_Num / 2;
constexpr auto num_ds_write_inst_a = A_LDS_Write_Inst_Num;
constexpr auto num_ds_write_inst_b = B_LDS_Write_Inst_Num;
constexpr auto num_buffer_load_inst_a = A_Buffer_Load_Inst_Num;
constexpr auto num_buffer_load_inst_b = B_Buffer_Load_Inst_Num;
constexpr auto num_mfma_inst = C_MFMA_Inst_Num;
constexpr auto mfma_cycle = NPerXDL == 16 ? 16 : 32;
constexpr auto ds_read_a_issue_cycle =
A_LDS_Read_Width * sizeof(ADataType) == 16 ? 8 : 4;
constexpr auto ds_read_b_issue_cycle =
B_LDS_Read_Width * sizeof(BDataType) == 16 ? 8 : 4;
constexpr auto ds_read_a_mfma_rate =
(mfma_cycle - 4 + 2 * ds_read_a_issue_cycle - 1) / (2 * ds_read_a_issue_cycle);
constexpr auto ds_read_b_mfma_rate =
(mfma_cycle - 4 + 2 * ds_read_b_issue_cycle - 1) / (2 * ds_read_b_issue_cycle);
constexpr auto num_dsread_a_mfma =
(num_ds_read_inst_a + ds_read_a_mfma_rate - 1) / ds_read_a_mfma_rate;
constexpr auto num_dsread_b_mfma =
(num_ds_read_inst_b + ds_read_b_mfma_rate - 1) / ds_read_b_mfma_rate;
// stage 1
// Separate this part?
// constexpr auto num_mfma_per_ds_read = sizeof(ComputeDataType) / sizeof(ADataType) >
// sizeof(ComputeDataType) /
// sizeof(BDataType)
// ? sizeof(ComputeDataType) /
// sizeof(ADataType) : sizeof(ComputeDataType)
// / sizeof(BDataType);
constexpr auto num_mfma_stage1 =
num_mfma_inst - (num_dsread_a_mfma + num_dsread_b_mfma);
constexpr auto num_mfma_per_issue =
num_mfma_stage1 / (num_buffer_load_inst_a + num_buffer_load_inst_b);
constexpr auto num_dswrite_per_issue_a = num_ds_write_inst_a / num_buffer_load_inst_a;
constexpr auto num_dswrite_per_issue_b = num_ds_write_inst_b / num_buffer_load_inst_b;
static_for<0, num_buffer_load_inst_a, 1>{}([&](auto i) {
ignore = i;
static_for<0, num_dswrite_per_issue_a, 1>{}([&](auto idswrite) {
ignore = idswrite;
__builtin_amdgcn_sched_group_barrier(0x200, 1, 0); // DS write
__builtin_amdgcn_sched_group_barrier(0x008, 1, 0); // MFMA
});
__builtin_amdgcn_sched_group_barrier(0x020, 1, 0); // VMEM read
__builtin_amdgcn_sched_group_barrier(
0x008, num_mfma_per_issue - num_dswrite_per_issue_a, 0); // MFMA
});
static_for<0, num_buffer_load_inst_b, 1>{}([&](auto i) {
ignore = i;
static_for<0, num_dswrite_per_issue_b, 1>{}([&](auto idswrite) {
ignore = idswrite;
__builtin_amdgcn_sched_group_barrier(0x200, 1, 0); // DS write
__builtin_amdgcn_sched_group_barrier(0x008, 1, 0); // MFMA
});
__builtin_amdgcn_sched_group_barrier(0x020, 1, 0); // VMEM read
__builtin_amdgcn_sched_group_barrier(
0x008, num_mfma_per_issue - num_dswrite_per_issue_b, 0); // MFMA
});
// stage 2
static_for<0, num_dsread_a_mfma, 1>{}([&](auto i) {
if constexpr((num_ds_read_inst_a - (i + 1) * ds_read_a_mfma_rate) >=
ds_read_a_mfma_rate)
{
__builtin_amdgcn_sched_group_barrier(0x100, ds_read_a_mfma_rate, 0); // DS read
}
else
{
__builtin_amdgcn_sched_group_barrier(
0x100,
num_ds_read_inst_a - (num_dsread_a_mfma - 1) * ds_read_a_mfma_rate,
0); // DS read
}
__builtin_amdgcn_sched_group_barrier(0x008, 1, 0); // MFMA
});
static_for<0, num_dsread_b_mfma, 1>{}([&](auto i) {
if constexpr((num_ds_read_inst_b - (i + 1) * ds_read_b_mfma_rate) >=
ds_read_b_mfma_rate)
{
__builtin_amdgcn_sched_group_barrier(0x100, ds_read_b_mfma_rate, 0); // DS read
}
else
{
__builtin_amdgcn_sched_group_barrier(
0x100,
num_ds_read_inst_b - (num_dsread_b_mfma - 1) * ds_read_b_mfma_rate,
0); // DS read
}
__builtin_amdgcn_sched_group_barrier(0x008, 1, 0); // MFMA
});
}
template <bool HasHotLoop,
TailNumber TailNum,
typename ADramBlockWindowTmp,
typename BDramBlockWindowTmp,
typename AElementFunction,
typename BElementFunction>
CK_TILE_DEVICE auto operator()(const ADramBlockWindowTmp& a_dram_block_window_tmp,
const AElementFunction& a_element_func,
const BDramBlockWindowTmp& b_dram_block_window_tmp,
const BElementFunction& b_element_func,
index_t num_loop,
void* p_smem) const
{
static_assert(
std::is_same_v<ADataType, remove_cvref_t<typename ADramBlockWindowTmp::DataType>> &&
std::is_same_v<BDataType,
remove_cvref_t<typename BDramBlockWindowTmp::DataType>>,
"A/B Dram block window should have the same data type as appropriate "
"([A|B]DataType) defined in Problem definition!");
static_assert(MPerBlock == ADramBlockWindowTmp{}.get_window_lengths()[I0{}] &&
NPerBlock == BDramBlockWindowTmp{}.get_window_lengths()[I0{}] &&
KPerBlock == ADramBlockWindowTmp{}.get_window_lengths()[I1{}],
"A/B block window appropriate sizes must be equal to MPerBlock/NPerblock"
" or KPerBlock!");
// ------------------------------------------------------------------------------------
// Definitions of all needed tiles
// A/B tiles in LDS
auto&& [a_lds_block, b_lds_block] = Base::GetABLdsTensorViews(p_smem);
// A DRAM tile window for load
// A LDS tile window for store
// A LDS tile for block GEMM
auto&& [a_copy_dram_window, a_copy_lds_window, a_lds_gemm_window] =
Base::GetAWindows(a_dram_block_window_tmp, a_lds_block);
// B DRAM tile window for load
// B LDS tile window for store
// B LDS tile for block GEMM
auto&& [b_copy_dram_window, b_copy_lds_window, b_lds_gemm_window] =
Base::GetBWindows(b_dram_block_window_tmp, b_lds_block);
// Block GEMM
auto block_gemm = BlockGemm();
auto c_block_tile = block_gemm.MakeCBlockTile();
using ABlockTileDistr = decltype(a_copy_dram_window.get_tile_distribution());
using BBlockTileDistr = decltype(b_copy_dram_window.get_tile_distribution());
using ABlockTile =
decltype(make_static_distributed_tensor<ADataType>(ABlockTileDistr{}));
using BBlockTile =
decltype(make_static_distributed_tensor<BDataType>(BBlockTileDistr{}));
ABlockTile a_block_tile;
BBlockTile b_block_tile;
// -----------------------------------------------------------------------------------------
// Gemm pipeline start
// prefetch
// global read 0
Base::GlobalPrefetch(a_block_tile, a_copy_dram_window);
Base::GlobalPrefetch(b_block_tile, b_copy_dram_window);
// initialize C
tile_elementwise_inout([](auto& c) { c = 0; }, c_block_tile);
// LDS write 0
Base::LocalPrefill(a_copy_lds_window, a_block_tile, a_element_func);
Base::LocalPrefill(b_copy_lds_window, b_block_tile, b_element_func);
Base::GlobalPrefetch(a_block_tile, a_copy_dram_window);
Base::GlobalPrefetch(b_block_tile, b_copy_dram_window);
block_sync_lds();
block_gemm.LocalPrefetch(a_lds_gemm_window, b_lds_gemm_window);
__builtin_amdgcn_sched_barrier(0);
// main body
if constexpr(HasHotLoop)
{
index_t i = 0;
do
{
block_sync_lds();
Base::LocalPrefill(a_copy_lds_window, a_block_tile, a_element_func);
Base::LocalPrefill(b_copy_lds_window, b_block_tile, b_element_func);
Base::GlobalPrefetch(a_block_tile, a_copy_dram_window);
Base::GlobalPrefetch(b_block_tile, b_copy_dram_window);
block_gemm(c_block_tile, a_lds_gemm_window, b_lds_gemm_window);
block_sync_lds();
block_gemm.LocalPrefetch(a_lds_gemm_window, b_lds_gemm_window);
HotLoopScheduler();
__builtin_amdgcn_sched_barrier(0);
i += 1;
} while(i < (num_loop - 1));
}
// tail
if constexpr(TailNum == TailNumber::Full)
{
block_gemm(c_block_tile, a_lds_gemm_window, b_lds_gemm_window);
}
// Let's leak last MFMA block to epilogue region, cover the potential lds-shuffle
// latency
// __builtin_amdgcn_sched_barrier(0);
return c_block_tile;
}
};
template <typename ADramBlockWindowTmp,
typename BDramBlockWindowTmp,
typename AElementFunction,
typename BElementFunction>
CK_TILE_DEVICE auto operator()(const ADramBlockWindowTmp& a_dram_block_window_tmp,
const AElementFunction& a_element_func,
const BDramBlockWindowTmp& b_dram_block_window_tmp,
const BElementFunction& b_element_func,
index_t num_loop,
void* p_smem) const
{
return PipelineImpl<Scheduler>{}.template operator()<HasHotLoop, TailNum>(
a_dram_block_window_tmp,
a_element_func,
b_dram_block_window_tmp,
b_element_func,
num_loop,
p_smem);
}
template <typename ADramBlockWindowTmp, typename BDramBlockWindowTmp>
CK_TILE_DEVICE auto operator()(const ADramBlockWindowTmp& a_dram_block_window_tmp,
const BDramBlockWindowTmp& b_dram_block_window_tmp,
index_t num_loop,
void* p_smem) const
{
return PipelineImpl<Scheduler>{}.template operator()<HasHotLoop, TailNum>(
a_dram_block_window_tmp,
[](const ADataType& a) { return a; },
b_dram_block_window_tmp,
[](const BDataType& b) { return b; },
num_loop,
p_smem);
}
};
} // namespace ck_tile
......@@ -6,6 +6,7 @@
#include "ck_tile/core.hpp"
#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_agmem_bgmem_creg_v1_default_policy.hpp"
#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_ag_bg_cr_scheduler.hpp"
#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_ag_bg_cr_base.hpp"
namespace ck_tile {
......@@ -91,6 +92,7 @@ template <typename Problem, typename Policy = GemmPipelineAGmemBGmemCRegV1Defaul
struct GemmPipelineAgBgCrMem : public BaseGemmPipelineAgBgCrMem<Problem>
{
using Base = BaseGemmPipelineAgBgCrMem<Problem>;
using PipelineImplBase = GemmPipelineAgBgCrImplBase<Problem, Policy>;
using ADataType = remove_cvref_t<typename Problem::ADataType>;
using BDataType = remove_cvref_t<typename Problem::BDataType>;
......@@ -103,8 +105,9 @@ struct GemmPipelineAgBgCrMem : public BaseGemmPipelineAgBgCrMem<Problem>
using BlockGemm = remove_cvref_t<decltype(Policy::template GetBlockGemm<Problem>())>;
using I0 = number<0>;
using I1 = number<1>;
using I2 = number<2>;
static constexpr index_t BlockSize = Problem::kBlockSize;
static constexpr index_t MPerBlock = BlockGemmShape::kM;
static constexpr index_t NPerBlock = BlockGemmShape::kN;
static constexpr index_t KPerBlock = BlockGemmShape::kK;
......@@ -124,47 +127,208 @@ struct GemmPipelineAgBgCrMem : public BaseGemmPipelineAgBgCrMem<Problem>
using Base::PrefetchStages;
CK_TILE_HOST_DEVICE constexpr index_t GetStaticLdsSize()
{
return integer_divide_ceil(
sizeof(ADataType) *
Policy::template MakeALdsBlockDescriptor<Problem>().get_element_space_size(),
16) *
16 +
sizeof(BDataType) *
Policy::template MakeBLdsBlockDescriptor<Problem>().get_element_space_size();
}
CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
{
return Policy::template GetSmemSize<Problem>();
}
template <GemmPipelineScheduler Scheduler>
struct PipelineImpl
struct PipelineImpl : public PipelineImplBase
{
};
template <>
struct PipelineImpl<GemmPipelineScheduler::Intrawave>
struct PipelineImpl<GemmPipelineScheduler::Intrawave> : public PipelineImplBase
{
template <typename DstBlockTile, typename SrcTileWindow>
CK_TILE_DEVICE void GlobalPrefetch(DstBlockTile& dst_block_tile,
SrcTileWindow& dram_tile_window) const
using Base = PipelineImplBase;
template <bool HasHotLoop,
TailNumber TailNum,
typename ADramBlockWindowTmp,
typename BDramBlockWindowTmp,
typename AElementFunction,
typename BElementFunction>
CK_TILE_DEVICE auto operator()(const ADramBlockWindowTmp& a_dram_block_window_tmp,
const AElementFunction& a_element_func,
const BDramBlockWindowTmp& b_dram_block_window_tmp,
const BElementFunction& b_element_func,
index_t num_loop,
void* p_smem) const
{
load_tile(dst_block_tile, dram_tile_window);
move_tile_window(dram_tile_window, {0, KPerBlock});
static_assert(
std::is_same_v<ADataType, remove_cvref_t<typename ADramBlockWindowTmp::DataType>> &&
std::is_same_v<BDataType,
remove_cvref_t<typename BDramBlockWindowTmp::DataType>>,
"A/B Dram block window should have the same data type as appropriate "
"([A|B]DataType) defined in Problem definition!");
static_assert(MPerBlock == ADramBlockWindowTmp{}.get_window_lengths()[I0{}] &&
NPerBlock == BDramBlockWindowTmp{}.get_window_lengths()[I0{}] &&
KPerBlock == ADramBlockWindowTmp{}.get_window_lengths()[I1{}],
"A/B block window appropriate sizes must be equal to MPerBlock/NPerblock"
" or KPerBlock!");
// ------------------------------------------------------------------------------------
// Definitions of all needed tiles
// A/B tiles in LDS
// With c++20 could simplify to below line.
