338 lines
12 KiB
Plaintext
338 lines
12 KiB
Plaintext
/***************************************************************************************************
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* Copyright (c) 2017 - 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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/*! \file
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\brief Unit tests for thread-level GEMM
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*/
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#include "cutlass/arch/wmma.h"
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#ifdef CUTLASS_ARCH_WMMA_SM75_ENABLED
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#include "mma_pipelined_testbed.h"
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#include "cutlass/gemm/threadblock/default_mma_core_wmma.h"
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/// All tests use double-buffered (kStages=2) mma pipeline for the gemm mainloop
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/// Test name format: SM[arch]_gemm_threadblock_wmma_tensor_op_[alayout]_[blayout]_[clayout]_[atype].[threadblock_shape]_[warp_shape]_[instruction_shape]
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/////////////////////////////////////////////////////////////////////////
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/// Integer (s8 and u8) WMMA threadblock level tests /////
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/////////////////////////////////////////////////////////////////////////
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#if defined(CUTLASS_ARCH_INTEGER_MATRIX_MULTIPLY_ENABLED)
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TEST(SM75_gemm_threadblock_wmma_tensor_op_row_col_row_s8, 64x64x32_64x64x32_16x16x16) {
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using ElementA = int8_t;
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using LayoutA = cutlass::layout::RowMajor;
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using ElementB = int8_t;
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using LayoutB = cutlass::layout::ColumnMajor;
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using ElementC = int32_t;
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using LayoutC = cutlass::layout::RowMajor;
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static const int kStages = 2;
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cutlass::gemm::GemmCoord problem_size(64, 64, 128);
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using ThreadblockShape = cutlass::gemm::GemmShape<64, 64, 32>;
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using WarpShape = cutlass::gemm::GemmShape<64, 64, 32>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 16, 16>;
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float alpha = 1.f;
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float beta = 0.0f;
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// Define the MmaCore components
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using MmaCore = typename cutlass::gemm::threadblock::DefaultMmaCore<
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ThreadblockShape, WarpShape, InstructionShape,
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ElementA, LayoutA,
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ElementB, LayoutB,
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ElementC, LayoutC,
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cutlass::arch::OpClassWmmaTensorOp, kStages>;
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dim3 grid(1, 1);
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dim3 block(32, 1, 1);
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test::gemm::threadblock::Testbed<MmaCore, kStages>(problem_size.m(), problem_size.n(),
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problem_size.k(), alpha, beta)
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.run(grid, block);
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}
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TEST(SM75_gemm_threadblock_wmma_tensor_op_row_col_row_s8, 64x64x64_64x64x64_16x16x16) {
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using ElementA = int8_t;
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using LayoutA = cutlass::layout::RowMajor;
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using ElementB = int8_t;
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using LayoutB = cutlass::layout::ColumnMajor;
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using ElementC = int32_t;
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using LayoutC = cutlass::layout::RowMajor;
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static const int kStages = 2;
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cutlass::gemm::GemmCoord problem_size(64, 64, 128);
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using ThreadblockShape = cutlass::gemm::GemmShape<64, 64, 64>;
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using WarpShape = cutlass::gemm::GemmShape<64, 64, 64>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 16, 16>;
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float alpha = 1.f;
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float beta = 0.0f;
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// Define the MmaCore components
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using MmaCore = typename cutlass::gemm::threadblock::DefaultMmaCore<
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ThreadblockShape, WarpShape, InstructionShape,
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ElementA, LayoutA,
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ElementB, LayoutB,
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ElementC, LayoutC,
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cutlass::arch::OpClassWmmaTensorOp, kStages>;
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dim3 grid(1, 1);
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dim3 block(32, 1, 1);
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test::gemm::threadblock::Testbed<MmaCore, kStages>(problem_size.m(), problem_size.n(),
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problem_size.k(), alpha, beta)
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.run(grid, block);
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}
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TEST(SM75_gemm_threadblock_wmma_tensor_op_col_row_row_s8, 64x64x32_64x64x32_16x16x16) {
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using ElementA = int8_t;
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using LayoutA = cutlass::layout::ColumnMajor;
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using ElementB = int8_t;
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using LayoutB = cutlass::layout::RowMajor;
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using ElementC = int32_t;
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using LayoutC = cutlass::layout::RowMajor;
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static const int kStages = 2;
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cutlass::gemm::GemmCoord problem_size(64, 64, 128);
