Introduce gemm_softmax_gemm to codegen.

This commit is contained in:
Mirza Halilcevic
2024-09-25 08:22:07 +00:00
parent 3528a523ff
commit d43cd4ad32
52 changed files with 2108 additions and 187 deletions

View File

@@ -3,8 +3,12 @@
#pragma once
#ifndef __HIPCC_RTC__
#include <iostream>
#include <sstream>
#include "ck/host_utility/device_prop.hpp"
#include "ck/host_utility/kernel_launch.hpp"
#endif
#include "ck/utility/common_header.hpp"
#include "ck/tensor_description/tensor_descriptor.hpp"
@@ -15,8 +19,6 @@
#include "ck/tensor_operation/gpu/device/masking_specialization.hpp"
#include "ck/tensor_operation/gpu/device/matrix_padder.hpp"
#include "ck/tensor_operation/gpu/grid/gridwise_batched_gemm_softmax_gemm_xdl_cshuffle_v1.hpp"
#include "ck/host_utility/device_prop.hpp"
#include "ck/host_utility/kernel_launch.hpp"
namespace ck {
namespace tensor_operation {
@@ -40,27 +42,27 @@ template <typename GridwiseGemm,
bool HasMainKBlockLoop>
__global__ void
#if CK_USE_LAUNCH_BOUNDS
__launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU)
__launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU)
#endif
kernel_batched_gemm_softmax_gemm_xdl_cshuffle_v1(
const FloatAB* __restrict__ p_a_grid,
const FloatAB* __restrict__ p_b_grid,
const FloatAB* __restrict__ p_b1_grid,
FloatC* __restrict__ p_c_grid,
const AElementwiseOperation a_element_op,
const BElementwiseOperation b_element_op,
const AccElementwiseOperation acc_element_op,
const B1ElementwiseOperation b1_element_op,
const CElementwiseOperation c_element_op,
const AGridDesc_AK0_M_AK1 a_grid_desc_ak0_m_ak1,
const BGridDesc_BK0_N_BK1 b_grid_desc_bk0_n_bk1,
const B1GridDesc_BK0_N_BK1 b1_grid_desc_bk0_n_bk1,
const CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
c_grid_desc_mblock_mperblock_nblock_nperblock,
const Block2CTileMap block_2_ctile_map,
const index_t batch_count,
const ComputeBasePtrOfStridedBatch compute_base_ptr_of_batch,
const C0MatrixMask c0_matrix_mask)
kernel_batched_gemm_softmax_gemm_xdl_cshuffle_v1(
const FloatAB* __restrict__ p_a_grid,
const FloatAB* __restrict__ p_b_grid,
const FloatAB* __restrict__ p_b1_grid,
FloatC* __restrict__ p_c_grid,
const AElementwiseOperation a_element_op,
const BElementwiseOperation b_element_op,
const AccElementwiseOperation acc_element_op,
const B1ElementwiseOperation b1_element_op,
const CElementwiseOperation c_element_op,
const AGridDesc_AK0_M_AK1 a_grid_desc_ak0_m_ak1,
const BGridDesc_BK0_N_BK1 b_grid_desc_bk0_n_bk1,
const B1GridDesc_BK0_N_BK1 b1_grid_desc_bk0_n_bk1,
const CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
c_grid_desc_mblock_mperblock_nblock_nperblock,
const Block2CTileMap block_2_ctile_map,
const index_t batch_count,
const ComputeBasePtrOfStridedBatch compute_base_ptr_of_batch,
const C0MatrixMask c0_matrix_mask)
{
#if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__) || \
defined(__gfx94__))
@@ -430,6 +432,7 @@ struct DeviceBatchedGemmSoftmaxGemm_Xdl_CShuffle
matrix_padder.PadN,
MaskOutUpperTriangle>;
#ifndef __HIPCC_RTC__
// Argument
struct Argument : public BaseArgument
{
@@ -604,6 +607,7 @@ struct DeviceBatchedGemmSoftmaxGemm_Xdl_CShuffle
return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
}
};
#endif
static constexpr bool IsValidCompilationParameter()
{
@@ -611,6 +615,97 @@ struct DeviceBatchedGemmSoftmaxGemm_Xdl_CShuffle
return true;
}
static constexpr bool
IsSupported(index_t MRaw_, index_t NRaw_, index_t KRaw_, index_t Gemm1NRaw_)
