Files
composable_kernel/test/grouped_gemm/test_grouped_gemm_interface_xdl.cpp
Illia Silin ae57e5938e Split the instances by architecture. (#1223)
* parse examples inside the add_example_executable function

* fix the example 64 cmake file

* add xdl flag to the gemm_bias_softmax_gemm_permute example

* add filtering of tests based on architecture type

* enable test_grouped_gemm for gfx9 only

* enable test_transpose only for gfx9

* only linnk test_transpose if it gets built

* split the gemm instances by architectures

* split gemm_bilinear,grouped_conv_bwd_weight instances by targets

* split instances by architecture

* split grouped_conv instances by architecture

* fix clang format

* fix the if-else logic in group_conv headers

* small fix for grouped convolution instances

* fix the grouped conv bwd weight dl instances

* fix client examples

* only enable client examples 3 and 4 on gfx9

* set the gfx9 macro

* make sure the architecture macros are set by cmake

* use separate set of xdl/wmma flags for host code

* sinmplify the main cmake file

* add conv_fwd_bf8 instance declaration
2024-04-02 09:42:17 -07:00

207 lines
7.9 KiB
C++

// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#include <stdexcept>
#include <vector>
#include "gtest/gtest.h"
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "test_grouped_gemm_util.hpp"
class TestGGemmSplitKInterface_MKNKMN : public ::testing::Test
{
protected:
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
using ALayout = Row;
using BLayout = Col;
using ELayout = Row;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
template <ck::tensor_operation::device::GemmSpecialization GemmSpec,
ck::index_t KPerBlock,
ck::index_t K1,
ck::index_t ABlockTransferSrcScalarPerVector,
ck::index_t BBlockTransferSrcScalarPerVector,
ck::index_t CDEBlockTransferScalarPerVector_NPerBlock>
using GGemmInstance =
ck::test::DeviceGroupedGemmSplitkInstanceWrapper<ALayout,
BLayout,
ELayout,
GemmSpec,
KPerBlock,
K1,
ABlockTransferSrcScalarPerVector,
BBlockTransferSrcScalarPerVector,
CDEBlockTransferScalarPerVector_NPerBlock>;
using DefaultGGemmInstance = GGemmInstance<GemmDefault, 32, 8, 4, 8, 8>;
};
TEST_F(TestGGemmSplitKInterface_MKNKMN, TileSize)
{
std::vector<int> Ms{128, 256, 188, 512};
constexpr int N = 256;
constexpr int K = 128;
std::vector<int> Ns(Ms.size(), N);
std::vector<int> Ks(Ms.size(), K);
std::vector<int> StrideAs(Ms.size(), K);
std::vector<int> StrideBs(Ms.size(), K);
std::vector<int> StrideCs(Ms.size(), N);
// M % MPerBlock
EXPECT_FALSE(DefaultGGemmInstance{}.IsSupported(Ms, Ns, Ks, StrideAs, StrideBs, StrideCs));
Ms = std::vector<int>{256, 128, 128, 512};
Ns = std::vector<int>{256, 177, 128, 512};
// N % NPerBlock
EXPECT_FALSE(DefaultGGemmInstance{}.IsSupported(Ms, Ns, Ks, StrideAs, StrideBs, StrideCs));
}
TEST_F(TestGGemmSplitKInterface_MKNKMN, VectorLoadWidth)
{
static constexpr auto GemmMNKPadding =
ck::tensor_operation::device::GemmSpecialization::MNKPadding;
using PaddedGGemmInstance = GGemmInstance<GemmMNKPadding, 32, 8, 4, 8, 8>;
std::vector<int> Ms{128, 256, 256, 512};
constexpr int N = 256;
constexpr int K = 512;
std::vector<int> Ns(Ms.size(), N);
std::vector<int> Ks(Ms.size(), K);
std::vector<int> StrideAs(Ms.size(), K);
std::vector<int> StrideBs(Ms.size(), K);
std::vector<int> StrideCs(Ms.size(), N);
// K % ABlockTransferSrcScalarPerVector
Ks = std::vector<int>{256, 177, 128, 512};
EXPECT_FALSE(PaddedGGemmInstance{}.IsSupported(Ms, Ns, Ks, StrideAs, StrideBs, StrideCs));
Ks = std::vector<int>{256, 164, 128, 512};
// K % BBlockTransferSrcScalarPerVector
EXPECT_FALSE(PaddedGGemmInstance{}.IsSupported(Ms, Ns, Ks, StrideAs, StrideBs, StrideCs));