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using ThreadblockShape = cutlass::gemm::GemmShape<64, 64, 32>;
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using WarpShape = cutlass::gemm::GemmShape<64, 64, 32>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 16, 16>;
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float alpha = 1.f;
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float beta = 0.0f;
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// Define the MmaCore components
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using MmaCore = typename cutlass::gemm::threadblock::DefaultMmaCore<
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ThreadblockShape, WarpShape, InstructionShape,
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ElementA, LayoutA,
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ElementB, LayoutB,
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ElementC, LayoutC,
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cutlass::arch::OpClassWmmaTensorOp, kStages>;
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dim3 grid(1, 1);
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dim3 block(32, 1, 1);
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test::gemm::threadblock::Testbed<MmaCore, kStages>(problem_size.m(), problem_size.n(),
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problem_size.k(), alpha, beta)
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.run(grid, block);
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}
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TEST(SM75_gemm_threadblock_wmma_tensor_op_col_row_row_s8, 64x64x64_64x64x64_16x16x16) {
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using ElementA = int8_t;
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using LayoutA = cutlass::layout::ColumnMajor;
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using ElementB = int8_t;
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using LayoutB = cutlass::layout::RowMajor;
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using ElementC = int32_t;
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using LayoutC = cutlass::layout::RowMajor;
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static const int kStages = 2;
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cutlass::gemm::GemmCoord problem_size(64, 64, 128);
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using ThreadblockShape = cutlass::gemm::GemmShape<64, 64, 64>;
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using WarpShape = cutlass::gemm::GemmShape<64, 64, 64>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 16, 16>;
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float alpha = 1.f;
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float beta = 0.0f;
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// Define the MmaCore components
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using MmaCore = typename cutlass::gemm::threadblock::DefaultMmaCore<
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ThreadblockShape, WarpShape, InstructionShape,
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ElementA, LayoutA,
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ElementB, LayoutB,
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ElementC, LayoutC,
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cutlass::arch::OpClassWmmaTensorOp, kStages>;
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dim3 grid(1, 1);
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dim3 block(32, 1, 1);
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test::gemm::threadblock::Testbed<MmaCore, kStages>(problem_size.m(), problem_size.n(),
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problem_size.k(), alpha, beta)
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.run(grid, block);
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}
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#endif //CUTLASS_ARCH_INTEGER_MATRIX_MULTIPLY_ENABLED
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////////////////////////////////////////////////////////////////////////
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/// SUBBYTE (s4 and b1) WMMA threadblock level tests ////
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///////////////////////////////////////////////////////////////////////
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#if defined(CUTLASS_SUBBYTE_INTEGER_MATRIX_MULTIPLY_ENABLED)
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TEST(SM75_gemm_threadblock_wmma_tensor_op_row_col_row_s4, 64x64x128_64x64x128_8x8x32) {
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using ElementA = cutlass::int4b_t;
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using LayoutA = cutlass::layout::RowMajor;
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using ElementB = cutlass::int4b_t;
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using LayoutB = cutlass::layout::ColumnMajor;
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using ElementC = int32_t;
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using LayoutC = cutlass::layout::RowMajor;
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static const int kStages = 2;
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cutlass::gemm::GemmCoord problem_size(64, 64, 128);
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using ThreadBlockShape = cutlass::gemm::GemmShape<64, 64, 128>;
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using WarpShape = cutlass::gemm::GemmShape<64, 64, 128>;
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using InstructionShape = cutlass::gemm::GemmShape<8, 8, 32>;
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float alpha = 1.f;
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float beta = 0.f;
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// Define the MmaCore components
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using MmaCore = typename cutlass::gemm::threadblock::DefaultMmaCore<
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ThreadBlockShape, WarpShape, InstructionShape,
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ElementA, LayoutA,
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ElementB, LayoutB,
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ElementC, LayoutC,
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cutlass::arch::OpClassWmmaTensorOp, kStages>;
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dim3 grid(1, 1);
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dim3 block(32, 1, 1);
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test::gemm::threadblock::Testbed<MmaCore, kStages>(problem_size.m(), problem_size.n(),
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problem_size.k(), alpha, beta)
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.run(grid, block);
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}
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TEST(SM75_gemm_threadblock_wmma_tensor_op_row_col_col_s4, 64x64x64_64x64x64_8x8x32) {
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using ElementA = cutlass::int4b_t;
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using LayoutA = cutlass::layout::RowMajor;
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using ElementB = cutlass::int4b_t;
