b78588d163
* CUTLASS 3.7 * clean up changelog --------- Co-authored-by: yuzhai <yuzhai@nvidia.com> Co-authored-by: Haicheng Wu <haichengw@nvidia.com>
363 lines
12 KiB
Plaintext
363 lines
12 KiB
Plaintext
/***************************************************************************************************
|
|
* Copyright (c) 2023 - 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
|
|
* SPDX-License-Identifier: BSD-3-Clause
|
|
*
|
|
* Redistribution and use in source and binary forms, with or without
|
|
* modification, are permitted provided that the following conditions are met:
|
|
*
|
|
* 1. Redistributions of source code must retain the above copyright notice, this
|
|
* list of conditions and the following disclaimer.
|
|
*
|
|
* 2. Redistributions in binary form must reproduce the above copyright notice,
|
|
* this list of conditions and the following disclaimer in the documentation
|
|
* and/or other materials provided with the distribution.
|
|
*
|
|
* 3. Neither the name of the copyright holder nor the names of its
|
|
* contributors may be used to endorse or promote products derived from
|
|
* this software without specific prior written permission.
|
|
*
|
|
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
|
|
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
|
|
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
|
|
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
|
|
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
|
|
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
|
|
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
|
|
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
|
|
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
|
|
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
|
*
|
|
**************************************************************************************************/
|
|
|
|
#include "cutlass_unit_test.h"
|
|
|
|
#include <cute/tensor.hpp>
|
|
#include <cute/swizzle.hpp> // cute::Swizzle
|
|
#include <cute/swizzle_layout.hpp> // cute::compose(cute::Swizzle)
|
|
|
|
#include "../cooperative_gemm_common.hpp"
|
|
|
|
using namespace cute;
|
|
|
|
TEST(SM70_CuTe_Volta, CooperativeGemm1_FloatFMA) {
|
|
|
|
constexpr uint32_t thread_block_size = 128;
|
|
using value_type = float;
|
|
|
|
auto shape_mnk = make_shape(_64{}, _32{}, _16{});
|
|
auto tiled_mma =
|
|
TiledMMA<
|
|
MMA_Atom<UniversalFMA<value_type, value_type, value_type, value_type>>,
|
|
Layout<Shape<_16, _8, _1>>
|
|
>{};
|
|
|
|
test_cooperative_gemm_col_major_layout<thread_block_size, value_type>(shape_mnk, tiled_mma);
|
|
}
|
|
|
|
TEST(SM70_CuTe_Volta, CooperativeGemm1_FloatFMA_Predication) {
|
|
|
|
constexpr uint32_t thread_block_size = 128;
|
|
using value_type = float;
|
|
|
|
auto shape_mnk = make_shape(C<88>{}, C<20>{}, C<12>{});
|
|
auto tiled_mma =
|
|
TiledMMA<
|
|
MMA_Atom<UniversalFMA<value_type, value_type, value_type, value_type>>,
|
|
Layout<Shape<_2, _64, _1>>
|
|
>{};
|
|
|
|
