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Unverified Commit 453ca373 authored by aledudek's avatar aledudek Committed by GitHub
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[CK TILE] Refactor GemmKernel to be reused by other GEMM related operators (#1730) 

* Gemm Kernel Refactor part1

* Gemm Kernel Refactor common gemm pipeline part2

* [CK TILE] Refactor batched gemm to reuse GemmKernel

* [CK TILE] Refactor GemmKernel - review changes part1

* [CK TILE] Refactor GemmKernel - references fix

* [CK TILE] Refactor GemmKernel - naming changes, add problem

* [CK_TILE] Refactor GemmKernel - update tests

* [CK_TILE] Refactor GemmKernel - review changes

* [CK_TILE] Refactor GemmKernel - update test

* [CK_TILE] Refactor GemmKernel - constness fixes

* [CK_TILE] Refactor GemmKernel - update tests
parent 1c1b3363
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example/ck_tile/03_gemm/gemm_basic.cpp
View file @ 453ca373
...@@ -15,7 +15,7 @@ ...@@ -15,7 +15,7 @@
#include "gemm_basic.hpp" #include "gemm_basic.hpp"
template <typename ALayout, typename BLayout, typename CLayout> template <typename ALayout, typename BLayout, typename CLayout>
float gemm_calc(const gemm_basic_args& args, const ck_tile::stream_config& s) float gemm_calc(const ck_tile::GemmHostArgs& args, const ck_tile::stream_config& s)
{ {
// The kPadM, kPadN, kPadK & kBlockPerCu should also come from the Codegen part. // The kPadM, kPadN, kPadK & kBlockPerCu should also come from the Codegen part.
constexpr bool kPadM = false; constexpr bool kPadM = false;
...@@ -79,17 +79,9 @@ float gemm_calc(const gemm_basic_args& args, const ck_tile::stream_config& s) ...@@ -79,17 +79,9 @@ float gemm_calc(const gemm_basic_args& args, const ck_tile::stream_config& s)
// Now we only use the BlockGemmASmemBSmemCRegV1DefaultPolicy. // Now we only use the BlockGemmASmemBSmemCRegV1DefaultPolicy.
using Kernel = ck_tile::GemmKernel<TilePartitioner, CodegenGemmPipeline, GemmEpilogue>; using Kernel = ck_tile::GemmKernel<TilePartitioner, CodegenGemmPipeline, GemmEpilogue>;
auto kargs = Kernel::MakeKargs(args.p_a, auto kargs = Kernel::MakeKernelArgs(args);
args.p_b,
args.p_c, const dim3 grids = Kernel::GridSize(args.M, args.N, args.k_batch);
args.M,
args.N,
args.K,
args.stride_A,
args.stride_B,
args.stride_C);
const dim3 grids = Kernel::GridSize(args.M, args.N, args.kbatch);
constexpr dim3 blocks = Kernel::BlockSize(); constexpr dim3 blocks = Kernel::BlockSize();
if(!Kernel::IsSupportedArgument(kargs)) if(!Kernel::IsSupportedArgument(kargs))
......
example/ck_tile/03_gemm/gemm_basic.hpp
View file @ 453ca373
...@@ -51,20 +51,6 @@ using BDataType = Types::BDataType; ...@@ -51,20 +51,6 @@ using BDataType = Types::BDataType;
using AccDataType = Types::AccDataType; using AccDataType = Types::AccDataType;
using CDataType = Types::CDataType; using CDataType = Types::CDataType;
struct gemm_basic_args
{
const void* p_a;
const void* p_b;
void* p_c;
ck_tile::index_t kbatch;
ck_tile::index_t M;
ck_tile::index_t N;
ck_tile::index_t K;
ck_tile::index_t stride_A;
ck_tile::index_t stride_B;
ck_tile::index_t stride_C;
};
auto create_args(int argc, char* argv[]) auto create_args(int argc, char* argv[])
{ {
ck_tile::ArgParser arg_parser; ck_tile::ArgParser arg_parser;
...@@ -89,4 +75,4 @@ auto create_args(int argc, char* argv[]) ...@@ -89,4 +75,4 @@ auto create_args(int argc, char* argv[])
} }
// host API // host API
float gemm_calc(gemm_basic_args args, const ck_tile::stream_config& s); float gemm_calc(const ck_tile::GemmHostArgs& args, const ck_tile::stream_config& s);
example/ck_tile/03_gemm/run_gemm_example.inc
View file @ 453ca373
...@@ -16,11 +16,11 @@ float invoke_gemm(ck_tile::DeviceMem& a_m_k_dev_buf, ...@@ -16,11 +16,11 @@ float invoke_gemm(ck_tile::DeviceMem& a_m_k_dev_buf,
int n_warmup, int n_warmup,
int n_repeat) int n_repeat)
{ {
gemm_basic_args args; ck_tile::GemmHostArgs args;
args.p_a = a_m_k_dev_buf.GetDeviceBuffer(); args.a_ptr = a_m_k_dev_buf.GetDeviceBuffer();
args.p_b = b_k_n_dev_buf.GetDeviceBuffer(); args.b_ptr = b_k_n_dev_buf.GetDeviceBuffer();
args.p_c = c_m_n_dev_buf.GetDeviceBuffer(); args.c_ptr = c_m_n_dev_buf.GetDeviceBuffer();
args.kbatch = kbatch; args.k_batch = kbatch;
args.M = M; args.M = M;
args.N = N; args.N = N;
args.K = K; args.K = K;
......