// Currently get error: captured structured bindings are a C++20 extension
// auto&& [a_lds_block, b_lds_block] = Base::GetABLdsTensorViews(p_smem);
auto ab_lds_blocks = Base::GetABLdsTensorViews(p_smem);
auto& a_lds_block = ab_lds_blocks.at(I0{});
auto& b_lds_block = ab_lds_blocks.at(I1{});
// A DRAM tile window for load
// A LDS tile window for store
// A LDS tile for block GEMM
auto a_windows = Base::GetAWindows(a_dram_block_window_tmp, a_lds_block);
auto& a_copy_dram_window = a_windows.at(I0{});
auto& a_copy_lds_window = a_windows.at(I1{});
auto& a_lds_gemm_window = a_windows.at(I2{});
// B DRAM tile window for load
// B LDS tile window for store
// B LDS tile for block GEMM
auto b_windows = Base::GetBWindows(b_dram_block_window_tmp, b_lds_block);
auto& b_copy_dram_window = b_windows.at(I0{});
auto& b_copy_lds_window = b_windows.at(I1{});
auto& b_lds_gemm_window = b_windows.at(I2{});
// Block GEMM
auto block_gemm = BlockGemm();
auto c_block_tile = block_gemm.MakeCBlockTile();
using ABlockTileDistr = decltype(a_copy_dram_window.get_tile_distribution());
using BBlockTileDistr = decltype(b_copy_dram_window.get_tile_distribution());
using ABlockTile =
decltype(make_static_distributed_tensor<ADataType>(ABlockTileDistr{}));
using BBlockTile =
decltype(make_static_distributed_tensor<BDataType>(BBlockTileDistr{}));
tuple_array<ABlockTile, PrefetchStages> a_block_tiles;
tuple_array<BBlockTile, PrefetchStages> b_block_tiles;
// -----------------------------------------------------------------------------------------
// Gemm pipeline start
// prefetch
// global read 0
Base::GlobalPrefetch(a_block_tiles.get(I0{}), a_copy_dram_window);
Base::GlobalPrefetch(b_block_tiles.get(I0{}), b_copy_dram_window);
// initialize C
tile_elementwise_inout([](auto& c) { c = 0; }, c_block_tile);
// LDS write 0
Base::LocalPrefill(a_copy_lds_window, a_block_tiles.get(I0{}), a_element_func);
Base::LocalPrefill(b_copy_lds_window, b_block_tiles.get(I0{}), b_element_func);
// Global prefetch [1, PrefetchStages]
static_for<1, PrefetchStages, 1>{}([&](auto prefetch_idx) {
Base::GlobalPrefetch(a_block_tiles.get(number<prefetch_idx>{}), a_copy_dram_window);
Base::GlobalPrefetch(b_block_tiles.get(number<prefetch_idx>{}), b_copy_dram_window);
});
// main body
if constexpr(HasHotLoop)
{
index_t i = 0;
do
{
static_for<0, PrefetchStages, 1>{}([&](auto prefetch_idx) {
block_sync_lds();
block_gemm.LocalPrefetch(a_lds_gemm_window, b_lds_gemm_window);
block_gemm(c_block_tile, a_lds_gemm_window, b_lds_gemm_window);
block_sync_lds();
Base::LocalPrefill(
a_copy_lds_window,
a_block_tiles.get(number<(prefetch_idx + 1) % PrefetchStages>{}),
a_element_func);
Base::LocalPrefill(
b_copy_lds_window,
b_block_tiles.get(number<(prefetch_idx + 1) % PrefetchStages>{}),
b_element_func);
Base::GlobalPrefetch(a_block_tiles.get(number<prefetch_idx>{}),
a_copy_dram_window);
Base::GlobalPrefetch(b_block_tiles.get(number<prefetch_idx>{}),
b_copy_dram_window);
});
i += PrefetchStages;
} while(i < (num_loop - PrefetchStages));
}
template <typename DstTileWindow, typename SrcBlockTile, typename ElementFunction>
CK_TILE_DEVICE void LocalPrefill(DstTileWindow& lds_tile_window,
const SrcBlockTile& src_block_tile,
const ElementFunction& element_func) const
auto HotLoopTail = [&](auto tail_num) {
static_for<1, tail_num, 1>{}([&](auto prefetch_idx) {
block_sync_lds();
block_gemm.LocalPrefetch(a_lds_gemm_window, b_lds_gemm_window);
block_gemm(c_block_tile, a_lds_gemm_window, b_lds_gemm_window);
block_sync_lds();
Base::LocalPrefill(a_copy_lds_window,
a_block_tiles.get(number<prefetch_idx>{}),
a_element_func);
Base::LocalPrefill(b_copy_lds_window,
b_block_tiles.get(number<prefetch_idx>{}),
b_element_func);
});
block_sync_lds();
block_gemm.LocalPrefetch(a_lds_gemm_window, b_lds_gemm_window);
block_gemm(c_block_tile, a_lds_gemm_window, b_lds_gemm_window);
};
if constexpr(TailNum == TailNumber::One)
{
block_sync_lds();
block_gemm.LocalPrefetch(a_lds_gemm_window, b_lds_gemm_window);
block_gemm(c_block_tile, a_lds_gemm_window, b_lds_gemm_window);
}
else if constexpr(TailNum == TailNumber::Two)
{
HotLoopTail(number<2>{});
}
else if constexpr(TailNum == TailNumber::Three)
{
const auto block_tile_tmp = tile_elementwise_in(element_func, src_block_tile);
store_tile(lds_tile_window, block_tile_tmp);
HotLoopTail(number<3>{});
}
else if constexpr(TailNum == TailNumber::Four)
{
HotLoopTail(number<4>{});
}
else if constexpr(TailNum == TailNumber::Five)
{
HotLoopTail(number<5>{});
}
else if constexpr(TailNum == TailNumber::Six)
{
HotLoopTail(number<6>{});
}
else if constexpr(TailNum == TailNumber::Seven)
{
HotLoopTail(number<7>{});
}
else if constexpr(TailNum == TailNumber::Full)
{
HotLoopTail(number<PrefetchStages>{});
}
return c_block_tile;
}
};
template <>
struct PipelineImpl<GemmPipelineScheduler::Interwave> : public PipelineImplBase
{
using Base = PipelineImplBase;
template <bool HasHotLoop,
TailNumber TailNum,
typename ADramBlockWindowTmp,
......@@ -185,69 +349,41 @@ struct GemmPipelineAgBgCrMem : public BaseGemmPipelineAgBgCrMem<Problem>
"A/B Dram block window should have the same data type as appropriate "
"([A|B]DataType) defined in Problem definition!");
static_assert(MPerBlock == ADramBlockWindowTmp{}.get_window_lengths()[number<0>{}] &&
NPerBlock ==
BDramBlockWindowTmp{}.get_window_lengths()[number<0>{}] &&
KPerBlock == ADramBlockWindowTmp{}.get_window_lengths()[number<1>{}],
static_assert(MPerBlock == ADramBlockWindowTmp{}.get_window_lengths()[I0{}] &&
NPerBlock == BDramBlockWindowTmp{}.get_window_lengths()[I0{}] &&
KPerBlock == ADramBlockWindowTmp{}.get_window_lengths()[I1{}],
"A/B block window appropriate sizes must be equal to MPerBlock/NPerblock"
" or KPerBlock!");
// ------------------------------------------------------------------------------------
// Definitions of all needed tiles
// A tile in LDS
ADataType* p_a_lds = static_cast<ADataType*>(p_smem);
constexpr auto a_lds_block_desc = Policy::template MakeALdsBlockDescriptor<Problem>();
auto a_lds_block = make_tensor_view<address_space_enum::lds>(p_a_lds, a_lds_block_desc);
// TODO: LDS alignment should come from Policy!
constexpr index_t a_lds_block_space_size_aligned =
integer_divide_ceil(sizeof(ADataType) * a_lds_block_desc.get_element_space_size(),
16) *
16;
// B tile in LDS
BDataType* p_b_lds = static_cast<BDataType*>(
static_cast<void*>(static_cast<char*>(p_smem) + a_lds_block_space_size_aligned));
constexpr auto b_lds_block_desc = Policy::template MakeBLdsBlockDescriptor<Problem>();
auto b_lds_block = make_tensor_view<address_space_enum::lds>(p_b_lds, b_lds_block_desc);
// A/B tiles in LDS
// With c++20 could simplify to below line.