{
// check vector load/store
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
// check vector load of A
if constexpr(is_same_v<ALayout, Row>)
{
if(KRaw_ % ABlockTransferSrcScalarPerVector != 0)
{
return false;
}
}
else if constexpr(is_same_v<ALayout, Col>)
{
if(MRaw_ % ABlockTransferSrcScalarPerVector != 0)
{
return false;
}
}
else
{
return false;
}
// check vector load of B
if constexpr(is_same_v<BLayout, Row>)
{
if(NRaw_ % BBlockTransferSrcScalarPerVector != 0)
{
return false;
}
}
else if constexpr(is_same_v<BLayout, Col>)
{
if(KRaw_ % BBlockTransferSrcScalarPerVector != 0)
{
return false;
}
}
else
{
return false;
}
// check vector load of B1
if constexpr(is_same_v<B1Layout, Row>)
{
if(Gemm1NRaw_ % B1BlockTransferSrcScalarPerVector != 0)
{
return false;
}
}
else if constexpr(is_same_v<B1Layout, Col>)
{
if(NRaw_ % B1BlockTransferSrcScalarPerVector != 0)
{
return false;
}
}
else
{
return false;
}
// check vector load of C
if constexpr(is_same_v<CLayout, Row>)
{
if(Gemm1NRaw_ % CShuffleBlockTransferScalarPerVector_NPerBlock != 0)
{
return false;
}
}
else if constexpr(is_same_v<CLayout, Col>)
{
if(MRaw_ % CShuffleBlockTransferScalarPerVector_NPerBlock != 0)
{
return false;
}
}
else
{
return false;
}
return true;
}
#ifndef __HIPCC_RTC__
static bool IsSupportedArgument(const Argument& arg)
{
if(!ck::is_xdl_supported())
@@ -765,8 +860,271 @@ struct DeviceBatchedGemmSoftmaxGemm_Xdl_CShuffle
return str.str();
}
#endif
template <class ADesc, class BDesc, class B1Desc, class CDesc>
struct Descriptor
{
template <class AGridDescriptor>
static constexpr auto MakeAGridDescriptor_AK0_M_AK1(const AGridDescriptor& a_grid_desc)
{
const auto a_grid_desc_m_k = DeviceOp::matrix_padder.PadADescriptor_M_K(a_grid_desc);
const auto M = a_grid_desc_m_k.GetLength(I0);
const auto K = a_grid_desc_m_k.GetLength(I1);
const auto AK0 = K / AK1;
return transform_tensor_descriptor(
a_grid_desc_m_k,
make_tuple(make_unmerge_transform(make_tuple(AK0, AK1)),
make_pass_through_transform(M)),
make_tuple(Sequence<1>{}, Sequence<0>{}),
make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
}
template <class BGridDescriptor>
static constexpr auto MakeBGridDescriptor_BK0_N_BK1(const BGridDescriptor& b_grid_desc)
{
const auto b_grid_desc_n_k = DeviceOp::matrix_padder.PadBDescriptor_N_K(b_grid_desc);
const auto N = b_grid_desc_n_k.GetLength(I0);
const auto K = b_grid_desc_n_k.GetLength(I1);
const auto BK0 = K / BK1;
return transform_tensor_descriptor(
b_grid_desc_n_k,
make_tuple(make_unmerge_transform(make_tuple(BK0, BK1)),
make_pass_through_transform(N)),
make_tuple(Sequence<1>{}, Sequence<0>{}),
make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
}
template <class B1GridDescriptor>
static constexpr auto MakeB1GridDescriptor_BK0_N_BK1(const B1GridDescriptor& b1_grid_desc)
{
const auto b1_grid_desc_n_k = DeviceOp::matrix_padder.PadB1Descriptor_N_K(b1_grid_desc);
const auto N = b1_grid_desc_n_k.GetLength(I0);
const auto K = b1_grid_desc_n_k.GetLength(I1);
const auto B1K0 = K / B1K1;
return transform_tensor_descriptor(
b1_grid_desc_n_k,
make_tuple(make_unmerge_transform(make_tuple(B1K0, B1K1)),
make_pass_through_transform(N)),
make_tuple(Sequence<1>{}, Sequence<0>{}),
make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
}
template <class CGridDescriptor>
static constexpr auto MakeCGridDescriptor_M_N(const CGridDescriptor& c_grid_desc)
{
return DeviceOp::matrix_padder.PadCDescriptor_M_N(c_grid_desc);