example/ck_tile/16_batched_gemm/batched_gemm.cpp
View file @ 453ca373
...@@ -16,7 +16,7 @@ ...@@ -16,7 +16,7 @@
#include "batched_gemm.hpp" #include "batched_gemm.hpp"
template <typename ALayout, typename BLayout, typename CLayout> template <typename ALayout, typename BLayout, typename CLayout>
float batched_gemm(const batched_gemm_kargs& args, const ck_tile::stream_config& s) float batched_gemm(const ck_tile::BatchedGemmHostArgs& args, const ck_tile::stream_config& s)
{ {
// The kPadM, kPadN, kPadK & kBlockPerCu should also come from the Codegen part. // The kPadM, kPadN, kPadK & kBlockPerCu should also come from the Codegen part.
constexpr bool kPadM = false; constexpr bool kPadM = false;
...@@ -79,9 +79,9 @@ float batched_gemm(const batched_gemm_kargs& args, const ck_tile::stream_config& ...@@ -79,9 +79,9 @@ float batched_gemm(const batched_gemm_kargs& args, const ck_tile::stream_config&
// Now we only use the BlockGemmASmemBSmemCRegV1DefaultPolicy. // Now we only use the BlockGemmASmemBSmemCRegV1DefaultPolicy.
using Kernel = ck_tile::BatchedGemmKernel<TilePartitioner, CodegenGemmPipeline, GemmEpilogue>; using Kernel = ck_tile::BatchedGemmKernel<TilePartitioner, CodegenGemmPipeline, GemmEpilogue>;
auto kargs = Kernel::MakeKargs(args); auto kargs = Kernel::MakeKernelArgs(args);
const dim3 grids = Kernel::GridSize(args); const dim3 grids = Kernel::GridSize(args.M, args.N, args.batch_count);
constexpr dim3 blocks = Kernel::BlockSize(); constexpr dim3 blocks = Kernel::BlockSize();
if(s.log_level_ > 0) if(s.log_level_ > 0)
......
example/ck_tile/16_batched_gemm/batched_gemm.hpp
View file @ 453ca373
...@@ -29,10 +29,6 @@ using BDataType = Types::BDataType; ...@@ -29,10 +29,6 @@ using BDataType = Types::BDataType;
using AccDataType = Types::AccDataType; using AccDataType = Types::AccDataType;
using CDataType = Types::CDataType; using CDataType = Types::CDataType;
struct batched_gemm_kargs : public ck_tile::BatchedGemmHostArgs
{
};
auto create_args(int argc, char* argv[]) auto create_args(int argc, char* argv[])
{ {
ck_tile::ArgParser arg_parser; ck_tile::ArgParser arg_parser;
...@@ -60,4 +56,4 @@ auto create_args(int argc, char* argv[]) ...@@ -60,4 +56,4 @@ auto create_args(int argc, char* argv[])
} }
// host API // host API
float batched_gemm(batched_gemm_kargs args, const ck_tile::stream_config& s); float batched_gemm(const ck_tile::BatchedGemmHostArgs& args, const ck_tile::stream_config& s);
example/ck_tile/16_batched_gemm/run_batched_gemm_example.inc
View file @ 453ca373
...@@ -20,7 +20,7 @@ float invoke_batched_gemm(ck_tile::DeviceMem& a_m_k_dev_buf, ...@@ -20,7 +20,7 @@ float invoke_batched_gemm(ck_tile::DeviceMem& a_m_k_dev_buf,
int n_warmup, int n_warmup,
int n_repeat) int n_repeat)
{ {
batched_gemm_kargs args; ck_tile::BatchedGemmHostArgs args;
args.a_ptr = a_m_k_dev_buf.GetDeviceBuffer(); args.a_ptr = a_m_k_dev_buf.GetDeviceBuffer();
args.b_ptr = b_k_n_dev_buf.GetDeviceBuffer(); args.b_ptr = b_k_n_dev_buf.GetDeviceBuffer();
args.c_ptr = c_m_n_dev_buf.GetDeviceBuffer(); args.c_ptr = c_m_n_dev_buf.GetDeviceBuffer();
......