// Currently get error: captured structured bindings are a C++20 extension
// auto&& [a_lds_block, b_lds_block] = Base::GetABLdsTensorViews(p_smem);
auto ab_lds_blocks = Base::GetABLdsTensorViews(p_smem);
auto& a_lds_block = ab_lds_blocks.at(I0{});
auto& b_lds_block = ab_lds_blocks.at(I1{});
// A DRAM tile window for load
auto a_copy_dram_window =
make_tile_window(a_dram_block_window_tmp.get_bottom_tensor_view(),
make_tuple(number<MPerBlock>{}, number<KPerBlock>{}),
a_dram_block_window_tmp.get_window_origin(),
Policy::template MakeADramTileDistribution<Problem>());
// A LDS tile window for store
auto a_copy_lds_window =
make_tile_window(a_lds_block,
make_tuple(number<MPerBlock>{}, number<KPerBlock>{}),
{0, 0},
a_copy_dram_window.get_tile_distribution());
// B DRAM tile window for load
auto b_copy_dram_window =
make_tile_window(b_dram_block_window_tmp.get_bottom_tensor_view(),
make_tuple(number<NPerBlock>{}, number<KPerBlock>{}),
b_dram_block_window_tmp.get_window_origin(),
Policy::template MakeBDramTileDistribution<Problem>());
// A LDS tile for block GEMM
auto a_windows = Base::GetAWindows(a_dram_block_window_tmp, a_lds_block);
auto& a_copy_dram_window = a_windows.at(I0{});
auto& a_copy_lds_window = a_windows.at(I1{});
auto& a_lds_gemm_window = a_windows.at(I2{});
// B DRAM tile window for load
// B LDS tile window for store
auto b_copy_lds_window =
make_tile_window(b_lds_block,
make_tuple(number<NPerBlock>{}, number<KPerBlock>{}),
{0, 0},
b_copy_dram_window.get_tile_distribution());
// A LDS tile for block GEMM
auto a_lds_gemm_window = make_tile_window(
a_lds_block, make_tuple(number<MPerBlock>{}, number<KPerBlock>{}), {0, 0});
// B LDS tile for block GEMM
auto b_lds_gemm_window = make_tile_window(
b_lds_block, make_tuple(number<NPerBlock>{}, number<KPerBlock>{}), {0, 0});
auto b_windows = Base::GetBWindows(b_dram_block_window_tmp, b_lds_block);
auto& b_copy_dram_window = b_windows.at(I0{});
auto& b_copy_lds_window = b_windows.at(I1{});
auto& b_lds_gemm_window = b_windows.at(I2{});
// Block GEMM
constexpr auto block_gemm = BlockGemm();
auto block_gemm = BlockGemm();
auto c_block_tile = block_gemm.MakeCBlockTile();
using ABlockTileDistr = decltype(a_copy_dram_window.get_tile_distribution());
......@@ -266,20 +402,20 @@ struct GemmPipelineAgBgCrMem : public BaseGemmPipelineAgBgCrMem<Problem>
// prefetch
// global read 0
GlobalPrefetch(a_block_tiles.get(I0{}), a_copy_dram_window);
GlobalPrefetch(b_block_tiles.get(I0{}), b_copy_dram_window);
Base::GlobalPrefetch(a_block_tiles.get(I0{}), a_copy_dram_window);
Base::GlobalPrefetch(b_block_tiles.get(I0{}), b_copy_dram_window);
// initialize C
tile_elementwise_inout([](auto& c) { c = 0; }, c_block_tile);
// LDS write 0
LocalPrefill(a_copy_lds_window, a_block_tiles.get(I0{}), a_element_func);
LocalPrefill(b_copy_lds_window, b_block_tiles.get(I0{}), b_element_func);
Base::LocalPrefill(a_copy_lds_window, a_block_tiles.get(I0{}), a_element_func);
Base::LocalPrefill(b_copy_lds_window, b_block_tiles.get(I0{}), b_element_func);
// Global prefetch [1, PrefetchStages]
static_for<1, PrefetchStages, 1>{}([&](auto prefetch_idx) {
GlobalPrefetch(a_block_tiles.get(number<prefetch_idx>{}), a_copy_dram_window);
GlobalPrefetch(b_block_tiles.get(number<prefetch_idx>{}), b_copy_dram_window);
Base::GlobalPrefetch(a_block_tiles.get(number<prefetch_idx>{}), a_copy_dram_window);
Base::GlobalPrefetch(b_block_tiles.get(number<prefetch_idx>{}), b_copy_dram_window);
});
// main body
......@@ -290,23 +426,21 @@ struct GemmPipelineAgBgCrMem : public BaseGemmPipelineAgBgCrMem<Problem>
{
static_for<0, PrefetchStages, 1>{}([&](auto prefetch_idx) {
block_sync_lds();
// block_gemm.LocalPrefetch();
block_gemm(c_block_tile, a_lds_gemm_window, b_lds_gemm_window);
// no second block_sync_lds because it's interwave
block_sync_lds();
LocalPrefill(
Base::LocalPrefill(
a_copy_lds_window,
a_block_tiles.get(number<(prefetch_idx + 1) % PrefetchStages>{}),
a_element_func);
LocalPrefill(
Base::LocalPrefill(
b_copy_lds_window,
b_block_tiles.get(number<(prefetch_idx + 1) % PrefetchStages>{}),
b_element_func);
GlobalPrefetch(a_block_tiles.get(number<prefetch_idx>{}),
Base::GlobalPrefetch(a_block_tiles.get(number<prefetch_idx>{}),
a_copy_dram_window);
GlobalPrefetch(b_block_tiles.get(number<prefetch_idx>{}),
Base::GlobalPrefetch(b_block_tiles.get(number<prefetch_idx>{}),
b_copy_dram_window);
});
......@@ -317,28 +451,24 @@ struct GemmPipelineAgBgCrMem : public BaseGemmPipelineAgBgCrMem<Problem>
auto HotLoopTail = [&](auto tail_num) {
static_for<1, tail_num, 1>{}([&](auto prefetch_idx) {
block_sync_lds();
// block_gemm.LocalPrefetch();
block_gemm(c_block_tile, a_lds_gemm_window, b_lds_gemm_window);
// no second block_sync_lds because it's interwave
block_sync_lds();
LocalPrefill(a_copy_lds_window,
Base::LocalPrefill(a_copy_lds_window,
a_block_tiles.get(number<prefetch_idx>{}),
a_element_func);
LocalPrefill(b_copy_lds_window,
Base::LocalPrefill(b_copy_lds_window,
b_block_tiles.get(number<prefetch_idx>{}),
b_element_func);
});
block_sync_lds();
// block_gemm.LocalPrefetch();
block_gemm(c_block_tile, a_lds_gemm_window, b_lds_gemm_window);
};
if constexpr(TailNum == TailNumber::One)
{
block_sync_lds();
// block_gemm.LocalPrefetch();
block_gemm(c_block_tile, a_lds_gemm_window, b_lds_gemm_window);
}
else if constexpr(TailNum == TailNumber::Two)
......
......@@ -11,6 +11,7 @@ namespace ck_tile {
enum struct GemmPipelineScheduler
{
Default,
Intrawave,
Interwave,
};
......@@ -43,6 +44,7 @@ inline std::ostream& operator<<(std::ostream& os, const ck_tile::GemmPipelineSch
{
switch(s)
{
case ck_tile::GemmPipelineScheduler::Default: os << "Default"; break;
case ck_tile::GemmPipelineScheduler::Intrawave: os << "Intrawave"; break;
case ck_tile::GemmPipelineScheduler::Interwave: os << "Interwave"; break;
default: os << "";
......
......@@ -124,7 +124,7 @@ struct GemmPipelineAGmemBGmemCRegV1
b_lds_block, make_tuple(number<kNPerBlock>{}, number<kKPerBlock>{}), {0, 0});
// Block GEMM
constexpr auto block_gemm = Policy::template GetBlockGemm<Problem>();
auto block_gemm = Policy::template GetBlockGemm<Problem>();
// Acc register tile
auto c_block_tile = decltype(block_gemm(a_lds_gemm_window, b_lds_gemm_window)){};
......
......@@ -4,6 +4,7 @@
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/ops/gemm/warp/warp_gemm_dispatcher.hpp"
namespace ck_tile {
......@@ -52,6 +53,7 @@ struct GemmPipelineAGmemBGmemCRegV1DefaultPolicy
constexpr index_t kMPerBlock = Problem::BlockGemmShape::kM;
constexpr index_t kKPerBlock = Problem::BlockGemmShape::kK;
// TODO: this 8 is AK1! should be a policy parameter!
constexpr auto a_lds_block_desc_0 = make_naive_tensor_descriptor(
make_tuple(number<kKPerBlock / 8>{}, number<kMPerBlock>{}, number<8>{}),
make_tuple(number<(kMPerBlock + 1) * 8>{}, number<8>{}, number<1>{}),
......@@ -264,6 +266,9 @@ struct GemmPipelineAGmemBGmemCRegV1DefaultPolicy
static_assert(M2 != 0, "M2 is zero, which will lead to a division by zero error.");
static_assert(M1 != 0, "M1 is zero, which will lead to a division by zero error.");
constexpr index_t M0 = MPerBlock / (M2 * M1);
static_assert(M0 * M1 * M2 == MPerBlock,
"Incorrect M0, M2, M1 configuration! "
"M0, M1, M2 must cover whole MPerBlock!");
return make_static_tile_distribution(
tile_distribution_encoding<sequence<1>,
......@@ -277,6 +282,9 @@ struct GemmPipelineAGmemBGmemCRegV1DefaultPolicy
{
constexpr index_t M0 = BlockSize / get_warp_size();
constexpr index_t M1 = MPerBlock / (M2 * M0);
static_assert(M0 * M1 * M2 == MPerBlock,
"Incorrect M0, M1, M2 configuration! "
"M0, M1, M2 must cover whole MPerBlock!");
return make_static_tile_distribution(
tile_distribution_encoding<sequence<1>,
tuple<sequence<M0, M1, M2>, sequence<K0, K1>>,
......@@ -350,6 +358,9 @@ struct GemmPipelineAGmemBGmemCRegV1DefaultPolicy
static_assert(N2 != 0, "N2 is zero, which will lead to a division by zero error.");
static_assert(N1 != 0, "N1 is zero, which will lead to a division by zero error.");
constexpr index_t N0 = NPerBlock / (N2 * N1);
static_assert(N0 * N1 * N2 == NPerBlock,
"Incorrect N0, N1, N2 configuration! "
"N0, N1, N2 must cover whole NPerBlock!");
return make_static_tile_distribution(
tile_distribution_encoding<sequence<1>,
......@@ -364,7 +375,9 @@ struct GemmPipelineAGmemBGmemCRegV1DefaultPolicy
{
constexpr index_t N0 = BlockSize / get_warp_size();
constexpr index_t N1 = NPerBlock / (N2 * N0);
static_assert(N0 * N1 * N2 == NPerBlock,
"Incorrect N0, N1, N2 configuration! "
"N0, N1, N2 must cover whole NPerBlock!");
return make_static_tile_distribution(
tile_distribution_encoding<sequence<1>,
tuple<sequence<N0, N1, N2>, sequence<K0, K1>>,
......@@ -475,9 +488,28 @@ struct GemmPipelineAGmemBGmemCRegV1DefaultPolicy
template <typename Problem>
CK_TILE_HOST_DEVICE static constexpr auto GetBlockGemm()
{
using BlockGemmPolicy = BlockGemmASmemBSmemCRegV1DefaultPolicy;
return BlockGemmASmemBSmemCRegV1<Problem, BlockGemmPolicy>{};
constexpr bool TransposeC = false;
constexpr auto I0 = number<0>{};
constexpr auto I1 = number<1>{};
constexpr auto I2 = number<2>{};
using AccDataType = float;
using BlockWarps = typename Problem::BlockGemmShape::BlockWarps;
using WarpTile = typename Problem::BlockGemmShape::WarpTile;
using WarpGemm = WarpGemmMfmaDispatcher<typename Problem::ADataType,
typename Problem::BDataType,
AccDataType,
WarpTile::at(I0),
WarpTile::at(I1),
WarpTile::at(I2),
TransposeC>;
using BlockGemmPolicy = BlockGemmASmemBSmemCRegV1CustomPolicy<typename Problem::ADataType,
typename Problem::BDataType,
typename Problem::CDataType,
BlockWarps,
WarpGemm>;
return BlockUniversalGemmAsBsCr<Problem, BlockGemmPolicy>{};
}
};
......