test_cooperative_gemm_col_major_layout<thread_block_size, value_type>(shape_mnk, tiled_mma);
|
|
}
|
|
|
|
TEST(SM70_CuTe_Volta, CooperativeGemm1_FloatFMA_Predication2) {
|
|
|
|
constexpr uint32_t thread_block_size = 128;
|
|
using value_type = float;
|
|
|
|
auto shape_mnk = make_shape(C<88>{}, C<36>{}, C<24>{});
|
|
auto tiled_mma =
|
|
TiledMMA<
|
|
MMA_Atom<UniversalFMA<value_type, value_type, value_type, value_type>>,
|
|
Layout<Shape<_4, _32, _1>>
|
|
>{};
|
|
|
|
test_cooperative_gemm_col_major_layout<thread_block_size, value_type>(shape_mnk, tiled_mma);
|
|
}
|
|
|
|
TEST(SM70_CuTe_Volta, CooperativeGemm1_FloatFMA_Predication3) {
|
|
constexpr uint32_t thread_block_size = 128;
|
|
using value_type = float;
|
|
|
|
auto shape_mnk = make_shape(C<67>{}, C<13>{}, C<11>{});
|
|
auto tiled_mma =
|
|
TiledMMA<
|
|
MMA_Atom<UniversalFMA<value_type, value_type, value_type, value_type>>,
|
|
Layout<Shape<_1, _128, _1>>
|
|
>{};
|
|
|
|
test_cooperative_gemm_col_major_layout<thread_block_size, value_type>(shape_mnk, tiled_mma);
|
|
}
|
|
|
|
TEST(SM70_CuTe_Volta, CooperativeGemm2_DoubleFMA) {
|
|
constexpr uint32_t thread_block_size = 128;
|
|
using value_type = double;
|
|
|
|
auto shape_mnk = make_shape(C<16>{}, C<32>{}, C<32>{});
|
|
auto tiled_mma =
|
|
TiledMMA<
|
|
MMA_Atom<UniversalFMA<value_type, value_type, value_type, value_type>>,
|
|
Layout<Shape<_16, _8, _1>>
|
|
>{};
|
|
|
|
test_cooperative_gemm_col_major_layout<thread_block_size, value_type>(shape_mnk, tiled_mma);
|
|
}
|
|
|
|
TEST(SM70_CuTe_Volta, CooperativeGemm3_Float_FMA_CustomPermutationMNK) {
|
|
|
|
constexpr uint32_t thread_block_size = 256;
|
|
using value_type = float;
|
|
|
|
auto shape_mnk = make_shape(_32{}, _32{}, _32{});
|
|
auto tiled_mma = TiledMMA<
|
|
MMA_Atom<
|
|
UniversalFMA<value_type, value_type, value_type, value_type>
|
|
>,
|
|
Layout<
|
|
Shape<_16, _16, _1>
|
|
>,
|
|
Tile<
|
|
Layout<
|
|
Shape<_16,_2>, Stride<_2,_1>
|
|
>, // 32x32x1 MMA with perm for load vectorization
|
|
Layout<
|
|
Shape<_16,_2>, Stride<_2,_1>
|
|
>,
|
|
Underscore
|
|
>
|
|
>{};
|
|
|
|
test_cooperative_gemm_col_major_layout<thread_block_size, value_type>(shape_mnk, tiled_mma);
|
|
}
|
|
|
|
TEST(SM70_CuTe_Volta, CooperativeGemm4_Half_MMA) {
|
|
constexpr uint32_t thread_block_size = 128;
|
|
using value_type = cutlass::half_t;
|
|
|
|
auto shape_mnk = make_shape(_32{}, _32{}, _32{});
|
|
auto tiled_mma = TiledMMA<
|
|
MMA_Atom<SM70_8x8x4_F16F16F16F16_TN>,
|
|
Layout<Shape<_4, _4, _1>>
|
|
>{};
|
|
|
|
auto smem_a_atom_layout = typename decltype(tiled_mma)::AtomLayoutB_TV{};
|
|
auto smem_b_atom_layout = typename decltype(tiled_mma)::AtomLayoutA_TV{};
|
|
auto smem_c_atom_layout = make_layout(select<0, 1>(shape_mnk));
|
|
|
|
test_cooperative_gemm_col_major_layout<thread_block_size,
|
|
value_type>
|
|
(smem_a_atom_layout,
|
|
smem_b_atom_layout,
|
|
smem_c_atom_layout,
|
|
shape_mnk,
|
|
tiled_mma);
|
|
}
|
|
|
|
TEST(SM70_CuTe_Volta, CooperativeGemm5_Half_MMA) {
|
|
|
|
constexpr uint32_t thread_block_size = 128;