include/ck_tile/ops/gemm/kernel/batched_gemm_kernel.hpp
View file @ 453ca373
...@@ -3,90 +3,93 @@ ...@@ -3,90 +3,93 @@
#pragma once #pragma once
#include <iostream> #include "ck_tile/ops/gemm/kernel/gemm_kernel.hpp"
#include <string>
#include "ck_tile/core.hpp"
#include "ck_tile/ops/common.hpp"
namespace ck_tile { namespace ck_tile {
struct BatchedGemmHostArgs struct BatchedGemmHostArgs : public ck_tile::GemmHostArgs
{ {
const void* a_ptr; CK_TILE_HOST BatchedGemmHostArgs() = default;
const void* b_ptr; CK_TILE_HOST BatchedGemmHostArgs(const void* a_ptr_,
void* c_ptr; const void* b_ptr_,
index_t M; void* c_ptr_,
index_t N; ck_tile::index_t k_batch_,
index_t K; ck_tile::index_t M_,
index_t stride_A; ck_tile::index_t N_,
index_t stride_B; ck_tile::index_t K_,
index_t stride_C; ck_tile::index_t stride_A_,
index_t batch_stride_A; ck_tile::index_t stride_B_,
index_t batch_stride_B; ck_tile::index_t stride_C_,
index_t batch_stride_C; ck_tile::index_t batch_stride_A_,
index_t batch_count; ck_tile::index_t batch_stride_B_,
ck_tile::index_t batch_stride_C_,
ck_tile::index_t batch_count_)
: GemmHostArgs(
a_ptr_, b_ptr_, c_ptr_, k_batch_, M_, N_, K_, stride_A_, stride_B_, stride_C_),
batch_stride_A(batch_stride_A_),
batch_stride_B(batch_stride_B_),
batch_stride_C(batch_stride_C_),
batch_count(batch_count_)
{
}
ck_tile::index_t batch_stride_A;
ck_tile::index_t batch_stride_B;
ck_tile::index_t batch_stride_C;
ck_tile::index_t batch_count;
}; };
template <typename TilePartitioner_, typename GemmPipeline_, typename EpiloguePipeline_> template <typename TilePartitioner_, typename GemmPipeline_, typename EpiloguePipeline_>
struct BatchedGemmKernel struct BatchedGemmKernel : public GemmKernel<TilePartitioner_, GemmPipeline_, EpiloguePipeline_>
{ {
using TilePartitioner = remove_cvref_t<TilePartitioner_>; using Base = GemmKernel<TilePartitioner_, GemmPipeline_, EpiloguePipeline_>;
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 GemmKernelArgs = typename Base::GemmKernelArgs;
using BDataType = remove_cvref_t<typename GemmPipeline::BDataType>;
using CDataType = remove_cvref_t<typename EpiloguePipeline::ODataType>;
struct BatchedGemmKargs using ADataType = typename Base::ADataType;
using BDataType = typename Base::BDataType;
using CDataType = typename Base::CDataType;
using TilePartitioner = typename Base::TilePartitioner;
using GemmPipeline = typename Base::GemmPipeline;
using EpiloguePipeline = typename Base::EpiloguePipeline;
using ALayout = typename Base::ALayout;
using BLayout = typename Base::BLayout;
using CLayout = typename Base::CLayout;
struct BatchedGemmKernelArgs : GemmKernelArgs
{ {
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_A;
index_t batch_stride_B; index_t batch_stride_B;
index_t batch_stride_C; index_t batch_stride_C;
index_t batch_count; index_t batch_count;
}; };
using Kargs = BatchedGemmKargs; using KernelArgs = BatchedGemmKernelArgs;
using Hargs = BatchedGemmHostArgs;
__host__ static constexpr auto GridSize(const Hargs& h) __host__ static constexpr auto GridSize(index_t M, index_t N, index_t batch_count)
{ {
return TilePartitioner::GridSize(h.M, h.N, h.batch_count); return TilePartitioner::GridSize(M, N, batch_count);
} }
__host__ static constexpr auto BlockSize() { return dim3(KernelBlockSize); } __host__ static constexpr auto BlockSize() { return dim3(Base::KernelBlockSize); }
CK_TILE_HOST static constexpr BatchedGemmKargs MakeKargs(const Hargs& h) CK_TILE_HOST static constexpr BatchedGemmKernelArgs
MakeKernelArgs(const BatchedGemmHostArgs& hostArgs)
{ {
Kargs k; return BatchedGemmKernelArgs{{hostArgs.a_ptr,
k.a_ptr = h.a_ptr; hostArgs.b_ptr,
k.b_ptr = h.b_ptr; hostArgs.c_ptr,
k.c_ptr = h.c_ptr; hostArgs.M,
k.M = h.M; hostArgs.N,
k.N = h.N; hostArgs.K,
k.K = h.K; hostArgs.stride_A,
k.stride_A = h.stride_A; hostArgs.stride_B,
k.stride_B = h.stride_B; hostArgs.stride_C},