......@@ -33,6 +33,8 @@ struct GemmPipelineProblemBase
static constexpr bool kPadN = GemmTraits::kPadN;
static constexpr bool kPadK = GemmTraits::kPadK;
static constexpr auto Scheduler = GemmPipelineScheduler::Default;
CK_TILE_HOST_DEVICE static constexpr auto GetAlignmentA()
{
if constexpr(std::is_same_v<ALayout, ck_tile::tensor_layout::gemm::ColumnMajor>)
......
......@@ -10,114 +10,134 @@
namespace ck_tile {
// fp16
using WarpGemmMfmaF16F16F32M32N32K8 =
WarpGemmImpl<WarpGemmAtrributeMfma<WarpGemmAttributeMfmaImplF16F16F32M32N32K8>>;
using WarpGemmMfmaF16F16F32M16N16K16 =
WarpGemmImpl<WarpGemmAtrributeMfma<WarpGemmAttributeMfmaImplF16F16F32M16N16K16>>;
using WarpGemmMfmaF16F16F32M32N32K8 = WarpGemmImpl<
WarpGemmAtrributeMfma<WarpGemmAttributeMfmaImplF16F16F32M32N32K8<WGAttrCtlEnum::Default_>>>;
using WarpGemmMfmaF16F16F32M32N32K16 =
WarpGemmImpl<WarpGemmAtrributeMfmaIterateK<WarpGemmAttributeMfmaImplF16F16F32M32N32K8, 2>>;
using WarpGemmMfmaF16F16F32M16N16K16 = WarpGemmImpl<
WarpGemmAtrributeMfma<WarpGemmAttributeMfmaImplF16F16F32M16N16K16<WGAttrCtlEnum::Default_>>>;
using WarpGemmMfmaF16F16F32M16N16K32 =
WarpGemmImpl<WarpGemmAtrributeMfmaIterateK<WarpGemmAttributeMfmaImplF16F16F32M16N16K16, 2>>;
using WarpGemmMfmaF16F16F32M32N32K16 = WarpGemmImpl<WarpGemmAtrributeMfmaIterateK<
WarpGemmAttributeMfmaImplF16F16F32M32N32K8<WGAttrCtlEnum::Default_>,
2>>;
using WarpGemmMfmaF16F16F32M32N32K8SwizzleA = WarpGemmImpl<
WarpGemmAtrributeMfmaIterateK_SwizzleA<WarpGemmAttributeMfmaImplF16F16F32M32N32K8, 1>>;
using WarpGemmMfmaF16F16F32M16N16K32 = WarpGemmImpl<WarpGemmAtrributeMfmaIterateK<
WarpGemmAttributeMfmaImplF16F16F32M16N16K16<WGAttrCtlEnum::Default_>,
2>>;
using WarpGemmMfmaF16F16F32M32N32K16SwizzleA = WarpGemmImpl<
WarpGemmAtrributeMfmaIterateK_SwizzleA<WarpGemmAttributeMfmaImplF16F16F32M32N32K8, 2>>;
using WarpGemmMfmaF16F16F32M32N32K8SwizzleA = WarpGemmImpl<WarpGemmAtrributeMfmaIterateK_SwizzleA<
WarpGemmAttributeMfmaImplF16F16F32M32N32K8<WGAttrCtlEnum::Default_>,
1>>;
using WarpGemmMfmaF16F16F32M32N32K8TransposedCDistribution = WarpGemmImpl<
WarpGemmAtrributeMfmaTransposedCDistribution<WarpGemmAttributeMfmaImplF16F16F32M32N32K8>>;
using WarpGemmMfmaF16F16F32M32N32K16SwizzleA = WarpGemmImpl<WarpGemmAtrributeMfmaIterateK_SwizzleA<
WarpGemmAttributeMfmaImplF16F16F32M32N32K8<WGAttrCtlEnum::Default_>,
2>>;
using WarpGemmMfmaF16F16F32M16N16K16TransposedCDistribution = WarpGemmImpl<
WarpGemmAtrributeMfmaTransposedCDistribution<WarpGemmAttributeMfmaImplF16F16F32M16N16K16>>;
using WarpGemmMfmaF16F16F32M32N32K8TransposedCDistribution =
WarpGemmImpl<WarpGemmAtrributeMfmaTransposedCDistribution<
WarpGemmAttributeMfmaImplF16F16F32M32N32K8<WGAttrCtlEnum::Default_>>>;
using WarpGemmMfmaF16F16F32M16N16K16TransposedCDistribution =
WarpGemmImpl<WarpGemmAtrributeMfmaTransposedCDistribution<
WarpGemmAttributeMfmaImplF16F16F32M16N16K16<WGAttrCtlEnum::Default_>>>;
using WarpGemmMfmaF16F16F32M32N32K16TransposedCDistribution =
WarpGemmImpl<WarpGemmAtrributeMfmaIterateKAndTransposedCDistribution<
WarpGemmAttributeMfmaImplF16F16F32M32N32K8,
WarpGemmAttributeMfmaImplF16F16F32M32N32K8<WGAttrCtlEnum::Default_>,
2>>;
using WarpGemmMfmaF16F16F32M16N16K32TransposedCDistribution =
WarpGemmImpl<WarpGemmAtrributeMfmaIterateKAndTransposedCDistribution<
WarpGemmAttributeMfmaImplF16F16F32M16N16K16,
WarpGemmAttributeMfmaImplF16F16F32M16N16K16<WGAttrCtlEnum::Default_>,
2>>;
using WarpGemmMfmaF16F16F32M32N32K16SwizzleBTransposedCDistribution =
WarpGemmImpl<WarpGemmAtrributeMfmaIterateKAndTransposedCDistribution_SwizzleB<
WarpGemmAttributeMfmaImplF16F16F32M32N32K8,
WarpGemmAttributeMfmaImplF16F16F32M32N32K8<WGAttrCtlEnum::Default_>,
2>>;
// bf16
using WarpGemmMfmaBf16Bf16F32M32N32K8 =
WarpGemmImpl<WarpGemmAtrributeMfma<WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8>>;
using WarpGemmMfmaBf16Bf16F32M16N16K16 =
WarpGemmImpl<WarpGemmAtrributeMfma<WarpGemmAttributeMfmaImplBf16Bf16F32M16N16K16>>;
using WarpGemmMfmaBf16Bf16F32M32N32K8 = WarpGemmImpl<
WarpGemmAtrributeMfma<WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8<WGAttrCtlEnum::Default_>>>;
using WarpGemmMfmaBf16Bf16F32M32N32K16 =
WarpGemmImpl<WarpGemmAtrributeMfmaIterateK<WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8, 2>>;
using WarpGemmMfmaBf16Bf16F32M16N16K16 = WarpGemmImpl<
WarpGemmAtrributeMfma<WarpGemmAttributeMfmaImplBf16Bf16F32M16N16K16<WGAttrCtlEnum::Default_>>>;
using WarpGemmMfmaBf16Bf16F32M16N16K32 =
WarpGemmImpl<WarpGemmAtrributeMfmaIterateK<WarpGemmAttributeMfmaImplBf16Bf16F32M16N16K16, 2>>;
using WarpGemmMfmaBf16Bf16F32M32N32K16 = WarpGemmImpl<WarpGemmAtrributeMfmaIterateK<
WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8<WGAttrCtlEnum::Default_>,
2>>;
using WarpGemmMfmaBf16Bf16F32M32N32K8SwizzleA = WarpGemmImpl<
WarpGemmAtrributeMfmaIterateK_SwizzleA<WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8, 1>>;
using WarpGemmMfmaBf16Bf16F32M16N16K32 = WarpGemmImpl<WarpGemmAtrributeMfmaIterateK<
WarpGemmAttributeMfmaImplBf16Bf16F32M16N16K16<WGAttrCtlEnum::Default_>,
2>>;
using WarpGemmMfmaBf16Bf16F32M32N32K8SwizzleA = WarpGemmImpl<WarpGemmAtrributeMfmaIterateK_SwizzleA<
WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8<WGAttrCtlEnum::Default_>,
1>>;
using WarpGemmMfmaBf16Bf16F32M32N32K16SwizzleA = WarpGemmImpl<
WarpGemmAtrributeMfmaIterateK_SwizzleA<WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8, 2>>;
using WarpGemmMfmaBf16Bf16F32M32N32K16SwizzleA =
WarpGemmImpl<WarpGemmAtrributeMfmaIterateK_SwizzleA<
WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8<WGAttrCtlEnum::Default_>,
2>>;
using WarpGemmMfmaBf16Bf16F32M32N32K8TransposedCDistribution = WarpGemmImpl<
WarpGemmAtrributeMfmaTransposedCDistribution<WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8>>;
using WarpGemmMfmaBf16Bf16F32M32N32K8TransposedCDistribution =
WarpGemmImpl<WarpGemmAtrributeMfmaTransposedCDistribution<
WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8<WGAttrCtlEnum::Default_>>>;
using WarpGemmMfmaBf16Bf16F32M16N16K16TransposedCDistribution = WarpGemmImpl<
WarpGemmAtrributeMfmaTransposedCDistribution<WarpGemmAttributeMfmaImplBf16Bf16F32M16N16K16>>;
using WarpGemmMfmaBf16Bf16F32M16N16K16TransposedCDistribution =
WarpGemmImpl<WarpGemmAtrributeMfmaTransposedCDistribution<
WarpGemmAttributeMfmaImplBf16Bf16F32M16N16K16<WGAttrCtlEnum::Default_>>>;
using WarpGemmMfmaBf16Bf16F32M32N32K16TransposedCDistribution =
WarpGemmImpl<WarpGemmAtrributeMfmaIterateKAndTransposedCDistribution<
WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8,
WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8<WGAttrCtlEnum::Default_>,
2>>;
using WarpGemmMfmaBf16Bf16F32M16N16K32TransposedCDistribution =
WarpGemmImpl<WarpGemmAtrributeMfmaIterateKAndTransposedCDistribution<
WarpGemmAttributeMfmaImplBf16Bf16F32M16N16K16,
WarpGemmAttributeMfmaImplBf16Bf16F32M16N16K16<WGAttrCtlEnum::Default_>,
2>>;
using WarpGemmMfmaBf16Bf16F32M32N32K16SwizzleBTransposedCDistribution =
WarpGemmImpl<WarpGemmAtrributeMfmaIterateKAndTransposedCDistribution_SwizzleB<
WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8,
WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8<WGAttrCtlEnum::Default_>,
2>>;
// fp8
using WarpGemmMfma_f32_32x32x16_fp8_fp8 =
WarpGemmImpl<WarpGemmAtrributeMfma<WarpGemmAttributeMfmaImpl_f32_32x32x16_fp8_fp8>>;
using WarpGemmMfma_f32_32x32x16_fp8_bf8 =
WarpGemmImpl<WarpGemmAtrributeMfma<WarpGemmAttributeMfmaImpl_f32_32x32x16_fp8_bf8>>;
using WarpGemmMfma_f32_32x32x16_fp8_fp8 = WarpGemmImpl<
WarpGemmAtrributeMfma<WarpGemmAttributeMfmaImpl_f32_32x32x16_fp8_fp8<WGAttrCtlEnum::Default_>>>;
using WarpGemmMfma_f32_32x32x16_fp8_bf8 = WarpGemmImpl<
WarpGemmAtrributeMfma<WarpGemmAttributeMfmaImpl_f32_32x32x16_fp8_bf8<WGAttrCtlEnum::Default_>>>;
using WarpGemmMfma_f32_32x32x16_bf8_fp8 =
WarpGemmImpl<WarpGemmAtrributeMfma<WarpGemmAttributeMfmaImpl_f32_32x32x16_bf8_fp8>>;
using WarpGemmMfma_f32_32x32x16_bf8_fp8 = WarpGemmImpl<
WarpGemmAtrributeMfma<WarpGemmAttributeMfmaImpl_f32_32x32x16_bf8_fp8<WGAttrCtlEnum::Default_>>>;
using WarpGemmMfma_f32_32x32x16_bf8_bf8 =
WarpGemmImpl<WarpGemmAtrributeMfma<WarpGemmAttributeMfmaImpl_f32_32x32x16_bf8_bf8>>;
using WarpGemmMfma_f32_32x32x16_bf8_bf8 = WarpGemmImpl<
WarpGemmAtrributeMfma<WarpGemmAttributeMfmaImpl_f32_32x32x16_bf8_bf8<WGAttrCtlEnum::Default_>>>;
using WarpGemmMfma_f32_32x32x16_fp8_fp8_CTransposed = WarpGemmImpl<
WarpGemmAtrributeMfmaTransposedCDistribution<WarpGemmAttributeMfmaImpl_f32_32x32x16_fp8_fp8>>;
using WarpGemmMfma_f32_32x32x16_fp8_fp8_CTransposed =
WarpGemmImpl<WarpGemmAtrributeMfmaTransposedCDistribution<
WarpGemmAttributeMfmaImpl_f32_32x32x16_fp8_fp8<WGAttrCtlEnum::Default_>>>;
using WarpGemmMfma_f32_32x32x16_fp8_bf8_CTransposed = WarpGemmImpl<
WarpGemmAtrributeMfmaTransposedCDistribution<WarpGemmAttributeMfmaImpl_f32_32x32x16_fp8_bf8>>;
using WarpGemmMfma_f32_32x32x16_fp8_bf8_CTransposed =
WarpGemmImpl<WarpGemmAtrributeMfmaTransposedCDistribution<
WarpGemmAttributeMfmaImpl_f32_32x32x16_fp8_bf8<WGAttrCtlEnum::Default_>>>;
using WarpGemmMfma_f32_32x32x16_bf8_fp8_CTransposed = WarpGemmImpl<
WarpGemmAtrributeMfmaTransposedCDistribution<WarpGemmAttributeMfmaImpl_f32_32x32x16_bf8_fp8>>;
using WarpGemmMfma_f32_32x32x16_bf8_fp8_CTransposed =
WarpGemmImpl<WarpGemmAtrributeMfmaTransposedCDistribution<
WarpGemmAttributeMfmaImpl_f32_32x32x16_bf8_fp8<WGAttrCtlEnum::Default_>>>;
using WarpGemmMfma_f32_32x32x16_bf8_bf8_CTransposed = WarpGemmImpl<
WarpGemmAtrributeMfmaTransposedCDistribution<WarpGemmAttributeMfmaImpl_f32_32x32x16_bf8_bf8>>;
using WarpGemmMfma_f32_32x32x16_bf8_bf8_CTransposed =
WarpGemmImpl<WarpGemmAtrributeMfmaTransposedCDistribution<
WarpGemmAttributeMfmaImpl_f32_32x32x16_bf8_bf8<WGAttrCtlEnum::Default_>>>;
template <index_t swizzle_factor = 2>
using WarpGemmMfmaFp8Fp8F32M32N32K16SwizzleBTransposedCDistribution =
WarpGemmImpl<WarpGemmAtrributeMfmaIterateKAndTransposedCDistribution_SwizzleB<
WarpGemmAttributeMfmaImpl_f32_32x32x16_f8_base<fp8_t, fp8_t>,
WarpGemmAttributeMfmaImpl_f32_32x32x16_f8_base<fp8_t, fp8_t, WGAttrCtlEnum::Default_>,
2,
swizzle_factor>>;
......
