cc3c29a81a
* v3.6 * update changelog * update readme * fix typo * fixing typos * hopper gemm with weight prefetch --------- Co-authored-by: yuzhai <yuzhai@nvidia.com> Co-authored-by: Haicheng Wu <haichengw@nvidia.com>
446 lines
16 KiB
Plaintext
446 lines
16 KiB
Plaintext
/***************************************************************************************************
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* Copyright (c) 2023 - 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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* SPDX-License-Identifier: BSD-3-Clause
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions are met:
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*
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* 1. Redistributions of source code must retain the above copyright notice, this
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* list of conditions and the following disclaimer.
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*
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* 2. Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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* 3. Neither the name of the copyright holder nor the names of its
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* contributors may be used to endorse or promote products derived from
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* this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*
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**************************************************************************************************/
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#include "cutlass_unit_test.h"
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#include <cute/tensor.hpp>
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#include <cute/swizzle.hpp> // cute::Swizzle
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#include <cute/swizzle_layout.hpp> // cute::compose(cute::Swizzle)
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#include "../cooperative_gemm_common.hpp"
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using namespace cute;
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TEST(SM80_CuTe_Ampere, CooperativeGemm1_Half_MMA) {
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using value_type = cutlass::half_t;
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constexpr uint32_t m = 64;
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constexpr uint32_t n = 64;
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constexpr uint32_t k = 64;
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constexpr uint32_t thread_block_size = 128;
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using tiled_mma_t =
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TiledMMA<
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MMA_Atom<SM80_16x8x8_F16F16F16F16_TN>,
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Layout<Shape<_2, _2, _1>>
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>;
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test_cooperative_gemm_col_major_layout<m, n, k, thread_block_size, tiled_mma_t, value_type>();
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}
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TEST(SM80_CuTe_Ampere, CooperativeGemm2_Double_MMA) {
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using value_type = double;
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constexpr uint32_t m = 64;
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constexpr uint32_t n = 64;
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constexpr uint32_t k = 64;
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constexpr uint32_t thread_block_size = 128;
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using tiled_mma_t =
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TiledMMA<
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MMA_Atom<SM80_8x8x4_F64F64F64F64_TN>,
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Layout<Shape<_2,_2,_1>>
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>;
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test_cooperative_gemm_col_major_layout<m, n, k, thread_block_size, tiled_mma_t, value_type>();
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}
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TEST(SM80_CuTe_Ampere, CooperativeGemm3_Half_MMA_CustomSmemLayouts) {
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using value_type = cutlass::half_t;
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constexpr uint32_t m = 128;
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constexpr uint32_t n = 128;
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constexpr uint32_t k = 128;
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constexpr uint32_t thread_block_size = 128;
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using tiled_mma_t =
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TiledMMA<
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MMA_Atom<SM80_16x8x16_F16F16F16F16_TN>,
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Layout<Shape<_2, _2, _1>>, // 2x2x1 thread group
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Tile<_32, _32, _16> // 32x32x16 MMA for LDSM, 1x2x1 value group`
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>;
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using smem_a_atom_layout_t = Layout<Shape<_64, _8>, Stride< _1,_64>>;
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using smem_b_atom_layout_t = Layout<Shape< _8,_32>, Stride<_32, _1>>;
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using smem_c_atom_layout_t = decltype(make_layout(make_shape(Int<m>{}, Int<n>{})));
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test_cooperative_gemm_col_major_layout<smem_a_atom_layout_t,
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smem_b_atom_layout_t,
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smem_c_atom_layout_t,
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m,
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n,
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k,
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thread_block_size,
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tiled_mma_t,
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128,
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value_type,
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value_type,
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value_type>();
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}
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TEST(SM80_CuTe_Ampere, CooperativeGemm4_Half_MMA_SwizzledSmemLayouts) {
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using value_type = cutlass::half_t;
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constexpr uint32_t m = 128;
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constexpr uint32_t n = 128;
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constexpr uint32_t k = 128;
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constexpr uint32_t thread_block_size = 128;
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using tiled_mma_t =
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TiledMMA<
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MMA_Atom<SM80_16x8x16_F16F16F16F16_TN>,
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Layout<Shape<_2, _2, _1>>, // 2x2x1 thread group
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Tile<_32, _32, _16> // 32x32x16 MMA for LDSM, 1x2x1 value group`