k.stride_C = h.stride_C; hostArgs.batch_stride_A,
k.batch_stride_A = h.batch_stride_A; hostArgs.batch_stride_B,
k.batch_stride_B = h.batch_stride_B; hostArgs.batch_stride_C,
k.batch_stride_C = h.batch_stride_C; hostArgs.batch_count};
k.batch_count = h.batch_count;
return k;
} }
CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize() CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
...@@ -94,7 +97,7 @@ struct BatchedGemmKernel ...@@ -94,7 +97,7 @@ struct BatchedGemmKernel
return max(GemmPipeline::GetSmemSize(), EpiloguePipeline::GetSmemSize()); return max(GemmPipeline::GetSmemSize(), EpiloguePipeline::GetSmemSize());
} }
CK_TILE_DEVICE void operator()(Kargs kargs) const CK_TILE_DEVICE void operator()(BatchedGemmKernelArgs kargs) const
{ {
const auto [i_m, i_n] = TilePartitioner{}(); const auto [i_m, i_n] = TilePartitioner{}();
const auto i_batch = __builtin_amdgcn_readfirstlane(blockIdx.z); const auto i_batch = __builtin_amdgcn_readfirstlane(blockIdx.z);
...@@ -102,156 +105,17 @@ struct BatchedGemmKernel ...@@ -102,156 +105,17 @@ struct BatchedGemmKernel
// options // options
const auto batch_stride_A = __builtin_amdgcn_readfirstlane(kargs.batch_stride_A); 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 auto batch_offset_A = __builtin_amdgcn_readfirstlane(i_batch * batch_stride_A);
const ADataType* a_start = static_cast<const ADataType*>(kargs.a_ptr); const ADataType* a_ptr = static_cast<const ADataType*>(kargs.a_ptr) + batch_offset_A;
const auto batch_stride_B = __builtin_amdgcn_readfirstlane(kargs.batch_stride_B); 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 auto batch_offset_B = __builtin_amdgcn_readfirstlane(i_batch * batch_stride_B);
const BDataType* b_start = static_cast<const BDataType*>(kargs.b_ptr); const BDataType* b_ptr = static_cast<const BDataType*>(kargs.b_ptr) + batch_offset_B;
// 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_stride_C = __builtin_amdgcn_readfirstlane(kargs.batch_stride_C);
const auto batch_offset_C = __builtin_amdgcn_readfirstlane(i_batch * 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); CDataType* c_ptr = static_cast<CDataType*>(kargs.c_ptr) + batch_offset_C;
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); this->RunGemm(a_ptr, b_ptr, c_ptr, kargs, i_m, i_n);
} }
}; };
......
include/ck_tile/ops/gemm/kernel/gemm_kernel.hpp
View file @ 453ca373
...@@ -12,6 +12,50 @@ ...@@ -12,6 +12,50 @@
namespace ck_tile { namespace ck_tile {
struct GemmProblem
{
CK_TILE_HOST GemmProblem() = default;
CK_TILE_HOST GemmProblem(
index_t M_, index_t N_, index_t K_, index_t stride_A_, index_t stride_B_, index_t stride_C_)
: M(M_), N(N_), K(K_), stride_A(stride_A_), stride_B(stride_B_), stride_C(stride_C_)
{
}
index_t M;
index_t N;
index_t K;
index_t stride_A;
index_t stride_B;
index_t stride_C;
};
struct GemmHostArgs : public GemmProblem
{
CK_TILE_HOST GemmHostArgs() = default;
CK_TILE_HOST GemmHostArgs(const void* a_ptr_,
const void* b_ptr_,
void* c_ptr_,
index_t k_batch_,
index_t M_,
index_t N_,
index_t K_,
index_t stride_A_,
index_t stride_B_,
index_t stride_C_)
: GemmProblem(M_, N_, K_, stride_A_, stride_B_, stride_C_),
a_ptr(a_ptr_),
b_ptr(b_ptr_),
c_ptr(c_ptr_),
k_batch(k_batch_)
{
}
const void* a_ptr;
const void* b_ptr;
void* c_ptr;
index_t k_batch;
};
template <typename TilePartitioner_, typename GemmPipeline_, typename EpiloguePipeline_> template <typename TilePartitioner_, typename GemmPipeline_, typename EpiloguePipeline_>
struct GemmKernel struct GemmKernel
{ {
...@@ -25,9 +69,12 @@ struct GemmKernel ...@@ -25,9 +69,12 @@ struct GemmKernel
using ADataType = remove_cvref_t<typename GemmPipeline::ADataType>; using ADataType = remove_cvref_t<typename GemmPipeline::ADataType>;
using BDataType = remove_cvref_t<typename GemmPipeline::BDataType>; using BDataType = remove_cvref_t<typename GemmPipeline::BDataType>;
// using CAccDataType = remove_cvref_t<typename GemmPipeline::CDataType>;