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -24,6 +24,9 @@ struct WarpGemmAtrributeMfma
static constexpr index_t kM = Impl::kM;
static constexpr index_t kN = Impl::kN;
static constexpr index_t kK = Impl::kK;
static constexpr index_t kKPerThread = Impl::kABKPerLane;
CK_TILE_HOST_DEVICE static constexpr auto get_num_of_access() { return 1; }
using AWarpDstrEncoding = tile_distribution_encoding<
sequence<>,
......@@ -51,10 +54,13 @@ struct WarpGemmAtrributeMfma
sequence<0, 2>>;
// c_vec += a_vec * b_vec
CK_TILE_DEVICE void
operator()(CVecType& c_vec, const AVecType& a_vec, const BVecType& b_vec) const
template <bool post_nop_ = false>
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
bool_constant<post_nop_> = {}) const
{
Impl{}(c_vec, a_vec, b_vec);
Impl{}(c_vec, a_vec, b_vec, bool_constant<post_nop_>{});
}
// c_vec = a_vec * b_vec
......@@ -84,6 +90,9 @@ struct WarpGemmAtrributeMfmaIterateK
static constexpr index_t kM = Impl::kM;
static constexpr index_t kN = Impl::kN;
static constexpr index_t kK = Impl::kK * kKIter;
static constexpr index_t kKPerThread = Impl::kABKPerLane * kKIter;
CK_TILE_HOST_DEVICE static constexpr auto get_num_of_access() { return kKIter; }
using AWarpDstrEncoding = tile_distribution_encoding<
sequence<>,
......@@ -111,8 +120,11 @@ struct WarpGemmAtrributeMfmaIterateK
sequence<0, 2>>;
// c_vec += a_vec * b_vec
CK_TILE_DEVICE void
operator()(CVecType& c_vec, const AVecType& a_vec, const BVecType& b_vec) const
template <bool post_nop_ = false>
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
bool_constant<post_nop_> = {}) const
{
using buf_a = thread_buffer<typename Impl::AVecType, kKIter>;
using buf_b = thread_buffer<typename Impl::BVecType, kKIter>;
......@@ -122,10 +134,33 @@ struct WarpGemmAtrributeMfmaIterateK
reinterpret_cast<const buf_a&>(a_vec)
.template get_as<typename Impl::AVecType>()[iKIter],
reinterpret_cast<const buf_b&>(b_vec)
.template get_as<typename Impl::BVecType>()[iKIter]);
.template get_as<typename Impl::BVecType>()[iKIter],
bool_constant<post_nop_>{});
});
}
template <index_t iKIter, bool post_nop_ = false>
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
number<iKIter>,
bool_constant<post_nop_> = {}) const
{
using buf_a = thread_buffer<typename Impl::AVecType, kKIter>;
using buf_b = thread_buffer<typename Impl::BVecType, kKIter>;
static_assert(iKIter < kKIter);
// static_for<0, kKIter, 1>{}([&](auto iKIter) {
Impl{}(c_vec,
reinterpret_cast<const buf_a&>(a_vec)
.template get_as<typename Impl::AVecType>()[iKIter],
reinterpret_cast<const buf_b&>(b_vec)
.template get_as<typename Impl::BVecType>()[iKIter],
bool_constant<post_nop_>{});
//});
}
// c_vec = a_vec * b_vec
CK_TILE_DEVICE CVecType operator()(const AVecType& a_vec, const BVecType& b_vec) const
{
......@@ -167,6 +202,9 @@ struct WarpGemmAtrributeMfmaTransposedCDistribution
static constexpr index_t kM = Impl::kN;
static constexpr index_t kN = Impl::kM;
static constexpr index_t kK = Impl::kK;
static constexpr index_t kKPerThread = Impl::kABKPerLane;
CK_TILE_HOST_DEVICE static constexpr auto get_num_of_access() { return 1; }
using AWarpDstrEncoding = tile_distribution_encoding<
sequence<>,
......@@ -194,11 +232,14 @@ struct WarpGemmAtrributeMfmaTransposedCDistribution
sequence<0, 2>>;
// c_vec += a_vec * b_vec
CK_TILE_DEVICE void
operator()(CVecType& c_vec, const AVecType& a_vec, const BVecType& b_vec) const
template <bool post_nop_ = false>
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
bool_constant<post_nop_> = {}) const
{
// swap A and B
Impl{}(c_vec, b_vec, a_vec);
Impl{}(c_vec, b_vec, a_vec, bool_constant<post_nop_>{});
}
// c_vec = a_vec * b_vec
......@@ -225,6 +266,9 @@ struct WarpGemmAtrributeMfmaTransposedCDistribution_SwizzleB
static constexpr index_t kM = Impl::kN;
static constexpr index_t kN = Impl::kM;
static constexpr index_t kK = Impl::kK;
static constexpr index_t kKPerThread = Impl::kABKPerLane;
CK_TILE_HOST_DEVICE static constexpr auto get_num_of_access() { return 1; }
using AWarpDstrEncoding = tile_distribution_encoding<
sequence<>,
......@@ -255,12 +299,15 @@ struct WarpGemmAtrributeMfmaTransposedCDistribution_SwizzleB
sequence<2, 2>,
sequence<0, 2>>;
template <bool post_nop_ = false>
// c_vec += a_vec * b_vec
CK_TILE_DEVICE void
operator()(CVecType& c_vec, const AVecType& a_vec, const BVecType& b_vec) const
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
bool_constant<post_nop_> = {}) const
{
// swap A and B
Impl{}(c_vec, b_vec, a_vec);
Impl{}(c_vec, b_vec, a_vec, bool_constant<post_nop_>{});
}
// c_vec = a_vec * b_vec
......@@ -290,6 +337,9 @@ struct WarpGemmAtrributeMfmaIterateKAndTransposedCDistribution
static constexpr index_t kM = Impl::kN;
static constexpr index_t kN = Impl::kM;
static constexpr index_t kK = Impl::kK * kKIter;
static constexpr index_t kKPerThread = Impl::kABKPerLane * kKIter;
CK_TILE_HOST_DEVICE static constexpr auto get_num_of_access() { return kKIter; }
using AWarpDstrEncoding = tile_distribution_encoding<
sequence<>,
......@@ -316,9 +366,12 @@ struct WarpGemmAtrributeMfmaIterateKAndTransposedCDistribution
sequence<2, 2>,
sequence<0, 2>>;
template <bool post_nop_ = false>
// c_vec += a_vec * b_vec
CK_TILE_DEVICE void
operator()(CVecType& c_vec, const AVecType& a_vec, const BVecType& b_vec) const
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
bool_constant<post_nop_> = {}) const
{
using buf_a = thread_buffer<typename Impl::AVecType, kKIter>;
using buf_b = thread_buffer<typename Impl::BVecType, kKIter>;
......@@ -328,10 +381,34 @@ struct WarpGemmAtrributeMfmaIterateKAndTransposedCDistribution
reinterpret_cast<const buf_b&>(b_vec)
.template get_as<typename Impl::BVecType>()[iKIter],
reinterpret_cast<const buf_a&>(a_vec)
.template get_as<typename Impl::AVecType>()[iKIter]);
.template get_as<typename Impl::AVecType>()[iKIter],
bool_constant<post_nop_>{});
});
}
template <index_t iKIter, bool post_nop_ = false>
// c_vec += a_vec * b_vec
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
number<iKIter>,
bool_constant<post_nop_> = {}) const
{
using buf_a = thread_buffer<typename Impl::AVecType, kKIter>;
using buf_b = thread_buffer<typename Impl::BVecType, kKIter>;
static_assert(iKIter < kKIter);
// swap A and B, value and type
// static_for<0, kKIter, 1>{}([&](auto iKIter) {
Impl{}(c_vec,
reinterpret_cast<const buf_b&>(b_vec)
.template get_as<typename Impl::BVecType>()[iKIter],
reinterpret_cast<const buf_a&>(a_vec)
.template get_as<typename Impl::AVecType>()[iKIter],
bool_constant<post_nop_>{});
//});
}
// c_vec = a_vec * b_vec
CK_TILE_DEVICE CVecType operator()(const AVecType& a_vec, const BVecType& b_vec) const
{
......@@ -375,8 +452,11 @@ struct WarpGemmAtrributeMfmaIterateKAndTransposedCDistribution_SwizzleB
static constexpr index_t kM = Impl::kN;
static constexpr index_t kN = Impl::kM;
static constexpr index_t kK = Impl::kK * kKIter;
static constexpr index_t kKPerThread = Impl::kABKPerLane * kKIter;
static constexpr index_t SFactor = SFactor_; // group how many CM1 together
CK_TILE_HOST_DEVICE static constexpr auto get_num_of_access() { return kKIter; }
using AWarpDstrEncoding = tile_distribution_encoding<
sequence<>,
tuple<sequence<Impl::kBNLane>, sequence<Impl::kABKLane, Impl::kABKPerLane * kKIter>>,
......@@ -429,8 +509,11 @@ struct WarpGemmAtrributeMfmaIterateKAndTransposedCDistribution_SwizzleB
sequence<0, 2>>;
#endif
// c_vec += a_vec * b_vec
CK_TILE_DEVICE void
operator()(CVecType& c_vec, const AVecType& a_vec, const BVecType& b_vec) const
template <bool post_nop_ = false>
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
bool_constant<post_nop_> = {}) const
{
using buf_a = thread_buffer<typename Impl::AVecType, kKIter>;
using buf_b = thread_buffer<typename Impl::BVecType, kKIter>;
......@@ -440,10 +523,33 @@ struct WarpGemmAtrributeMfmaIterateKAndTransposedCDistribution_SwizzleB
reinterpret_cast<const buf_b&>(b_vec)
.template get_as<typename Impl::BVecType>()[iKIter],
reinterpret_cast<const buf_a&>(a_vec)
.template get_as<typename Impl::AVecType>()[iKIter]);
.template get_as<typename Impl::AVecType>()[iKIter],
bool_constant<post_nop_>{});
});
}
template <index_t iKIter, bool post_nop_ = false>
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
number<iKIter>,
bool_constant<post_nop_> = {}) const
{
using buf_a = thread_buffer<typename Impl::AVecType, kKIter>;
using buf_b = thread_buffer<typename Impl::BVecType, kKIter>;
static_assert(iKIter < kKIter);
// swap A and B, value and type