|
|
constexpr uint32_t max_vec_bits = 128;
|
|
using value_type = cutlass::half_t;
|
|
|
|
auto shape_mnk = make_shape(_32{}, _32{}, _32{});
|
|
auto tiled_mma = TiledMMA<
|
|
MMA_Atom<SM70_8x8x4_F16F16F16F16_TN>,
|
|
Layout<Shape<_4, _4, _1>>
|
|
>{};
|
|
|
|
auto gmem_a_layout = make_layout(select<0, 2>(shape_mnk));
|
|
auto gmem_b_layout = make_layout(select<1, 2>(shape_mnk), GenColMajor{});
|
|
auto gmem_c_layout = make_layout(select<0, 1>(shape_mnk));
|
|
|
|
auto smem_a_layout = make_layout(select<0, 2>(shape_mnk));
|
|
auto smem_b_layout = make_layout(select<1, 2>(shape_mnk), GenColMajor{});
|
|
auto smem_c_layout = make_layout(select<0, 1>(shape_mnk));
|
|
|
|
test_cooperative_gemm<thread_block_size,
|
|
max_vec_bits,
|
|
value_type,
|
|
value_type,
|
|
value_type>
|
|
(gmem_a_layout,
|
|
gmem_b_layout,
|
|
gmem_c_layout,
|
|
smem_a_layout,
|
|
smem_b_layout,
|
|
smem_c_layout,
|
|
tiled_mma);
|
|
}
|
|
|
|
TEST(SM70_CuTe_Volta, CooperativeGemm5_Half_MMA_Predicated) {
|
|
|
|
constexpr uint32_t thread_block_size = 128;
|
|
constexpr uint32_t max_vec_bits = 16;
|
|
using value_type = cutlass::half_t;
|
|
|
|
auto shape_mnk = make_shape(C<31>{}, C<27>{}, C<17>{});
|
|
auto tiled_mma = TiledMMA<
|
|
MMA_Atom<SM70_8x8x4_F16F16F16F16_TN>,
|
|
Layout<Shape<_4, _4, _1>>
|
|
>{};
|
|
|
|
auto gmem_a_layout = make_layout(select<0, 2>(shape_mnk));
|
|
auto gmem_b_layout = make_layout(select<1, 2>(shape_mnk), GenColMajor{});
|
|
auto gmem_c_layout = make_layout(select<0, 1>(shape_mnk));
|
|
|
|
auto smem_a_layout = make_layout(select<0, 2>(shape_mnk));
|
|
auto smem_b_layout = make_layout(select<1, 2>(shape_mnk), GenColMajor{});
|
|
auto smem_c_layout = make_layout(select<0, 1>(shape_mnk));
|
|
|
|
test_cooperative_gemm<thread_block_size,
|
|
max_vec_bits,
|
|
value_type,
|
|
value_type,
|
|
value_type>
|
|
(gmem_a_layout,
|
|
gmem_b_layout,
|
|
gmem_c_layout,
|
|
smem_a_layout,
|
|
smem_b_layout,
|
|
smem_c_layout,
|
|
tiled_mma);
|
|
}
|
|
|
|
TEST(SM70_CuTe_Volta, CooperativeGemm6_Half_MAA_SwizzledSmemLayouts) {
|
|
|
|
constexpr uint32_t thread_block_size = 128;
|
|
constexpr uint32_t max_vec_bits = 128;
|
|
using value_type = cutlass::half_t;
|
|
|
|
auto shape_mnk = make_shape(_128{}, _128{}, _64{});
|
|
auto tiled_mma = TiledMMA<
|
|
MMA_Atom<SM70_8x8x4_F16F16F16F16_TN>,
|
|
Layout<Shape<_4, _4, _1>>
|
|
>{};
|
|
|
|
auto smem_a_atom_layout = composition(Swizzle<3,3,3>{}, Layout<Shape < _8,_64>, Stride<_64, _1>>{});
|
|
auto smem_b_atom_layout = composition(Swizzle<3,3,3>{}, Layout<Shape <_64, _8>, Stride< _1,_64>>{});
|
|
auto smem_c_atom_layout = make_layout(select<0, 1>(shape_mnk), GenRowMajor{});
|
|
|
|
auto gmem_a_layout = make_layout(select<0, 2>(shape_mnk), GenRowMajor{});
|
|
auto gmem_b_layout = make_layout(select<1, 2>(shape_mnk), GenColMajor{});
|
|
auto gmem_c_layout = make_layout(select<0, 1>(shape_mnk), GenRowMajor{});
|
|
|
|
auto smem_a_layout = tile_to_shape(
|
|
smem_a_atom_layout,
|
|