using CDataType = remove_cvref_t<typename EpiloguePipeline::ODataType>; using CDataType = remove_cvref_t<typename EpiloguePipeline::ODataType>;
static constexpr auto I0 = number<0>();
static constexpr auto I1 = number<1>();
static constexpr auto I2 = number<2>();
__host__ static constexpr auto GridSize(index_t M, index_t N, index_t KBatch) __host__ static constexpr auto GridSize(index_t M, index_t N, index_t KBatch)
{ {
return TilePartitioner::GridSize(M, N, KBatch); return TilePartitioner::GridSize(M, N, KBatch);
...@@ -35,7 +82,7 @@ struct GemmKernel ...@@ -35,7 +82,7 @@ struct GemmKernel
__host__ static constexpr auto BlockSize() { return dim3(KernelBlockSize); } __host__ static constexpr auto BlockSize() { return dim3(KernelBlockSize); }
struct GemmCommonKargs struct GemmKernelArgs
{ {
const void* a_ptr; const void* a_ptr;
const void* b_ptr; const void* b_ptr;
...@@ -48,25 +95,37 @@ struct GemmKernel ...@@ -48,25 +95,37 @@ struct GemmKernel
index_t stride_C; index_t stride_C;
}; };
CK_TILE_HOST static constexpr GemmCommonKargs MakeKargs(const void* a_ptr, CK_TILE_HOST static constexpr GemmKernelArgs MakeKernelArgs(const GemmHostArgs& hostArgs)
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)
{ {
return GemmCommonKargs{a_ptr, b_ptr, c_ptr, M, N, K, stride_A, stride_B, stride_C}; return GemmKernelArgs{hostArgs.a_ptr,
hostArgs.b_ptr,
hostArgs.c_ptr,
hostArgs.M,
hostArgs.N,
hostArgs.K,
hostArgs.stride_A,
hostArgs.stride_B,
hostArgs.stride_C};
} }
// CK_TILE_HOST static constexpr GemmKernelArgs MakeKernelArgs(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)
// {
// return GemmKernelArgs{a_ptr, b_ptr, c_ptr, M, N, K, stride_A, stride_B, stride_C};
// }
CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize() CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
{ {
return max(GemmPipeline::GetSmemSize(), EpiloguePipeline::GetSmemSize()); return max(GemmPipeline::GetSmemSize(), EpiloguePipeline::GetSmemSize());
} }
CK_TILE_HOST static bool IsSupportedArgument(const GemmCommonKargs& kargs) CK_TILE_HOST static bool IsSupportedArgument(const GemmKernelArgs& kargs)
{ {
if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>) if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
{ {
...@@ -139,18 +198,16 @@ struct GemmKernel ...@@ -139,18 +198,16 @@ struct GemmKernel
return true; return true;
} }
CK_TILE_DEVICE void operator()(GemmCommonKargs kargs) const CK_TILE_DEVICE auto MakeGemmTensorViews(const ADataType* a_ptr,
const BDataType* b_ptr,
CDataType* c_ptr,
const GemmKernelArgs& kargs) const
{ {
const auto [i_m, i_n] = TilePartitioner{}(); const auto& a_tensor_view = [&]() {
// 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>) if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
{ {
return make_naive_tensor_view<address_space_enum::global>( return make_naive_tensor_view<address_space_enum::global>(
a_start, a_ptr,
make_tuple(kargs.M, kargs.K), make_tuple(kargs.M, kargs.K),
make_tuple(kargs.stride_A, 1), make_tuple(kargs.stride_A, 1),
number<GemmPipeline::VectorSizeA>{}, number<GemmPipeline::VectorSizeA>{},
...@@ -159,7 +216,7 @@ struct GemmKernel ...@@ -159,7 +216,7 @@ struct GemmKernel
else else
{ {
return make_naive_tensor_view<address_space_enum::global>( return make_naive_tensor_view<address_space_enum::global>(
a_start, a_ptr,
make_tuple(kargs.M, kargs.K), make_tuple(kargs.M, kargs.K),
make_tuple(1, kargs.stride_A), make_tuple(1, kargs.stride_A),
number<1>{}, number<1>{},
...@@ -167,11 +224,11 @@ struct GemmKernel ...@@ -167,11 +224,11 @@ struct GemmKernel
} }
}(); }();
auto b_tensor_view = [&]() { const auto& b_tensor_view = [&]() {
if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::RowMajor>) if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::RowMajor>)
{ {
return make_naive_tensor_view<address_space_enum::global>( return make_naive_tensor_view<address_space_enum::global>(