}
using AGridDesc_AK0_M_AK1 =
remove_cvref_t<decltype(MakeAGridDescriptor_AK0_M_AK1(ADesc{}))>;
using BGridDesc_BK0_N_BK1 =
remove_cvref_t<decltype(MakeBGridDescriptor_BK0_N_BK1(BDesc{}))>;
using B1GridDesc_BK0_N_BK1 =
remove_cvref_t<decltype(MakeB1GridDescriptor_BK0_N_BK1(B1Desc{}))>;
using CGridDesc_M_N = remove_cvref_t<decltype(MakeCGridDescriptor_M_N(CDesc{}))>;
// GridwiseGemm
using GridwiseGemm = GridwiseBatchedGemmSoftmaxGemm_Xdl_CShuffle<
ADataType, // TODO: distinguish A/B datatype
GemmAccDataType,
CShuffleDataType,
CDataType,
AElementwiseOperation,
BElementwiseOperation,
AccElementwiseOperation,
B1ElementwiseOperation,
CElementwiseOperation,
InMemoryDataOperationEnum::Set,
AGridDesc_AK0_M_AK1,
BGridDesc_BK0_N_BK1,
B1GridDesc_BK0_N_BK1,
CGridDesc_M_N,
NumGemmKPrefetchStage,
BlockSize,
MPerBlock,
NPerBlock,
KPerBlock,
Gemm1NPerBlock,
Gemm1KPerBlock,
AK1,
BK1,
B1K1,
MPerXDL,
NPerXDL,
MXdlPerWave,
NXdlPerWave,
Gemm1NXdlPerWave,
ABlockTransferThreadClusterLengths_AK0_M_AK1,
ABlockTransferThreadClusterArrangeOrder,
ABlockTransferSrcAccessOrder,
ABlockTransferSrcVectorDim,
ABlockTransferSrcScalarPerVector,
ABlockTransferDstScalarPerVector_AK1,
true,
ABlockLdsExtraM,
BBlockTransferThreadClusterLengths_BK0_N_BK1,
BBlockTransferThreadClusterArrangeOrder,
BBlockTransferSrcAccessOrder,
BBlockTransferSrcVectorDim,
BBlockTransferSrcScalarPerVector,
BBlockTransferDstScalarPerVector_BK1,
true,
BBlockLdsExtraN,
B1BlockTransferThreadClusterLengths_BK0_N_BK1,
B1BlockTransferThreadClusterArrangeOrder,
B1BlockTransferSrcAccessOrder,
B1BlockTransferSrcVectorDim,
B1BlockTransferSrcScalarPerVector,
B1BlockTransferDstScalarPerVector_BK1,
false,
B1BlockLdsExtraN,
CShuffleMXdlPerWavePerShuffle,
CShuffleNXdlPerWavePerShuffle,
CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
CShuffleBlockTransferScalarPerVector_NPerBlock,
LoopSched,
matrix_padder.PadN,
MaskOutUpperTriangle>;
AGridDesc_AK0_M_AK1 a_grid_desc_ak0_m_ak1;
BGridDesc_BK0_N_BK1 b_grid_desc_bk0_n_bk1;
B1GridDesc_BK0_N_BK1 b1_grid_desc_bk0_n_bk1;
CGridDesc_M_N c_grid_desc_m_n;
C0MatrixMask c0_matrix_mask;
typename GridwiseGemm::DefaultBlock2CTileMap block_2_ctile_map;
typename GridwiseGemm::CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
c_grid_descriptor_mblock_mperblock_nblock_nperblock;
// element-wise op
AElementwiseOperation a_element_op;
BElementwiseOperation b_element_op;
B1ElementwiseOperation b1_element_op;
CElementwiseOperation c_element_op;
bool has_main_k_block_loop = true;
bool is_valid = false;
constexpr Descriptor(ADesc a,
BDesc b,
B1Desc b1,
CDesc c,
AElementwiseOperation a_element_op_,
BElementwiseOperation b_element_op_,
B1ElementwiseOperation b1_element_op_,
CElementwiseOperation c_element_op_)
: a_grid_desc_ak0_m_ak1{MakeAGridDescriptor_AK0_M_AK1(a)},
b_grid_desc_bk0_n_bk1{MakeBGridDescriptor_BK0_N_BK1(b)},
b1_grid_desc_bk0_n_bk1{MakeB1GridDescriptor_BK0_N_BK1(b1)},
c_grid_desc_m_n{MakeCGridDescriptor_M_N(c)},
block_2_ctile_map{GridwiseGemm::MakeDefaultBlock2CTileMap(c_grid_desc_m_n)},
c_grid_descriptor_mblock_mperblock_nblock_nperblock{
GridwiseGemm::MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
c_grid_desc_m_n)},
has_main_k_block_loop{GridwiseGemm::CalculateHasMainKBlockLoop(
a_grid_desc_ak0_m_ak1.GetLength(I0) * a_grid_desc_ak0_m_ak1.GetLength(I2))},
c0_matrix_mask{c.GetLength(I1)},
a_element_op{a_element_op_},
b_element_op{b_element_op_},
b1_element_op{b1_element_op_},