make_shape(shape<0>(gmem_a_layout), shape<1>(gmem_a_layout)));
|
|
|
|
auto smem_b_layout = tile_to_shape(
|
|
smem_b_atom_layout,
|
|
make_shape(shape<0>(gmem_b_layout), shape<1>(gmem_b_layout)));
|
|
|
|
auto smem_c_layout = tile_to_shape(
|
|
smem_c_atom_layout,
|
|
make_shape(shape<0>(gmem_c_layout), shape<1>(gmem_c_layout)));
|
|
|
|
test_cooperative_gemm<thread_block_size,
|
|
max_vec_bits,
|
|
value_type,
|
|
value_type,
|
|
value_type>
|
|
(gmem_a_layout,
|
|
gmem_b_layout,
|
|
gmem_c_layout,
|
|
smem_a_layout,
|
|
smem_b_layout,
|
|
smem_c_layout,
|
|
tiled_mma);
|
|
}
|
|
|
|
TEST(SM70_CuTe_Volta, CooperativeGemm7_TransformNegate_FMA) {
|
|
constexpr uint32_t thread_block_size = 128;
|
|
constexpr uint32_t max_vec_bits = 64;
|
|
using TA = float;
|
|
using TB = float;
|
|
using TC = double;
|
|
|
|
auto shape_mnk = make_shape(_32{}, _32{}, _32{});
|
|
auto tiled_mma = TiledMMA<
|
|
MMA_Atom<UniversalFMA<TC, TA, TB, TC>>,
|
|
Layout<Shape<_16, _8, _1>>
|
|
>{};
|
|
|
|
auto aload = cute::negate {};
|
|
auto bload = cute::negate {};
|
|
auto cload = cute::negate {};
|
|
auto cstore = cute::negate {};
|
|
|
|
test_cooperative_gemm_col_major_layout<thread_block_size, max_vec_bits, TA, TB, TC>(
|
|
shape_mnk, tiled_mma, aload, bload, cload, cstore);
|
|
}
|
|
|
|
TEST(SM70_CuTe_Volta, CooperativeGemm7_TransformNegate_MMA) {
|
|
|
|
constexpr uint32_t thread_block_size = 128;
|
|
using value_type = cutlass::half_t;
|
|
|
|
auto shape_mnk = make_shape(_32{}, _32{}, _32{});
|
|
auto tiled_mma = TiledMMA<
|
|
MMA_Atom<SM70_8x8x4_F16F16F16F16_TN>,
|
|
Layout<Shape<_4, _4, _1>>
|
|
>{};
|
|
|
|
auto aload = cute::negate {};
|
|
auto bload = cute::negate {};
|
|
auto cload = cute::negate {};
|
|
auto cstore = cute::negate {};
|
|
|
|
test_cooperative_gemm_col_major_layout<thread_block_size, value_type>(
|
|
shape_mnk, tiled_mma, aload, bload, cload, cstore);
|
|
}
|
|
|
|
template<class ConstantType>
|
|
struct increment_by_x {
|
|
ConstantType x;
|
|
|
|
template <class T>
|
|
CUTE_HOST_DEVICE constexpr
|
|
T operator()(const T& arg) const {
|
|
return arg + x;
|
|
}
|
|
};
|
|
|
|
template<class From, class To>
|
|
struct convert_to {
|
|
CUTE_HOST_DEVICE constexpr
|
|
To operator()(const From& arg) const {
|
|
return static_cast<To>(arg);
|
|
}
|
|
};
|
|
|
|
TEST(SM70_CuTe_Volta, CooperativeGemm7_TransformCustomOp_FMA) {
|
|
|
|
constexpr uint32_t thread_block_size = 128;
|
|
constexpr uint32_t max_vec_bits = 64;
|
|
|
|
using TA = float;
|
|
using TB = float;
|
|
using TC = double;
|
|
|
|
auto shape_mnk = make_shape(_32{}, _32{}, _32{});
|
|
auto tiled_mma = TiledMMA<
|
|
MMA_Atom<UniversalFMA<TC, TA, TB, TC>>,
|
|
Layout<Shape<_16, _8, _1>>
|
|
>{};
|
|
|
|
auto aload = increment_by_x<float>{1.111f};
|
|
auto bload = convert_to<float, double> {};
|
|
auto cload = cute::negate {};
|
|
auto cstore = cute::negate {};
|
|
|
|
test_cooperative_gemm_col_major_layout<thread_block_size, max_vec_bits, TA, TB, TC>(
|
|
shape_mnk, tiled_mma, aload, bload, cload, cstore);
|
|
}
|