// static_for<0, kKIter, 1>{}([&](auto iKIter) {
Impl{}(c_vec,
reinterpret_cast<const buf_b&>(b_vec)
.template get_as<typename Impl::BVecType>()[iKIter],
reinterpret_cast<const buf_a&>(a_vec)
.template get_as<typename Impl::AVecType>()[iKIter],
bool_constant<post_nop_>{});
//});
}
// c_vec = a_vec * b_vec
CK_TILE_DEVICE CVecType operator()(const AVecType& a_vec, const BVecType& b_vec) const
{
......@@ -486,8 +592,11 @@ struct WarpGemmAtrributeMfmaIterateK_SwizzleA
static constexpr index_t kM = Impl::kM;
static constexpr index_t kN = Impl::kN;
static constexpr index_t kK = Impl::kK * kKIter;
static constexpr index_t kKPerThread = Impl::kABKPerLane * kKIter;
static constexpr index_t SFactor = SFactor_; // group how many CM1 together
CK_TILE_HOST_DEVICE static constexpr auto get_num_of_access() { return kKIter; }
using AWarpDstrEncoding = tile_distribution_encoding<
sequence<>,
tuple<sequence<Impl::kAMLane / (Impl::kCMLane * SFactor * Impl::kCM1PerLane),
......@@ -518,8 +627,11 @@ struct WarpGemmAtrributeMfmaIterateK_SwizzleA
sequence<0, 2>>;
// c_vec += a_vec * b_vec
CK_TILE_DEVICE void
operator()(CVecType& c_vec, const AVecType& a_vec, const BVecType& b_vec) const
template <bool post_nop_ = false>
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
bool_constant<post_nop_> = {}) const
{
using buf_a = thread_buffer<typename Impl::AVecType, kKIter>;
using buf_b = thread_buffer<typename Impl::BVecType, kKIter>;
......@@ -529,10 +641,33 @@ struct WarpGemmAtrributeMfmaIterateK_SwizzleA
reinterpret_cast<const buf_a&>(a_vec)
.template get_as<typename Impl::AVecType>()[iKIter],
reinterpret_cast<const buf_b&>(b_vec)
.template get_as<typename Impl::BVecType>()[iKIter]);
.template get_as<typename Impl::BVecType>()[iKIter],
bool_constant<post_nop_>{});
});
}
template <index_t iKIter, bool post_nop_ = false>
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
number<iKIter>,
bool_constant<post_nop_> = {}) const
{
using buf_a = thread_buffer<typename Impl::AVecType, kKIter>;
using buf_b = thread_buffer<typename Impl::BVecType, kKIter>;
static_assert(iKIter < kKIter);
// static_for<0, kKIter, 1>{}([&](auto iKIter) {
Impl{}(c_vec,
reinterpret_cast<const buf_a&>(a_vec)
.template get_as<typename Impl::AVecType>()[iKIter],
reinterpret_cast<const buf_b&>(b_vec)
.template get_as<typename Impl::BVecType>()[iKIter],
bool_constant<post_nop_>{});
//});
}
// c_vec = a_vec * b_vec
CK_TILE_DEVICE CVecType operator()(const AVecType& a_vec, const BVecType& b_vec) const
{
......
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -7,9 +7,65 @@
namespace ck_tile {
// TODO: refactor warp-gemm
// currently there is a discrepency for vav/vva if we need transpose C/D
// e.g. if we want A:agpr, B:vgpr, we have to use vva in WGAttrEnum
// because we swap the A/B pointer in _impl code (but not known this info here)
enum class WGAttrCtlEnum
{
Default_ = 0,
Raw_vvv = 1, // c-vgpr, a-vgpr, b-vgpr
Raw_vaa = 2, // c-vgpr, a-agpr, b-agpr
Raw_vav = 3, // c-vgpr, a-agpr, b-vgpr
Raw_vva = 4, // c-vgpr, a-vgpr, b-agpr
Raw_avv = 5, // c-agpr, a-vgpr, b-vgpr
// raw_a_a_a = 3, // c-agpr, a-agpr, b-agpr
};
#define DISPATCH_MFMA_(mfma_, dmod_, amod_, bmod_, cmod_) \
if constexpr(post_nop_) \
{ \
asm volatile(mfma_ " %0, %1, %2, %3 ; yyy\n" \
"s_nop 3" \
: dmod_(c_vec) \
: amod_(a_vec), bmod_(b_vec), cmod_(c_vec) \
:); \
} \
else \
{ \
asm volatile(mfma_ " %0, %1, %2, %3\n" \
: dmod_(c_vec) \
: amod_(a_vec), bmod_(b_vec), cmod_(c_vec) \
:); \
}
#define DISPATCH_MFMA_CTRL_(mfma_, ctrl_) \
if constexpr(ctrl_ == WGAttrCtlEnum::Raw_vvv) \
{ \
DISPATCH_MFMA_(mfma_, "+v", "v", "v", "v") \
} \
else if constexpr(ctrl_ == WGAttrCtlEnum::Raw_vaa) \
{ \
DISPATCH_MFMA_(mfma_, "+v", "a", "a", "v") \
} \
else if constexpr(ctrl_ == WGAttrCtlEnum::Raw_vav) \
{ \
DISPATCH_MFMA_(mfma_, "+v", "a", "v", "v") \
} \
else if constexpr(ctrl_ == WGAttrCtlEnum::Raw_vva) \
{ \
DISPATCH_MFMA_(mfma_, "+v", "v", "a", "v") \
} \
else if constexpr(ctrl_ == WGAttrCtlEnum::Raw_avv) \
{ \
DISPATCH_MFMA_(mfma_, "+a", "v", "v", "a") \
}
// FP16
template <WGAttrCtlEnum Ctrl_ = WGAttrCtlEnum::Default_>
struct WarpGemmAttributeMfmaImplF16F16F32M32N32K8
{
static constexpr WGAttrCtlEnum Ctrl = Ctrl_;
using ADataType = fp16_t;
using BDataType = fp16_t;
using CDataType = float;
......@@ -33,17 +89,24 @@ struct WarpGemmAttributeMfmaImplF16F16F32M32N32K8
static constexpr index_t kCM1PerLane = 4;
// c_vec += a_vec * b_vec
CK_TILE_DEVICE void
operator()(CVecType& c_vec, const AVecType& a_vec, const BVecType& b_vec) const
template <bool post_nop_ = false>
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
bool_constant<post_nop_> = {}) const
{
DISPATCH_MFMA_CTRL_("v_mfma_f32_32x32x8f16", Ctrl)
else
{
#if defined(__gfx9__)
c_vec = __builtin_amdgcn_mfma_f32_32x32x8f16(a_vec, b_vec, c_vec, 0, 0, 0);
#else
ignore = c_vec;
ignore = a_vec;
ignore = b_vec;
ck_tile::ignore = c_vec;
ck_tile::ignore = a_vec;
ck_tile::ignore = b_vec;
#endif
}
}
// c_vec = a_vec * b_vec
CK_TILE_DEVICE CVecType operator()(const AVecType& a_vec, const BVecType& b_vec) const
......@@ -52,15 +115,17 @@ struct WarpGemmAttributeMfmaImplF16F16F32M32N32K8
return bit_cast<CVecType>(
__builtin_amdgcn_mfma_f32_32x32x8f16(a_vec, b_vec, fp32x16_t{0.f}, 0, 0, 0));
#else
ignore = a_vec;
ignore = b_vec;
ck_tile::ignore = a_vec;
ck_tile::ignore = b_vec;
return CVecType{0.f};
#endif
}
};
template <WGAttrCtlEnum Ctrl_ = WGAttrCtlEnum::Default_>
struct WarpGemmAttributeMfmaImplF16F16F32M16N16K16
{
static constexpr WGAttrCtlEnum Ctrl = Ctrl_;
using ADataType = fp16_t;
using BDataType = fp16_t;
using CDataType = float;
......@@ -84,17 +149,24 @@ struct WarpGemmAttributeMfmaImplF16F16F32M16N16K16
static constexpr index_t kCM1PerLane = 4;
// c_vec += a_vec * b_vec
CK_TILE_DEVICE void
operator()(CVecType& c_vec, const AVecType& a_vec, const BVecType& b_vec) const
template <bool post_nop_ = false>
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
bool_constant<post_nop_> = {}) const
{
DISPATCH_MFMA_CTRL_("v_mfma_f32_16x16x16f16", Ctrl)
else
{
#if defined(__gfx9__)
c_vec = __builtin_amdgcn_mfma_f32_16x16x16f16(a_vec, b_vec, c_vec, 0, 0, 0);
#else
ignore = c_vec;
ignore = a_vec;
ignore = b_vec;
ck_tile::ignore = c_vec;
ck_tile::ignore = a_vec;
ck_tile::ignore = b_vec;
#endif
}
}
// c_vec = a_vec * b_vec
CK_TILE_DEVICE CVecType operator()(const AVecType& a_vec, const BVecType& b_vec) const
......@@ -103,16 +175,18 @@ struct WarpGemmAttributeMfmaImplF16F16F32M16N16K16
return bit_cast<CVecType>(
__builtin_amdgcn_mfma_f32_16x16x16f16(a_vec, b_vec, fp32x4_t{0.f}, 0, 0, 0));
#else
ignore = a_vec;
ignore = b_vec;
ck_tile::ignore = a_vec;
ck_tile::ignore = b_vec;
return CVecType{0.f};
#endif
}
};
// Bf16
template <WGAttrCtlEnum Ctrl_ = WGAttrCtlEnum::Default_>
struct WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8
{
static constexpr WGAttrCtlEnum Ctrl = Ctrl_;
using ADataType = bf16_t;
using BDataType = bf16_t;
using CDataType = float;
......@@ -136,8 +210,14 @@ struct WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8
static constexpr index_t kCM1PerLane = 4;
// c_vec += a_vec * b_vec
CK_TILE_DEVICE void
operator()(CVecType& c_vec, const AVecType& a_vec, const BVecType& b_vec) const
template <bool post_nop_ = false>
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
bool_constant<post_nop_> = {}) const
{
DISPATCH_MFMA_CTRL_("v_mfma_f32_32x32x8bf16_1k", Ctrl)
else
{
#if defined(__gfx90a__) || defined(__gfx94__)
c_vec = __builtin_amdgcn_mfma_f32_32x32x8bf16_1k(a_vec, b_vec, c_vec, 0, 0, 0);
......@@ -154,11 +234,12 @@ struct WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8
0);
});
#else
ignore = c_vec;
ignore = a_vec;
ignore = b_vec;
ck_tile::ignore = c_vec;
ck_tile::ignore = a_vec;
ck_tile::ignore = b_vec;
#endif
}
}
// c_vec = a_vec * b_vec
CK_TILE_DEVICE CVecType operator()(const AVecType& a_vec, const BVecType& b_vec) const
......@@ -181,15 +262,17 @@ struct WarpGemmAttributeMfmaImplBf16Bf16F32M32N32K8
});
return c_vec;
#else
ignore = a_vec;
ignore = b_vec;
ck_tile::ignore = a_vec;
ck_tile::ignore = b_vec;
return CVecType{0.f};
#endif
}
};
template <WGAttrCtlEnum Ctrl_ = WGAttrCtlEnum::Default_>
struct WarpGemmAttributeMfmaImplBf16Bf16F32M16N16K16
{
static constexpr WGAttrCtlEnum Ctrl = Ctrl_;
using ADataType = bf16_t;
using BDataType = bf16_t;
using CDataType = float;
......@@ -213,8 +296,13 @@ struct WarpGemmAttributeMfmaImplBf16Bf16F32M16N16K16
static constexpr index_t kCM1PerLane = 4;