c_element_op{c_element_op_},
is_valid{GridwiseGemm::CheckValidity(a_grid_desc_ak0_m_ak1,
b_grid_desc_bk0_n_bk1,
b1_grid_desc_bk0_n_bk1,
c_grid_desc_m_n,
block_2_ctile_map) and
IsSupported(a_grid_desc_ak0_m_ak1.GetLength(I1),
b_grid_desc_bk0_n_bk1.GetLength(I1),
a_grid_desc_ak0_m_ak1.GetLength(I0) *
a_grid_desc_ak0_m_ak1.GetLength(I2),
b1_grid_desc_bk0_n_bk1.GetLength(I1))}
{
}
constexpr bool IsValid() const { return is_valid; }
};
template <class ADesc, class BDesc, class B1Desc, class CDesc>
static constexpr auto
make_descriptor(ADesc a,
BDesc b,
B1Desc b1,
CDesc c,
AElementwiseOperation a_element_op = AElementwiseOperation{},
BElementwiseOperation b_element_op = BElementwiseOperation{},
B1ElementwiseOperation b1_element_op = B1ElementwiseOperation{},
CElementwiseOperation c_element_op = CElementwiseOperation{})
{
return Descriptor<ADesc, BDesc, B1Desc, CDesc>(
a, b, b1, c, a_element_op, b_element_op, b1_element_op, c_element_op);
}
template <class Desc>
__device__ static void Run(const Desc& desc,
const float scale,
const ADataType* __restrict__ p_a_grid,
const ADataType* __restrict__ p_b_grid,
const ADataType* __restrict__ p_b1_grid,
CDataType* __restrict__ p_c_grid)
{
#ifndef __HIPCC_RTC__
assert(desc.is_valid);
#endif
__shared__ char p_shared_block[Desc::GridwiseGemm::GetSharedMemoryNumberOfByte()];
AccElementwiseOperation acc_element_op{scale};
if(desc.has_main_k_block_loop)
{
Desc::GridwiseGemm::template Run<true>(
p_a_grid,
p_b_grid,
p_b1_grid,
p_c_grid,
p_shared_block,
desc.a_element_op,
desc.b_element_op,
acc_element_op,
desc.b1_element_op,
desc.c_element_op,
desc.a_grid_desc_ak0_m_ak1,
desc.b_grid_desc_bk0_n_bk1,
desc.b1_grid_desc_bk0_n_bk1,
desc.c_grid_descriptor_mblock_mperblock_nblock_nperblock,
desc.block_2_ctile_map,
desc.c0_matrix_mask);
}
else
{
Desc::GridwiseGemm::template Run<false>(
p_a_grid,
p_b_grid,
p_b1_grid,
p_c_grid,
p_shared_block,
desc.a_element_op,
desc.b_element_op,
acc_element_op,
desc.b1_element_op,
desc.c_element_op,
desc.a_grid_desc_ak0_m_ak1,
desc.b_grid_desc_bk0_n_bk1,
desc.b1_grid_desc_bk0_n_bk1,
desc.c_grid_descriptor_mblock_mperblock_nblock_nperblock,
desc.block_2_ctile_map,
desc.c0_matrix_mask);
}
}
};
} // namespace device
} // namespace tensor_operation
} // namespace ck
} // namespace ck

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@@ -3,8 +3,12 @@
#pragma once
#ifndef __HIPCC_RTC__
#include <iostream>
#include <sstream>
#include "ck/host_utility/device_prop.hpp"
#include "ck/host_utility/kernel_launch.hpp"
#endif
#include "ck/utility/common_header.hpp"
#include "ck/tensor_description/tensor_descriptor.hpp"
@@ -14,8 +18,6 @@
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/matrix_padder.hpp"
#include "ck/tensor_operation/gpu/grid/gridwise_gemm_multiple_d_xdl_cshuffle.hpp"
#include "ck/host_utility/device_prop.hpp"
#include "ck/host_utility/kernel_launch.hpp"
namespace ck {
@@ -35,22 +37,22 @@ template <typename GridwiseGemm,
bool HasMainKBlockLoop>
__global__ void
#if CK_USE_LAUNCH_BOUNDS
__launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU)
__launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU)
#endif
kernel_gemm_multiple_d_xdl_cshuffle(const ADataType* __restrict__ p_a_grid,
const BDataType* __restrict__ p_b_grid,
DsPointer p_ds_grid,
EDataType* __restrict__ p_e_grid,
const AElementwiseOperation a_element_op,
const BElementwiseOperation b_element_op,
const CDEElementwiseOperation cde_element_op,