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>;
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// RowMajor
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using smem_rowmajor_atom_layout_t = decltype(
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composition(Swizzle<3,3,3>{},
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Layout<Shape < _8,_64>,
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Stride<_64, _1>>{}));
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// ColMajor
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using smem_colmajor_atom_layout_t = decltype(
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composition(Swizzle<3,3,3>{},
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Layout<Shape <_64, _8>,
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Stride< _1,_64>>{}));
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using smem_a_atom_layout_t = smem_rowmajor_atom_layout_t;
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using smem_b_atom_layout_t = smem_colmajor_atom_layout_t;
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using smem_c_atom_layout_t = decltype(make_layout(make_shape(Int<m>{}, Int<n>{}), GenRowMajor{}));
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using gmem_a_layout_t = decltype(make_layout(make_shape(Int<m> {}, Int<k> {}), GenRowMajor{}));
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using gmem_b_layout_t = decltype(make_layout(make_shape(Int<n> {}, Int<k> {}), GenColMajor{}));
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using gmem_c_layout_t = decltype(make_layout(make_shape(Int<m> {}, Int<n> {}), GenRowMajor{}));
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using smem_a_atom_layout_t = smem_a_atom_layout_t;
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using smem_a_layout_t = decltype(tile_to_shape(
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smem_a_atom_layout_t{},
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make_shape(shape<0>(gmem_a_layout_t{}), shape<1>(gmem_a_layout_t{})))
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);
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using smem_b_atom_layout_t = smem_b_atom_layout_t;
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using smem_b_layout_t = decltype(tile_to_shape(
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smem_b_atom_layout_t{},
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make_shape(shape<0>(gmem_b_layout_t{}), shape<1>(gmem_b_layout_t{})))
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);
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using smem_c_atom_layout_t = smem_c_atom_layout_t;
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using smem_c_layout_t = decltype(tile_to_shape(
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smem_c_atom_layout_t{},
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make_shape(shape<0>(gmem_c_layout_t{}), shape<1>(gmem_c_layout_t{})))
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);
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test_cooperative_gemm<gmem_a_layout_t,
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gmem_b_layout_t,
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gmem_c_layout_t,
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smem_a_layout_t,
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smem_b_layout_t,
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smem_c_layout_t,
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SM75_U32x4_LDSM_N, // A
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SM75_U16x8_LDSM_T, // B
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AutoVectorizingCopyWithAssumedAlignment<128>, // C
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thread_block_size,
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tiled_mma_t,
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128,
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value_type,
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value_type,
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value_type>();
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}
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TEST(SM80_CuTe_Ampere, CooperativeGemm5_Double_MMA_SwizzledSmemLayouts) {
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using value_type = double;
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constexpr uint32_t m = 128;
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constexpr uint32_t n = 64;
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constexpr uint32_t k = 16;
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constexpr uint32_t thread_block_size = 128;
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using tiled_mma_t =
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TiledMMA<MMA_Atom<SM80_8x8x4_F64F64F64F64_TN>, // Atom
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Layout<Shape<_2, _2, _1>>, // Atom layout
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Tile<Layout<Shape<_16, _2>, Stride<_2, _1>>, // 32x32x4 MMA with perm for load vectorization
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Layout<Shape<_16, _2>, Stride<_2, _1>>,
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Underscore>>;
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using smem_a_atom_layout_t = decltype(
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composition(Swizzle<2,2,2>{},
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Layout<Shape <_16, _4>,
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Stride< _1,_16>>{})); // M, K
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using smem_b_atom_layout_t = decltype(
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composition(Swizzle<2,2,2>{},
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Layout<Shape <_16, _4>,
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Stride< _1,_16>>{})); // N, K
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using smem_c_atom_layout_t = decltype(make_layout(make_shape(Int<m>{}, Int<n>{}), GenRowMajor{}));
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using gmem_a_layout_t = decltype(make_layout(make_shape(Int<m> {}, Int<k> {}), GenRowMajor{}));
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using gmem_b_layout_t = decltype(make_layout(make_shape(Int<n> {}, Int<k> {}), GenColMajor{}));
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using gmem_c_layout_t = decltype(make_layout(make_shape(Int<m> {}, Int<n> {}), GenRowMajor{}));
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using smem_a_atom_layout_t = smem_a_atom_layout_t;
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using smem_a_layout_t = decltype(tile_to_shape(
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smem_a_atom_layout_t{},
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make_shape(shape<0>(gmem_a_layout_t{}), shape<1>(gmem_a_layout_t{})))
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);
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using smem_b_atom_layout_t = smem_b_atom_layout_t;
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using smem_b_layout_t = decltype(tile_to_shape(
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smem_b_atom_layout_t{},
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make_shape(shape<0>(gmem_b_layout_t{}), shape<1>(gmem_b_layout_t{})))
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);
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using smem_c_atom_layout_t = smem_c_atom_layout_t;