// c_vec += a_vec * b_vec
CK_TILE_DEVICE void
operator()(CVecType& c_vec, const AVecType& a_vec, const BVecType& b_vec) const
template <bool post_nop_ = false>
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
bool_constant<post_nop_> = {}) const
{
DISPATCH_MFMA_CTRL_("v_mfma_f32_16x16x16bf16_1k", Ctrl)
{
#if defined(__gfx90a__) || defined(__gfx94__)
c_vec = __builtin_amdgcn_mfma_f32_16x16x16bf16_1k(a_vec, b_vec, c_vec, 0, 0, 0);
......@@ -231,11 +319,12 @@ struct WarpGemmAttributeMfmaImplBf16Bf16F32M16N16K16
0);
});
#else
ignore = c_vec;
ignore = a_vec;
ignore = b_vec;
ck_tile::ignore = c_vec;
ck_tile::ignore = a_vec;
ck_tile::ignore = b_vec;
#endif
}
}
// c_vec = a_vec * b_vec
CK_TILE_DEVICE CVecType operator()(const AVecType& a_vec, const BVecType& b_vec) const
......@@ -258,17 +347,18 @@ struct WarpGemmAttributeMfmaImplBf16Bf16F32M16N16K16
});
return c_vec;
#else
ignore = a_vec;
ignore = b_vec;
ck_tile::ignore = a_vec;
ck_tile::ignore = b_vec;
return CVecType{0.f};
#endif
}
};
// FP8
template <typename AType_, typename BType_>
template <typename AType_, typename BType_, WGAttrCtlEnum Ctrl_ = WGAttrCtlEnum::Default_>
struct WarpGemmAttributeMfmaImpl_f32_32x32x16_f8_base
{
static constexpr WGAttrCtlEnum Ctrl = Ctrl_;
using ADataType = AType_;
using BDataType = BType_;
using CDataType = float;
......@@ -292,8 +382,89 @@ struct WarpGemmAttributeMfmaImpl_f32_32x32x16_f8_base
static constexpr index_t kCM1PerLane = 4;
// c_vec += a_vec * b_vec
CK_TILE_DEVICE void
operator()(CVecType& c_vec, const AVecType& a_vec, const BVecType& b_vec) const
template <bool post_nop_ = false>
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
bool_constant<post_nop_> = {}) const
{
if constexpr(Ctrl == WGAttrCtlEnum::Raw_vvv)
{
if constexpr(std::is_same_v<ADataType, fp8_t> && std::is_same_v<BDataType, fp8_t>)
{
DISPATCH_MFMA_("mfma_f32_32x32x16_fp8_fp8", "+v", "v", "v", "v")
}
else if constexpr(std::is_same_v<ADataType, fp8_t> && std::is_same_v<BDataType, bf8_t>)
{
DISPATCH_MFMA_("mfma_f32_32x32x16_fp8_bf8", "+v", "v", "v", "v")
}
else if constexpr(std::is_same_v<ADataType, bf8_t> && std::is_same_v<BDataType, fp8_t>)
{
DISPATCH_MFMA_("mfma_f32_32x32x16_bf8_fp8", "+v", "v", "v", "v")
}
else if constexpr(std::is_same_v<ADataType, bf8_t> && std::is_same_v<BDataType, bf8_t>)
{
DISPATCH_MFMA_("mfma_f32_32x32x16_bf8_bf8", "+v", "v", "v", "v")
}
}
else if constexpr(Ctrl == WGAttrCtlEnum::Raw_vaa)
{
if constexpr(std::is_same_v<ADataType, fp8_t> && std::is_same_v<BDataType, fp8_t>)
{
DISPATCH_MFMA_("mfma_f32_32x32x16_fp8_fp8", "+v", "a", "a", "v")
}
else if constexpr(std::is_same_v<ADataType, fp8_t> && std::is_same_v<BDataType, bf8_t>)
{
DISPATCH_MFMA_("mfma_f32_32x32x16_fp8_bf8", "+v", "a", "a", "v")
}
else if constexpr(std::is_same_v<ADataType, bf8_t> && std::is_same_v<BDataType, fp8_t>)
{
DISPATCH_MFMA_("mfma_f32_32x32x16_bf8_fp8", "+v", "a", "a", "v")
}
else if constexpr(std::is_same_v<ADataType, bf8_t> && std::is_same_v<BDataType, bf8_t>)
{
DISPATCH_MFMA_("mfma_f32_32x32x16_bf8_bf8", "+v", "a", "a", "v")
}
}
else if constexpr(Ctrl == WGAttrCtlEnum::Raw_vav)
{
if constexpr(std::is_same_v<ADataType, fp8_t> && std::is_same_v<BDataType, fp8_t>)
{
DISPATCH_MFMA_("mfma_f32_32x32x16_fp8_fp8", "+v", "a", "v", "v")
}
else if constexpr(std::is_same_v<ADataType, fp8_t> && std::is_same_v<BDataType, bf8_t>)
{
DISPATCH_MFMA_("mfma_f32_32x32x16_fp8_bf8", "+v", "a", "v", "v")
}
else if constexpr(std::is_same_v<ADataType, bf8_t> && std::is_same_v<BDataType, fp8_t>)
{
DISPATCH_MFMA_("mfma_f32_32x32x16_bf8_fp8", "+v", "a", "v", "v")
}
else if constexpr(std::is_same_v<ADataType, bf8_t> && std::is_same_v<BDataType, bf8_t>)
{
DISPATCH_MFMA_("mfma_f32_32x32x16_bf8_bf8", "+v", "a", "v", "v")
}
}
else if constexpr(Ctrl == WGAttrCtlEnum::Raw_vva)
{
if constexpr(std::is_same_v<ADataType, fp8_t> && std::is_same_v<BDataType, fp8_t>)
{
DISPATCH_MFMA_("mfma_f32_32x32x16_fp8_fp8", "+v", "v", "a", "v")
}
else if constexpr(std::is_same_v<ADataType, fp8_t> && std::is_same_v<BDataType, bf8_t>)
{
DISPATCH_MFMA_("mfma_f32_32x32x16_fp8_bf8", "+v", "v", "a", "v")
}
else if constexpr(std::is_same_v<ADataType, bf8_t> && std::is_same_v<BDataType, fp8_t>)
{
DISPATCH_MFMA_("mfma_f32_32x32x16_bf8_fp8", "+v", "v", "a", "v")
}
else if constexpr(std::is_same_v<ADataType, bf8_t> && std::is_same_v<BDataType, bf8_t>)
{
DISPATCH_MFMA_("mfma_f32_32x32x16_bf8_bf8", "+v", "v", "a", "v")
}
}
else
{
#if defined(__gfx94__)
if constexpr(std::is_same_v<ADataType, fp8_t> && std::is_same_v<BDataType, fp8_t>)
......@@ -320,11 +491,12 @@ struct WarpGemmAttributeMfmaImpl_f32_32x32x16_f8_base
c_vec = __builtin_amdgcn_mfma_f32_32x32x2f32(a_f32, b_f32, c_vec, 0, 0, 0);
});
#else
ignore = c_vec;
ignore = a_vec;
ignore = b_vec;
ck_tile::ignore = c_vec;
ck_tile::ignore = a_vec;
ck_tile::ignore = b_vec;
#endif
}
}
// c_vec = a_vec * b_vec
CK_TILE_DEVICE CVecType operator()(const AVecType& a_vec, const BVecType& b_vec) const
......@@ -356,20 +528,97 @@ struct WarpGemmAttributeMfmaImpl_f32_32x32x16_f8_base
});
return c_vec;
#else
ignore = a_vec;
ignore = b_vec;
ck_tile::ignore = a_vec;
ck_tile::ignore = b_vec;
return CVecType{0.f};
#endif
}
};
template <WGAttrCtlEnum Ctrl_ = WGAttrCtlEnum::Default_>
using WarpGemmAttributeMfmaImpl_f32_32x32x16_fp8_fp8 =
WarpGemmAttributeMfmaImpl_f32_32x32x16_f8_base<fp8_t, fp8_t>;
WarpGemmAttributeMfmaImpl_f32_32x32x16_f8_base<fp8_t, fp8_t, Ctrl_>;
template <WGAttrCtlEnum Ctrl_ = WGAttrCtlEnum::Default_>
using WarpGemmAttributeMfmaImpl_f32_32x32x16_fp8_bf8 =
WarpGemmAttributeMfmaImpl_f32_32x32x16_f8_base<fp8_t, bf8_t>;
WarpGemmAttributeMfmaImpl_f32_32x32x16_f8_base<fp8_t, bf8_t, Ctrl_>;
template <WGAttrCtlEnum Ctrl_ = WGAttrCtlEnum::Default_>
using WarpGemmAttributeMfmaImpl_f32_32x32x16_bf8_fp8 =
WarpGemmAttributeMfmaImpl_f32_32x32x16_f8_base<bf8_t, fp8_t>;
WarpGemmAttributeMfmaImpl_f32_32x32x16_f8_base<bf8_t, fp8_t, Ctrl_>;
template <WGAttrCtlEnum Ctrl_ = WGAttrCtlEnum::Default_>
using WarpGemmAttributeMfmaImpl_f32_32x32x16_bf8_bf8 =
WarpGemmAttributeMfmaImpl_f32_32x32x16_f8_base<bf8_t, bf8_t>;
WarpGemmAttributeMfmaImpl_f32_32x32x16_f8_base<bf8_t, bf8_t, Ctrl_>;
// int8
template <WGAttrCtlEnum Ctrl_ = WGAttrCtlEnum::Default_>
struct WarpGemmAttributeMfmaImpl_i32_32x32x16_i8
{
static constexpr WGAttrCtlEnum Ctrl = Ctrl_;
using ADataType = int8_t;
using BDataType = int8_t;
using CDataType = int32_t;
using AVecType = ext_vector_t<ADataType, 8>;
using BVecType = ext_vector_t<BDataType, 8>;
using CVecType = ext_vector_t<CDataType, 16>;
static constexpr index_t kM = 32;
static constexpr index_t kN = 32;
static constexpr index_t kK = 16;
static constexpr index_t kAMLane = 32;
static constexpr index_t kBNLane = 32;
static constexpr index_t kABKLane = 2;
static constexpr index_t kABKPerLane = 8;
static constexpr index_t kCMLane = 2;
static constexpr index_t kCNLane = 32;
static constexpr index_t kCM0PerLane = 4;
static constexpr index_t kCM1PerLane = 4;
// c_vec += a_vec * b_vec
template <bool post_nop_ = false>
CK_TILE_DEVICE void operator()(CVecType& c_vec,
const AVecType& a_vec,
const BVecType& b_vec,
bool_constant<post_nop_> = {}) const
{
DISPATCH_MFMA_CTRL_("v_mfma_i32_32x32x16_i8", Ctrl)
else
{
#if defined(__gfx94__)
c_vec = __builtin_amdgcn_mfma_i32_32x32x8i8(
bit_cast<long>(a_vec), bit_cast<long>(b_vec), c_vec, 0, 0, 0);
#elif defined(__gfx908__) || defined(__gfx90a__)
static_for<0, 8, 1>{}([&](auto k) {
float a_f32 =
type_convert<float>(reinterpret_cast<const thread_buffer<ADataType, 8>&>(a_vec)
.template get_as<ADataType>()[number<k>{}]);
float b_f32 =
type_convert<float>(reinterpret_cast<const thread_buffer<BDataType, 8>&>(b_vec)
.template get_as<BDataType>()[number<k>{}]);
c_vec = __builtin_amdgcn_mfma_f32_32x32x2f32(a_f32, b_f32, c_vec, 0, 0, 0);
});
#else
ck_tile::ignore = c_vec;
ck_tile::ignore = a_vec;
ck_tile::ignore = b_vec;
#endif
}
}
// c_vec = a_vec * b_vec
CK_TILE_DEVICE CVecType operator()(const AVecType& a_vec, const BVecType& b_vec) const
{
CVecType c_vec{0};
operator()(c_vec, a_vec, b_vec);
return c_vec;
}
};
#undef DISPATCH_MFMA_
} // namespace ck_tile
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -21,40 +21,40 @@ struct WarpGemmMfmaDispatcher;
// clang-format off
// fp16
template<> struct WarpGemmMfmaDispatcher<half_t, half_t, float, 32, 32, 8, false> { using Type = WarpGemmMfmaF16F16F32M32N32K8; };
template<> struct WarpGemmMfmaDispatcher<half_t, half_t, float, 32, 32, 8, true> { using Type = WarpGemmMfmaF16F16F32M32N32K8TransposedCDistribution; };