const AGridDesc_AK0_M_AK1 a_grid_desc_ak0_m_ak1,
const BGridDesc_BK0_N_BK1 b_grid_desc_bk0_n_bk1,
const DsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
ds_grid_desc_mblock_mperblock_nblock_nperblock,
const EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
e_grid_desc_mblock_mperblock_nblock_nperblock,
const Block2ETileMap block_2_etile_map)
kernel_gemm_multiple_d_xdl_cshuffle(const ADataType* __restrict__ p_a_grid,
const BDataType* __restrict__ p_b_grid,
DsPointer p_ds_grid,
EDataType* __restrict__ p_e_grid,
const AElementwiseOperation a_element_op,
const BElementwiseOperation b_element_op,
const CDEElementwiseOperation cde_element_op,
const AGridDesc_AK0_M_AK1 a_grid_desc_ak0_m_ak1,
const BGridDesc_BK0_N_BK1 b_grid_desc_bk0_n_bk1,
const DsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
ds_grid_desc_mblock_mperblock_nblock_nperblock,
const EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
e_grid_desc_mblock_mperblock_nblock_nperblock,
const Block2ETileMap block_2_etile_map)
{
#if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__) || \
defined(__gfx94__))
@@ -225,9 +227,9 @@ struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout,
return matrix_padder.PadCDescriptor_M_N(e_grid_desc_mraw_nraw);
}
static auto MakeDsGridDescriptor_M_N(const std::array<index_t, NumDTensor>& MRaws,
const std::array<index_t, NumDTensor>& NRaws,
const std::array<index_t, NumDTensor>& DsStride)
static auto MakeDsGridDescriptor_M_N(const Array<index_t, NumDTensor>& MRaws,
const Array<index_t, NumDTensor>& NRaws,
const Array<index_t, NumDTensor>& DsStride)
{
return generate_tuple(
[&](auto i) {
@@ -309,6 +311,7 @@ struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout,
using Block2ETileMap =
remove_cvref_t<decltype(GridwiseGemm::MakeDefaultBlock2ETileMap(EGridDesc_M_N{}))>;
#ifndef __HIPCC_RTC__
// Argument
struct Argument : public BaseArgument
{
@@ -498,6 +501,8 @@ struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout,
}
};
#endif
static constexpr bool IsSupported(index_t MRaw_, index_t NRaw_, index_t KRaw_)
{
// check vector load/store
@@ -578,6 +583,7 @@ struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout,
return true;
}
#ifndef __HIPCC_RTC__
static bool IsSupportedArgument(const Argument& arg)
{
if(!ck::is_xdl_supported())
@@ -676,11 +682,13 @@ struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout,
{
auto str = std::stringstream();
std::map<LoopScheduler, std::string> LoopSchedToString{
{LoopScheduler::Default, "Default"}, {LoopScheduler::Interwave, "Interwave"}};
std::map<LoopScheduler, std::string> LoopSchedToString{{LoopScheduler::Default, "Default"},
{ LoopScheduler::Interwave,
"Interwave" }};
std::map<PipelineVersion, std::string> PipelineVersionToString{{PipelineVersion::v1, "v1"},
{PipelineVersion::v2, "v2"}};
{ PipelineVersion::v2,
"v2" }};
// clang-format off
str << "DeviceGemmMultipleD_Xdl_CShuffle"
@@ -709,6 +717,7 @@ struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout,
return str.str();
}
#endif
template <class ADesc, class BDesc, class DsDesc, class EDesc>
struct Descriptor
@@ -847,7 +856,9 @@ struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout,
EDataType* __restrict__ p_e_grid)
{
__shared__ char p_shared_block[GridwiseGemm::GetSharedMemoryNumberOfByte()];
#ifndef __HIPCC_RTC__
assert(desc.IsValid());
#endif
if(desc.has_main_k_block_loop)
{
GridwiseGemm::template Run<true>(p_a_grid,