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using smem_c_layout_t = decltype(tile_to_shape(
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smem_c_atom_layout_t{},
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make_shape(shape<0>(gmem_c_layout_t{}), shape<1>(gmem_c_layout_t{})))
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);
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test_cooperative_gemm<gmem_a_layout_t,
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gmem_b_layout_t,
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gmem_c_layout_t,
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smem_a_layout_t,
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smem_b_layout_t,
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smem_c_layout_t,
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AutoVectorizingCopyWithAssumedAlignment<128>, // A
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AutoVectorizingCopyWithAssumedAlignment<128>, // B
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AutoVectorizingCopyWithAssumedAlignment<128>, // C
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thread_block_size,
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tiled_mma_t,
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128,
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value_type,
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value_type,
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value_type>();
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}
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TEST(SM80_CuTe_Ampere, CooperativeGemm6_MixedPrecisionFP16FP32_MMA) {
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using TA = cutlass::half_t;
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using TB = cutlass::half_t;
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using TC = float;
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constexpr uint32_t m = 64;
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constexpr uint32_t n = 64;
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constexpr uint32_t k = 64;
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constexpr uint32_t thread_block_size = 128;
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using tiled_mma_t =
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TiledMMA<
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MMA_Atom<SM80_16x8x8_F32F16F16F32_TN>,
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Layout<Shape<_2, _2, _1>>
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>;
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test_cooperative_gemm_col_major_layout<m, n, k, thread_block_size, tiled_mma_t, 128, TA, TB, TC>();
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}
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TEST(SM80_CuTe_Ampere, CooperativeGemm7_MixedPrecisionBF16FP32_MMA) {
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using TA = cutlass::bfloat16_t;
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using TB = cutlass::bfloat16_t;
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using TC = float;
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constexpr uint32_t m = 64;
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constexpr uint32_t n = 64;
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constexpr uint32_t k = 64;
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constexpr uint32_t thread_block_size = 128;
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using tiled_mma_t =
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TiledMMA<
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MMA_Atom<SM80_16x8x8_F32BF16BF16F32_TN>,
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Layout<Shape<_2, _2, _1>>
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>;
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test_cooperative_gemm_col_major_layout<m, n, k, thread_block_size, tiled_mma_t, 128, TA, TB, TC>();
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}
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TEST(SM80_CuTe_Ampere, CooperativeGemm8_MixedPrecisionTF32FP32_MMA) {
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using TA = cutlass::tfloat32_t;
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using TB = cutlass::tfloat32_t;
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using TC = float;
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constexpr uint32_t m = 64;
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constexpr uint32_t n = 64;
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constexpr uint32_t k = 64;
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constexpr uint32_t thread_block_size = 128;
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using tiled_mma_t =
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TiledMMA<
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MMA_Atom<SM80_16x8x8_F32TF32TF32F32_TN>,
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Layout<Shape<_2, _2, _1>>
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>;
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test_cooperative_gemm_col_major_layout<m, n, k, thread_block_size, tiled_mma_t, 128, TA, TB, TC>();
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}
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TEST(SM80_CuTe_Ampere, CooperativeGemm9_C64C64C64_MMA) {
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using TA = cutlass::complex<double>;
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using TB = cutlass::complex<double>;
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using TC = cutlass::complex<double>;
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constexpr uint32_t thread_block_size = 256;
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constexpr int MaxVecBits = 128;
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using tiled_mma_t =
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TiledMMA<
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MMA_Atom<SM80_8x8x4_C64C64C64C64_TN>,
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Layout<Shape<_4, _4, _1>, Stride<_1, _4, _0>>,
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Tile<Underscore, Underscore, Underscore>
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>;
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using ALayout = Layout<Shape<Int<13>,Int<35>>, Stride<Int<44>, Int<1> >>;
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using BLayout = Layout<Shape< Int<7>, Int<35>>, Stride<Int<44>, Int<1> >>;
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using CLayout = Layout<Shape<Int<13>, Int<7>>, Stride< Int<1>, Int<30>>>;
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test_cooperative_gemm<ALayout,
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BLayout,
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CLayout,
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ALayout,
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BLayout,
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CLayout,
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AutoVectorizingCopyWithAssumedAlignment<MaxVecBits>, // A
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AutoVectorizingCopyWithAssumedAlignment<MaxVecBits>, // B
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AutoVectorizingCopyWithAssumedAlignment<MaxVecBits>, // C
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thread_block_size,
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tiled_mma_t,
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MaxVecBits,