b_start, b_ptr,
make_tuple(kargs.N, kargs.K), make_tuple(kargs.N, kargs.K),
make_tuple(1, kargs.stride_B), make_tuple(1, kargs.stride_B),
number<1>{}, number<1>{},
...@@ -180,7 +237,7 @@ struct GemmKernel ...@@ -180,7 +237,7 @@ struct GemmKernel
else else
{ {
return make_naive_tensor_view<address_space_enum::global>( return make_naive_tensor_view<address_space_enum::global>(
b_start, b_ptr,
make_tuple(kargs.N, kargs.K), make_tuple(kargs.N, kargs.K),
make_tuple(kargs.stride_B, 1), make_tuple(kargs.stride_B, 1),
number<GemmPipeline::VectorSizeB>{}, number<GemmPipeline::VectorSizeB>{},
...@@ -188,7 +245,35 @@ struct GemmKernel ...@@ -188,7 +245,35 @@ struct GemmKernel
} }
}(); }();
auto a_pad_view = [&]() { const 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_ptr,
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_ptr,
make_tuple(kargs.M, kargs.N),
make_tuple(1, kargs.stride_C),
number<1>{},
number<1>{});
}
}();
return make_tuple(a_tensor_view, b_tensor_view, c_tensor_view);
}
template <typename TensorView>
CK_TILE_DEVICE auto MakeGemmPadViews(const TensorView& views) const
{
const auto& a_pad_view = [&]() {
const auto& a_tensor_view = views.at(I0);
if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>) if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
{ {
return pad_tensor_view( return pad_tensor_view(
...@@ -204,14 +289,9 @@ struct GemmKernel ...@@ -204,14 +289,9 @@ struct GemmKernel
sequence<GemmPipeline::kPadM, false>{}); 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 = [&]() { const auto& b_pad_view = [&]() {
const auto& b_tensor_view = views.at(I1);
if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::ColumnMajor>) if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::ColumnMajor>)
{ {
return pad_tensor_view( return pad_tensor_view(
...@@ -228,43 +308,8 @@ struct GemmKernel ...@@ -228,43 +308,8 @@ struct GemmKernel
} }
}(); }();
auto b_block_window = make_tile_window( const auto& c_pad_view = [&]() {
b_pad_view, const auto& c_tensor_view = views.at(I2);
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);
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>) if constexpr(std::is_same_v<CLayout, tensor_layout::gemm::RowMajor>)
{ {
return pad_tensor_view( return pad_tensor_view(
...@@ -280,12 +325,82 @@ struct GemmKernel ...@@ -280,12 +325,82 @@ struct GemmKernel
sequence<GemmPipeline::kPadM, false>{}); sequence<GemmPipeline::kPadM, false>{});
} }
}(); }();
auto CBlockWindow_pad = make_tile_window(
return make_tuple(a_pad_view, b_pad_view, c_pad_view);
}
template <typename PadView>
CK_TILE_DEVICE auto
MakeGemmTileWindows(const PadView& views, const index_t i_m, const index_t i_n) const
{
const auto& a_pad_view = views.at(I0);
const auto& a_block_window = make_tile_window(
a_pad_view,
make_tuple(number<TilePartitioner::kM>{}, number<TilePartitioner::kK>{}),
{i_m, 0});
const auto& b_pad_view = views.at(I1);
const auto& b_block_window = make_tile_window(
b_pad_view,
make_tuple(number<TilePartitioner::kN>{}, number<TilePartitioner::kK>{}),
{i_n, 0});
const auto& c_pad_view = views.at(I2);
auto c_block_window = make_tile_window(
c_pad_view, c_pad_view,
make_tuple(number<TilePartitioner::kM>{}, number<TilePartitioner::kN>{}), make_tuple(number<TilePartitioner::kM>{}, number<TilePartitioner::kN>{}),
{i_m, i_n}); {i_m, i_n});
EpiloguePipeline{}(CBlockWindow_pad, c_block_tile); return make_tuple(a_block_window, b_block_window, c_block_window);
}
/**
* @brief Runs single GEMM problem cooperatively by whole workgroup.
*
* @param a_ptr input A pointer
* @param b_ptr input B pointer
* @param c_ptr output C pointer
* @param kargs GEMM kernel arguments
* @param block_idx_m The GEMM's output M dimension tile index processed by this workgroup.
* @param block_idx_n The GEMM's output N dimension tile index processed by this workgroup.