Ks = std::vector<int>(4, 128);
Ns = std::vector<int>{256, 127, 128, 512};
// N % CBlockTransferScalarPerVector_NWaveNPerXDL
EXPECT_FALSE(PaddedGGemmInstance{}.IsSupported(Ms, Ns, Ks, StrideAs, StrideBs, StrideCs));
}
TEST_F(TestGGemmSplitKInterface_MKNKMN, KLoops)
{
std::vector<int> Ms{128, 256, 256, 512};
constexpr int N = 256;
constexpr int K = 128;
constexpr int kbatch = 4;
std::vector<int> Ns(Ms.size(), N);
std::vector<int> Ks(Ms.size(), K);
std::vector<int> StrideAs(Ms.size(), K);
std::vector<int> StrideBs(Ms.size(), K);
std::vector<int> StrideCs(Ms.size(), N);
// kloops % 2
Ks = std::vector<int>{256, 512, 320, 768};
EXPECT_FALSE(
DefaultGGemmInstance{}.IsSupported(Ms, Ns, Ks, StrideAs, StrideBs, StrideCs, kbatch));
Ks = std::vector<int>{256, 512, 384, 768};
EXPECT_TRUE(
DefaultGGemmInstance{}.IsSupported(Ms, Ns, Ks, StrideAs, StrideBs, StrideCs, kbatch));
// Not all gemms have same value for main_k0_block_loop!
Ks = std::vector<int>{256, 512, 512, 512};
EXPECT_THROW(DefaultGGemmInstance{}.Run(Ms, Ns, Ks, StrideAs, StrideBs, StrideCs, kbatch),
std::runtime_error);
}
class TestGGemmSplitKInterface_KMKNNM : public ::testing::Test
{
protected:
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
using ALayout = Col;
using BLayout = Row;
using ELayout = Col;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
template <ck::tensor_operation::device::GemmSpecialization GemmSpec,
ck::index_t KPerBlock,
ck::index_t K1,
ck::index_t ABlockTransferSrcScalarPerVector,
ck::index_t BBlockTransferSrcScalarPerVector,
ck::index_t CDEBlockTransferScalarPerVector_NPerBlock>
using GGemmInstance =
ck::test::DeviceGroupedGemmSplitkInstanceWrapper<ALayout,
BLayout,
ELayout,
GemmSpec,
KPerBlock,
K1,
ABlockTransferSrcScalarPerVector,
BBlockTransferSrcScalarPerVector,
CDEBlockTransferScalarPerVector_NPerBlock>;
using DefaultGGemmInstance = GGemmInstance<GemmDefault, 32, 8, 4, 8, 4>;
};
TEST_F(TestGGemmSplitKInterface_KMKNNM, TileSize)
{
std::vector<int> Ms{128, 256, 188, 512};
constexpr int N = 256;
constexpr int K = 128;
std::vector<int> Ns(Ms.size(), N);
std::vector<int> Ks(Ms.size(), K);
std::vector<int> StrideAs(Ms.size(), K);
std::vector<int> StrideBs(Ms.size(), K);
std::vector<int> StrideCs(Ms.size(), N);
// M % MPerBlock
EXPECT_FALSE(DefaultGGemmInstance{}.IsSupported(Ms, Ns, Ks, StrideAs, StrideBs, StrideCs));
Ms = std::vector<int>{128, 256, 256, 512};
Ns = std::vector<int>{256, 177, 128, 512};
// N % NPerBlock
EXPECT_FALSE(DefaultGGemmInstance{}.IsSupported(Ms, Ns, Ks, StrideAs, StrideBs, StrideCs));
}
TEST_F(TestGGemmSplitKInterface_KMKNNM, VectorLoadWidth)
{
static constexpr auto GemmMNKPadding =
ck::tensor_operation::device::GemmSpecialization::MNKPadding;
using PaddedGGemmInstance = GGemmInstance<GemmMNKPadding, 32, 8, 2, 8, 4>;
std::vector<int> Ms{128, 256, 256, 512};
constexpr int N = 256;
constexpr int K = 512;
std::vector<int> Ns(Ms.size(), N);
std::vector<int> Ks(Ms.size(), K);
std::vector<int> StrideAs(Ms.size(), K);
std::vector<int> StrideBs(Ms.size(), K);
std::vector<int> StrideCs(Ms.size(), N);
// M % ABlockTransferSrcScalarPerVector
Ms = std::vector<int>{256, 177, 128, 512};
EXPECT_FALSE(PaddedGGemmInstance{}.IsSupported(Ms, Ns, Ks, StrideAs, StrideBs, StrideCs));
Ms = std::vector<int>{128, 256, 256, 512};
Ns = std::vector<int>{256, 164, 128, 512};
// N % BBlockTransferSrcScalarPerVector
EXPECT_FALSE(PaddedGGemmInstance{}.IsSupported(Ms, Ns, Ks, StrideAs, StrideBs, StrideCs));
Ns = std::vector<int>{128, 256, 256, 512};
Ms = std::vector<int>{256, 130, 128, 512};
// M % CBlockTransferScalarPerVector_NWaveNPerXDL
EXPECT_FALSE(PaddedGGemmInstance{}.IsSupported(Ms, Ns, Ks, StrideAs, StrideBs, StrideCs));
}