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TA,
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TB,
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TC>();
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}
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TEST(SM80_CuTe_Ampere, CooperativeGemm10_F16F64F16_FMA) {
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using TA = cutlass::half_t;
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using TB = double;
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using TC = cutlass::half_t;
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constexpr uint32_t thread_block_size = 256;
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constexpr int MaxVecBits = 128;
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using tiled_mma_t =
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TiledMMA<
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MMA_Atom<UniversalFMA<half_t, half_t, double, half_t>>,
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Layout<Shape<_16, _16, _1>, Stride<_1, _16, _0>>,
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Tile<Underscore, Underscore, Underscore>
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>;
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using ALayout = Layout<Shape<Int<64>,Int<64>>, Stride<Int<64>, Int< 1>>>;
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using BLayout = Layout<Shape<Int<64>,Int<64>>, Stride<Int< 1>, Int<64>>>;
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using CLayout = Layout<Shape<Int<64>,Int<64>>, Stride<Int< 1>, Int<64>>>;
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test_cooperative_gemm<ALayout,
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BLayout,
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CLayout,
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ALayout,
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BLayout,
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CLayout,
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AutoVectorizingCopyWithAssumedAlignment<MaxVecBits>, // A
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AutoVectorizingCopyWithAssumedAlignment<MaxVecBits>, // B
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AutoVectorizingCopyWithAssumedAlignment<MaxVecBits>, // C
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thread_block_size,
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tiled_mma_t,
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MaxVecBits,
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TA,
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TB,
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TC>();
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}
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TEST(SM80_CuTe_Ampere, CooperativeGemmComposedStride) {
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using T = cute::half_t;
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constexpr uint32_t thread_block_size = 128;
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constexpr int MaxVecBits = 16;
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using tiled_mma_t =
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TiledMMA<
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MMA_Atom<SM80_16x8x16_F16F16F16F16_TN>,
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Layout<Shape<_2, _2, _1>, Stride<_1, _2, _0>>,
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Tile<Underscore, Underscore, Underscore>
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>;
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using swizzle = cute::Swizzle<3, 3, 3>;
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using offset = cute::_0;
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using atom_tile_right = decltype(cute::make_layout(cute::Shape<cute::_8, cute::_64>{}, cute::LayoutRight{}));
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using FP16AtomLayoutRight = decltype(cute::composition(swizzle{}, offset{}, atom_tile_right{}));
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using shape = cute::Shape<cute::Int<128>, cute::Int<128>>;
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using global_a_layout = decltype(cute::make_layout(shape{}, cute::LayoutRight{}));
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using global_b_layout = decltype(cute::make_layout(shape{}, cute::LayoutLeft{}));
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using global_c_layout = decltype(cute::make_layout(shape{}, cute::LayoutRight{}));
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// This is for A row major, B col major according to CUTLASS default configs
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using ALayout = decltype(cute::tile_to_shape(FP16AtomLayoutRight{}, global_a_layout{}));
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using BLayout = decltype(cute::tile_to_shape(FP16AtomLayoutRight{}, global_b_layout{}));
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using CLayout = global_c_layout;
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test_cooperative_gemm<ALayout,
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BLayout,
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CLayout,
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ALayout,
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BLayout,
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CLayout,
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AutoVectorizingCopyWithAssumedAlignment<MaxVecBits>, // A
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AutoVectorizingCopyWithAssumedAlignment<MaxVecBits>, // B
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AutoVectorizingCopyWithAssumedAlignment<MaxVecBits>, // C
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thread_block_size,
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tiled_mma_t,
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MaxVecBits,
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T,
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T,
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T>();
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}
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TEST(SM89_CuTe_Ampere, CooperativeGemm8_MixedPrecisionTF32FP32_Transform) {
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using TA = cutlass::tfloat32_t;
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using TB = cutlass::tfloat32_t;
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using TC = float;
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constexpr uint32_t m = 9;
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constexpr uint32_t n = 9;
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constexpr uint32_t k = 9;
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constexpr uint32_t thread_block_size = 64;
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using tiled_mma_t =
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TiledMMA<
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MMA_Atom<SM80_16x8x8_F32TF32TF32F32_TN>,
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Layout<Shape<_1, _2, _1>>
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>;
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test_cooperative_gemm_col_major_layout<m, n, k, thread_block_size, tiled_mma_t, 16, TA, TB, TC>(cute::negate{}, cute::negate{}, cute::negate{}, cute::negate{});
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}
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