*/
CK_TILE_DEVICE void RunGemm(const ADataType* a_ptr,
const BDataType* b_ptr,
CDataType* c_ptr,
const GemmKernelArgs& kargs,
const index_t block_idx_m,
const index_t block_idx_n) const
{
// Create Gemm tensor views, pad views and tile windows
const auto& gemm_tensor_views_tuple = MakeGemmTensorViews(a_ptr, b_ptr, c_ptr, kargs);
const auto& gemm_pad_views = MakeGemmPadViews(gemm_tensor_views_tuple);
auto gemm_tile_windows = MakeGemmTileWindows(gemm_pad_views, block_idx_m, block_idx_n);
// allocate LDS
__shared__ char smem_ptr[GetSmemSize()];
const index_t num_loop = TilePartitioner::GetLoopNum(kargs.K);
// Run GEMM cooperatively by whole workgroup.
const auto& a_block_window = gemm_tile_windows.at(I0);
const auto& b_block_window = gemm_tile_windows.at(I1);
const auto& c_block_tile =
GemmPipeline{}.template operator()(a_block_window, b_block_window, num_loop, smem_ptr);
// Run Epilogue Pipeline
auto& c_block_window = gemm_tile_windows.at(I2);
EpiloguePipeline{}(c_block_window, c_block_tile);
}
CK_TILE_DEVICE void operator()(GemmKernelArgs kargs) const
{
const auto [i_m, i_n] = TilePartitioner{}();
// options
const ADataType* a_ptr = static_cast<const ADataType*>(kargs.a_ptr);
const BDataType* b_ptr = static_cast<const BDataType*>(kargs.b_ptr);
CDataType* c_ptr = static_cast<CDataType*>(kargs.c_ptr);
RunGemm(a_ptr, b_ptr, c_ptr, kargs, i_m, i_n);
} }
}; };
......
test/ck_tile/batched_gemm/test_batched_gemm_util.hpp
View file @ 453ca373
...@@ -24,12 +24,9 @@ class TestCkTileBatchedGemm : public ::testing::Test ...@@ -24,12 +24,9 @@ class TestCkTileBatchedGemm : public ::testing::Test
using AccDataType = std::tuple_element_t<5, Tuple>; using AccDataType = std::tuple_element_t<5, Tuple>;
using CDataType = std::tuple_element_t<6, Tuple>; using CDataType = std::tuple_element_t<6, Tuple>;
struct batched_gemm_kargs : public ck_tile::BatchedGemmHostArgs
{
};
template <typename ALayout, typename BLayout, typename CLayout> template <typename ALayout, typename BLayout, typename CLayout>
void invoke_batched_gemm(const batched_gemm_kargs& args, const ck_tile::stream_config& s) void invoke_batched_gemm(const ck_tile::BatchedGemmHostArgs& args,
const ck_tile::stream_config& s)
{ {
// The kPadM, kPadN, kPadK & kBlockPerCu should also come from the Codegen part. // The kPadM, kPadN, kPadK & kBlockPerCu should also come from the Codegen part.
constexpr bool kPadM = false; constexpr bool kPadM = false;
...@@ -94,9 +91,9 @@ class TestCkTileBatchedGemm : public ::testing::Test ...@@ -94,9 +91,9 @@ class TestCkTileBatchedGemm : public ::testing::Test
using Kernel = using Kernel =
ck_tile::BatchedGemmKernel<TilePartitioner, CodegenGemmPipeline, GemmEpilogue>; ck_tile::BatchedGemmKernel<TilePartitioner, CodegenGemmPipeline, GemmEpilogue>;
auto kargs = Kernel::MakeKargs(args); auto kargs = Kernel::MakeKernelArgs(args);
const dim3 grids = Kernel::GridSize(args); const dim3 grids = Kernel::GridSize(args.M, args.N, args.batch_count);
constexpr dim3 blocks = Kernel::BlockSize(); constexpr dim3 blocks = Kernel::BlockSize();
if(s.log_level_ > 0) if(s.log_level_ > 0)
...@@ -185,21 +182,22 @@ class TestCkTileBatchedGemm : public ::testing::Test ...@@ -185,21 +182,22 @@ class TestCkTileBatchedGemm : public ::testing::Test
c_m_n_dev_buf.SetZero(); c_m_n_dev_buf.SetZero();
c_m_n_dev_result.SetZero(); c_m_n_dev_result.SetZero();
batched_gemm_kargs kargs{a_m_k_dev_buf.GetDeviceBuffer(), ck_tile::BatchedGemmHostArgs args;
b_k_n_dev_buf.GetDeviceBuffer(), args.a_ptr = a_m_k_dev_buf.GetDeviceBuffer();
c_m_n_dev_buf.GetDeviceBuffer(), args.b_ptr = b_k_n_dev_buf.GetDeviceBuffer();
M, args.c_ptr = c_m_n_dev_buf.GetDeviceBuffer();
N, args.M = M;
K, args.N = N;
StrideA, args.K = K;
StrideB, args.stride_A = StrideA;
StrideC, args.stride_B = StrideB;
BatchStrideA, args.stride_C = StrideC;
BatchStrideB, args.batch_stride_A = BatchStrideA;
BatchStrideC, args.batch_stride_B = BatchStrideB;
BatchCount}; args.batch_stride_C = BatchStrideC;
args.batch_count = BatchCount;
invoke_batched_gemm<ALayout, BLayout, CLayout>(kargs,
invoke_batched_gemm<ALayout, BLayout, CLayout>(args,
ck_tile::stream_config{nullptr, false}); ck_tile::stream_config{nullptr, false});
std::cout << "Run kernel with M =" << M << " N =" << N << " K =" << K std::cout << "Run kernel with M =" << M << " N =" << N << " K =" << K
......