template<> struct WarpGemmMfmaDispatcher<half_t, half_t, float, 32, 32, 16, false> { using Type = WarpGemmMfmaF16F16F32M32N32K16; };
template<> struct WarpGemmMfmaDispatcher<half_t, half_t, float, 32, 32, 16, true> { using Type = WarpGemmMfmaF16F16F32M32N32K16TransposedCDistribution; };
template<> struct WarpGemmMfmaDispatcher<half_t, half_t, float, 16, 16, 16, false> { using Type = WarpGemmMfmaF16F16F32M16N16K16; };
template<> struct WarpGemmMfmaDispatcher<half_t, half_t, float, 16, 16, 16, true> { using Type = WarpGemmMfmaF16F16F32M16N16K16TransposedCDistribution; };
template<> struct WarpGemmMfmaDispatcher<half_t, half_t, float, 16, 16, 32, false> { using Type = WarpGemmMfmaF16F16F32M16N16K32; };
template<> struct WarpGemmMfmaDispatcher<half_t, half_t, float, 16, 16, 32, true> { using Type = WarpGemmMfmaF16F16F32M16N16K32TransposedCDistribution; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::half_t, ck_tile::half_t, float, 32, 32, 8, false> { using Type = WarpGemmMfmaF16F16F32M32N32K8; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::half_t, ck_tile::half_t, float, 32, 32, 8, true> { using Type = WarpGemmMfmaF16F16F32M32N32K8TransposedCDistribution; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::half_t, ck_tile::half_t, float, 32, 32, 16, false> { using Type = WarpGemmMfmaF16F16F32M32N32K16; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::half_t, ck_tile::half_t, float, 32, 32, 16, true> { using Type = WarpGemmMfmaF16F16F32M32N32K16TransposedCDistribution; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::half_t, ck_tile::half_t, float, 16, 16, 16, false> { using Type = WarpGemmMfmaF16F16F32M16N16K16; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::half_t, ck_tile::half_t, float, 16, 16, 16, true> { using Type = WarpGemmMfmaF16F16F32M16N16K16TransposedCDistribution; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::half_t, ck_tile::half_t, float, 16, 16, 32, false> { using Type = WarpGemmMfmaF16F16F32M16N16K32; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::half_t, ck_tile::half_t, float, 16, 16, 32, true> { using Type = WarpGemmMfmaF16F16F32M16N16K32TransposedCDistribution; };
template<> struct WarpGemmMfmaDispatcher<half_t, half_t, float, 32, 32, 8, false, true> { using Type = WarpGemmMfmaF16F16F32M32N32K8SwizzleA; };
template<> struct WarpGemmMfmaDispatcher<half_t, half_t, float, 32, 32, 16, false, true> { using Type = WarpGemmMfmaF16F16F32M32N32K16SwizzleA; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::half_t, ck_tile::half_t, float, 32, 32, 8, false, true> { using Type = WarpGemmMfmaF16F16F32M32N32K8SwizzleA; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::half_t, ck_tile::half_t, float, 32, 32, 16, false, true> { using Type = WarpGemmMfmaF16F16F32M32N32K16SwizzleA; };
// bf16
template<> struct WarpGemmMfmaDispatcher<bf16_t, bf16_t, float, 32, 32, 8, false> { using Type = WarpGemmMfmaBf16Bf16F32M32N32K8; };
template<> struct WarpGemmMfmaDispatcher<bf16_t, bf16_t, float, 32, 32, 8, true> { using Type = WarpGemmMfmaBf16Bf16F32M32N32K8TransposedCDistribution; };
template<> struct WarpGemmMfmaDispatcher<bf16_t, bf16_t, float, 32, 32, 16, false> { using Type = WarpGemmMfmaBf16Bf16F32M32N32K16; };
template<> struct WarpGemmMfmaDispatcher<bf16_t, bf16_t, float, 32, 32, 16, true> { using Type = WarpGemmMfmaBf16Bf16F32M32N32K16TransposedCDistribution; };
template<> struct WarpGemmMfmaDispatcher<bf16_t, bf16_t, float, 16, 16, 16, false> { using Type = WarpGemmMfmaBf16Bf16F32M16N16K16; };
template<> struct WarpGemmMfmaDispatcher<bf16_t, bf16_t, float, 16, 16, 16, true> { using Type = WarpGemmMfmaBf16Bf16F32M16N16K16TransposedCDistribution; };
template<> struct WarpGemmMfmaDispatcher<bf16_t, bf16_t, float, 16, 16, 32, false> { using Type = WarpGemmMfmaBf16Bf16F32M16N16K32; };
template<> struct WarpGemmMfmaDispatcher<bf16_t, bf16_t, float, 16, 16, 32, true> { using Type = WarpGemmMfmaBf16Bf16F32M16N16K32TransposedCDistribution; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::bf16_t, ck_tile::bf16_t, float, 32, 32, 8, false> { using Type = WarpGemmMfmaBf16Bf16F32M32N32K8; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::bf16_t, ck_tile::bf16_t, float, 32, 32, 8, true> { using Type = WarpGemmMfmaBf16Bf16F32M32N32K8TransposedCDistribution; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::bf16_t, ck_tile::bf16_t, float, 32, 32, 16, false> { using Type = WarpGemmMfmaBf16Bf16F32M32N32K16; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::bf16_t, ck_tile::bf16_t, float, 32, 32, 16, true> { using Type = WarpGemmMfmaBf16Bf16F32M32N32K16TransposedCDistribution; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::bf16_t, ck_tile::bf16_t, float, 16, 16, 16, false> { using Type = WarpGemmMfmaBf16Bf16F32M16N16K16; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::bf16_t, ck_tile::bf16_t, float, 16, 16, 16, true> { using Type = WarpGemmMfmaBf16Bf16F32M16N16K16TransposedCDistribution; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::bf16_t, ck_tile::bf16_t, float, 16, 16, 32, false> { using Type = WarpGemmMfmaBf16Bf16F32M16N16K32; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::bf16_t, ck_tile::bf16_t, float, 16, 16, 32, true> { using Type = WarpGemmMfmaBf16Bf16F32M16N16K32TransposedCDistribution; };
template<> struct WarpGemmMfmaDispatcher<bf16_t, bf16_t, float, 32, 32, 8, false, true> { using Type = WarpGemmMfmaBf16Bf16F32M32N32K8SwizzleA; };
template<> struct WarpGemmMfmaDispatcher<bf16_t, bf16_t, float, 32, 32, 16, false, true> { using Type = WarpGemmMfmaBf16Bf16F32M32N32K16SwizzleA; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::bf16_t, ck_tile::bf16_t, float, 32, 32, 8, false, true> { using Type = WarpGemmMfmaBf16Bf16F32M32N32K8SwizzleA; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::bf16_t, ck_tile::bf16_t, float, 32, 32, 16, false, true> { using Type = WarpGemmMfmaBf16Bf16F32M32N32K16SwizzleA; };
// fp8
template<> struct WarpGemmMfmaDispatcher<fp8_t, fp8_t, float, 32, 32, 16, false> { using Type = WarpGemmMfma_f32_32x32x16_fp8_fp8; };
template<> struct WarpGemmMfmaDispatcher<fp8_t, fp8_t, float, 32, 32, 16, true> { using Type = WarpGemmMfma_f32_32x32x16_fp8_fp8_CTransposed; };
template<> struct WarpGemmMfmaDispatcher<fp8_t, bf8_t, float, 32, 32, 16, false> { using Type = WarpGemmMfma_f32_32x32x16_fp8_bf8; };
template<> struct WarpGemmMfmaDispatcher<fp8_t, bf8_t, float, 32, 32, 16, true> { using Type = WarpGemmMfma_f32_32x32x16_fp8_bf8_CTransposed; };
template<> struct WarpGemmMfmaDispatcher<bf8_t, fp8_t, float, 32, 32, 16, false> { using Type = WarpGemmMfma_f32_32x32x16_bf8_fp8; };
template<> struct WarpGemmMfmaDispatcher<bf8_t, fp8_t, float, 32, 32, 16, true> { using Type = WarpGemmMfma_f32_32x32x16_bf8_fp8_CTransposed; };
template<> struct WarpGemmMfmaDispatcher<bf8_t, bf8_t, float, 32, 32, 16, false> { using Type = WarpGemmMfma_f32_32x32x16_bf8_bf8; };
template<> struct WarpGemmMfmaDispatcher<bf8_t, bf8_t, float, 32, 32, 16, true> { using Type = WarpGemmMfma_f32_32x32x16_bf8_bf8_CTransposed; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::fp8_t, ck_tile::fp8_t, float, 32, 32, 16, false> { using Type = WarpGemmMfma_f32_32x32x16_fp8_fp8; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::fp8_t, ck_tile::fp8_t, float, 32, 32, 16, true> { using Type = WarpGemmMfma_f32_32x32x16_fp8_fp8_CTransposed; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::fp8_t, ck_tile::bf8_t, float, 32, 32, 16, false> { using Type = WarpGemmMfma_f32_32x32x16_fp8_bf8; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::fp8_t, ck_tile::bf8_t, float, 32, 32, 16, true> { using Type = WarpGemmMfma_f32_32x32x16_fp8_bf8_CTransposed; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::bf8_t, ck_tile::fp8_t, float, 32, 32, 16, false> { using Type = WarpGemmMfma_f32_32x32x16_bf8_fp8; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::bf8_t, ck_tile::fp8_t, float, 32, 32, 16, true> { using Type = WarpGemmMfma_f32_32x32x16_bf8_fp8_CTransposed; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::bf8_t, ck_tile::bf8_t, float, 32, 32, 16, false> { using Type = WarpGemmMfma_f32_32x32x16_bf8_bf8; };
template<> struct WarpGemmMfmaDispatcher<ck_tile::bf8_t, ck_tile::bf8_t, float, 32, 32, 16, true> { using Type = WarpGemmMfma_f32_32x32x16_bf8_bf8_CTransposed; };
// clang-format on
} // namespace impl
......
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