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using LayoutB = cutlass::layout::ColumnMajor;
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using ElementC = int32_t;
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using LayoutC = cutlass::layout::ColumnMajor;
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static const int kStages = 2;
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cutlass::gemm::GemmCoord problem_size(64, 64, 64);
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using ThreadBlockShape = cutlass::gemm::GemmShape<64, 64, 64>;
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using WarpShape = cutlass::gemm::GemmShape<64, 64, 64>;
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using InstructionShape = cutlass::gemm::GemmShape<8, 8, 32>;
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float alpha = 1.f;
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float beta = 0.f;
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// Define the MmaCore components
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using MmaCore = typename cutlass::gemm::threadblock::DefaultMmaCore<
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ThreadBlockShape, WarpShape, InstructionShape,
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ElementA, LayoutA,
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ElementB, LayoutB,
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ElementC, LayoutC,
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cutlass::arch::OpClassWmmaTensorOp, kStages>;
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dim3 grid(1, 1);
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dim3 block(32, 1, 1);
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test::gemm::threadblock::Testbed<MmaCore, kStages>(problem_size.m(), problem_size.n(),
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problem_size.k(), alpha, beta)
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.run(grid, block);
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}
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TEST(SM75_gemm_threadblock_wmma_tensor_op_row_col_row_b1, 64x64x512_64x64x512_8x8x128) {
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using ElementA = cutlass::uint1b_t;
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using LayoutA = cutlass::layout::RowMajor;
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using ElementB = cutlass::uint1b_t;
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using LayoutB = cutlass::layout::ColumnMajor;
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using ElementC = int32_t;
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using LayoutC = cutlass::layout::RowMajor;
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static const int kStages = 2;
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cutlass::gemm::GemmCoord problem_size(64, 64, 2048);
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using ThreadBlockShape = cutlass::gemm::GemmShape<64, 64, 512>;
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using WarpShape = cutlass::gemm::GemmShape<64, 64, 512>;
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using InstructionShape = cutlass::gemm::GemmShape<8, 8, 128>;
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float alpha = 1.f;
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float beta = 0.f;
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// Define the MmaCore components
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using MmaCore = typename cutlass::gemm::threadblock::DefaultMmaCore<
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ThreadBlockShape, WarpShape, InstructionShape,
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ElementA, LayoutA,
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ElementB, LayoutB,
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ElementC, LayoutC,
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cutlass::arch::OpClassWmmaTensorOp, kStages,
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cutlass::arch::OpXorPopc>;
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dim3 grid(1, 1);
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dim3 block(32, 1, 1);
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test::gemm::threadblock::Testbed<MmaCore, kStages>(problem_size.m(), problem_size.n(),
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problem_size.k(), alpha, beta)
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.run(grid, block);
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}
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TEST(SM75_gemm_threadblock_wmma_tensor_op_row_col_col_b1, 64x64x512_64x64x512_8x8x128) {
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using ElementA = cutlass::uint1b_t;
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using LayoutA = cutlass::layout::RowMajor;
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using ElementB = cutlass::uint1b_t;
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using LayoutB = cutlass::layout::ColumnMajor;
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using ElementC = int32_t;
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using LayoutC = cutlass::layout::ColumnMajor;
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static const int kStages = 2;
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cutlass::gemm::GemmCoord problem_size(64, 64, 2048);
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using ThreadBlockShape = cutlass::gemm::GemmShape<64, 64, 512>;
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using WarpShape = cutlass::gemm::GemmShape<64, 64, 512>;
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using InstructionShape = cutlass::gemm::GemmShape<8, 8, 128>;
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float alpha = 1.f;
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float beta = 0.f;
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// Define the MmaCore components
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using MmaCore = typename cutlass::gemm::threadblock::DefaultMmaCore<
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ThreadBlockShape, WarpShape, InstructionShape,
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ElementA, LayoutA,
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ElementB, LayoutB,
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ElementC, LayoutC,
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cutlass::arch::OpClassWmmaTensorOp, kStages,
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cutlass::arch::OpXorPopc>;
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dim3 grid(1, 1);
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dim3 block(32, 1, 1);
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test::gemm::threadblock::Testbed<MmaCore, kStages>(problem_size.m(), problem_size.n(),
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problem_size.k(), alpha, beta)
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.run(grid, block);
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}
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#endif //CUTLASS_SUBBYTE_INTEGER_MATRIX_MULTIPLY_ENABLED
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#endif //CUTLASS_ARCH_WMMA_SM75_ENABLED
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