test/ck_tile/gemm/test_gemm_pipeline_util.hpp
View file @ 453ca373
...@@ -31,22 +31,8 @@ class TestCkTileGemmPipeline : public ::testing::Test ...@@ -31,22 +31,8 @@ class TestCkTileGemmPipeline : public ::testing::Test
static constexpr auto PipelineType = std::tuple_element_t<8, Tuple>::value; static constexpr auto PipelineType = std::tuple_element_t<8, Tuple>::value;
// TODO: expose tile size through test t-param ? // TODO: expose tile size through test t-param ?
struct gemm_args
{
const void* p_a;
const void* p_b;
void* p_c;
ck_tile::index_t kbatch;
ck_tile::index_t M;
ck_tile::index_t N;
ck_tile::index_t K;
ck_tile::index_t stride_A;
ck_tile::index_t stride_B;
ck_tile::index_t stride_C;
};
template <bool PadM, bool PadN, bool PadK> template <bool PadM, bool PadN, bool PadK>
void invoke_gemm(const gemm_args& args, const ck_tile::stream_config& s) void invoke_gemm(const ck_tile::GemmHostArgs& args, const ck_tile::stream_config& s)
{ {
// TODO: This should be parameterized in tests // TODO: This should be parameterized in tests
constexpr ck_tile::index_t M_Tile = 128; constexpr ck_tile::index_t M_Tile = 128;
...@@ -117,17 +103,9 @@ class TestCkTileGemmPipeline : public ::testing::Test ...@@ -117,17 +103,9 @@ class TestCkTileGemmPipeline : public ::testing::Test
has_hot_loop_v, has_hot_loop_v,
tail_number_v>>>; tail_number_v>>>;
using Kernel = ck_tile::GemmKernel<TilePartitioner, GemmPipeline, GemmEpilogue>; using Kernel = ck_tile::GemmKernel<TilePartitioner, GemmPipeline, GemmEpilogue>;
auto kargs = Kernel::MakeKargs(args.p_a, auto kargs = Kernel::MakeKernelArgs(args);
args.p_b,
args.p_c, const dim3 grids = Kernel::GridSize(args.M, args.N, args.k_batch);
args.M,
args.N,
args.K,
args.stride_A,
args.stride_B,
args.stride_C);
const dim3 grids = Kernel::GridSize(args.M, args.N, args.kbatch);
constexpr dim3 blocks = Kernel::BlockSize(); constexpr dim3 blocks = Kernel::BlockSize();
if(!Kernel::IsSupportedArgument(kargs)) if(!Kernel::IsSupportedArgument(kargs))
...@@ -319,11 +297,11 @@ class TestCkTileGemmPipeline : public ::testing::Test ...@@ -319,11 +297,11 @@ class TestCkTileGemmPipeline : public ::testing::Test
c_m_n_dev_buf.SetZero(); c_m_n_dev_buf.SetZero();
c_m_n_dev_result.SetZero(); c_m_n_dev_result.SetZero();
gemm_args args; ck_tile::GemmHostArgs args;
args.p_a = a_m_k_dev_buf.GetDeviceBuffer(); args.a_ptr = a_m_k_dev_buf.GetDeviceBuffer();
args.p_b = b_k_n_dev_buf.GetDeviceBuffer(); args.b_ptr = b_k_n_dev_buf.GetDeviceBuffer();
args.p_c = c_m_n_dev_buf.GetDeviceBuffer(); args.c_ptr = c_m_n_dev_buf.GetDeviceBuffer();
args.kbatch = kbatch; args.k_batch = kbatch;
args.M = M; args.M = M;
args.N = N; args.N = N;
args.K = K; args.K = K;
......
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