186 lines
7.4 KiB
Plaintext
186 lines
7.4 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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#if defined(CUTLASS_ARCH_WMMA_SM72_ENABLED)
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#include "../../common/cutlass_unit_test.h"
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#include "cutlass/aligned_buffer.h"
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#include "cutlass/half.h"
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#include "cutlass/gemm/warp/default_mma_wmma_tensor_op.h"
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#include "cutlass/core_io.h"
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#include "cutlass/util/host_tensor.h"
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#include "cutlass/util/tensor_view_io.h"
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#include "cutlass/util/reference/host/tensor_fill.h"
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#include "cutlass/util/reference/host/tensor_compare.h"
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#include "cutlass/util/reference/host/gemm.h"
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#include "testbed.h"
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///////////////////////////////////////////////////////////////////////////////////////////////////////////////
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///////////////////////////////////////////// Integer wmma.mma ////////////////////////////////////////////////
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///////////////////////////////////////////////////////////////////////////////////////////////////////////////
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// TODO: SM75 should be SM72, but the compilation breaks as SM72 shows up and runs on VOLTA
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TEST(SM75_warp_wmma_row_col_s8, 16x16x16_16x16x16_16x16x16) {
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// Threadblock and warp with just one native WMMA operation (most basic unit test)
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using WarpShape = cutlass::gemm::GemmShape<16, 16, 16>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 16, 16>;
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using ElementA = int8_t;
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using ElementB = int8_t;
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using ElementC = int32_t;
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using LayoutA = cutlass::layout::RowMajor;
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using LayoutB = cutlass::layout::ColumnMajor;
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using LayoutC = cutlass::layout::RowMajor;
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using WmmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOpWmma<
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WarpShape,
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InstructionShape,
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ElementA, LayoutA,
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ElementB, LayoutB,
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ElementC, LayoutC>::Type;
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test::gemm::warp::Testbed<WmmaTensorOp, cutlass::gemm::GemmShape<16, 16, 16> >().run();
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}
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TEST(SM75_warp_wmma_row_col_s8, 32x8x16_32x8x16_32x8x16) {
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// Threadblock and warp with just one native WMMA operation (most basic unit test)
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using WarpShape = cutlass::gemm::GemmShape<32, 8, 16>;
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using InstructionShape = cutlass::gemm::GemmShape<32, 8, 16>;
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using ElementA = int8_t;
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using ElementB = int8_t;
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using ElementC = int32_t;
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using LayoutA = cutlass::layout::RowMajor;
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using LayoutB = cutlass::layout::ColumnMajor;
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using LayoutC = cutlass::layout::RowMajor;
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using WmmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOpWmma<
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WarpShape,
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InstructionShape,
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ElementA, LayoutA,
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ElementB, LayoutB,
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ElementC, LayoutC>::Type;
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test::gemm::warp::Testbed<WmmaTensorOp, cutlass::gemm::GemmShape<32, 8, 16> >().run();
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}
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TEST(SM75_warp_wmma_row_col_s8, 8x32x16_8x32x16_8x32x16) {
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// Threadblock and warp with just one native WMMA operation (most basic unit test)
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using WarpShape = cutlass::gemm::GemmShape<8, 32, 16>;
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using InstructionShape = cutlass::gemm::GemmShape<8, 32, 16>;
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using ElementA = int8_t;
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using ElementB = int8_t;
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using ElementC = int32_t;
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using LayoutA = cutlass::layout::RowMajor;
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using LayoutB = cutlass::layout::ColumnMajor;
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using LayoutC = cutlass::layout::RowMajor;
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using WmmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOpWmma<
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WarpShape,
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InstructionShape,
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ElementA, LayoutA,
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ElementB, LayoutB,
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ElementC, LayoutC>::Type;
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test::gemm::warp::Testbed<WmmaTensorOp, cutlass::gemm::GemmShape<8, 32, 16> >().run();
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}
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TEST(SM75_warp_wmma_row_col_u8, 16x16x16_16x16x16_16x16x16) {
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// Threadblock and warp with just one native WMMA operation (most basic unit test)
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using WarpShape = cutlass::gemm::GemmShape<16, 16, 16>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 16, 16>;
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using ElementA = uint8_t;
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using ElementB = uint8_t;
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using ElementC = int32_t;
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using LayoutA = cutlass::layout::RowMajor;
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using LayoutB = cutlass::layout::ColumnMajor;
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using LayoutC = cutlass::layout::RowMajor;
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using WmmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOpWmma<
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WarpShape,
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InstructionShape,
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ElementA, LayoutA,
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ElementB, LayoutB,
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ElementC, LayoutC>::Type;
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test::gemm::warp::Testbed<WmmaTensorOp, cutlass::gemm::GemmShape<16, 16, 16> >().run();
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}
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TEST(SM75_warp_wmma_row_col_u8, 32x8x16_32x8x16_32x8x16) {
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// Threadblock and warp with just one native WMMA operation (most basic unit test)
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using WarpShape = cutlass::gemm::GemmShape<32, 8, 16>;
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using InstructionShape = cutlass::gemm::GemmShape<32, 8, 16>;
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using ElementA = uint8_t;
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using ElementB = uint8_t;
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using ElementC = int32_t;
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using LayoutA = cutlass::layout::RowMajor;
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using LayoutB = cutlass::layout::ColumnMajor;
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using LayoutC = cutlass::layout::RowMajor;
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using WmmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOpWmma<
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WarpShape,
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InstructionShape,
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ElementA, LayoutA,
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ElementB, LayoutB,
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ElementC, LayoutC>::Type;
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test::gemm::warp::Testbed<WmmaTensorOp, cutlass::gemm::GemmShape<32, 8, 16> >().run();
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}
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TEST(SM75_warp_wmma_row_col_u8, 8x32x16_8x32x16_8x32x16) {
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// Threadblock and warp with just one native WMMA operation (most basic unit test)
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using WarpShape = cutlass::gemm::GemmShape<8, 32, 16>;
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using InstructionShape = cutlass::gemm::GemmShape<8, 32, 16>;
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using ElementA = uint8_t;
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using ElementB = uint8_t;
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using ElementC = int32_t;
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using LayoutA = cutlass::layout::RowMajor;
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using LayoutB = cutlass::layout::ColumnMajor;
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using LayoutC = cutlass::layout::RowMajor;
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using WmmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOpWmma<
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WarpShape,
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InstructionShape,
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ElementA, LayoutA,
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ElementB, LayoutB,
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ElementC, LayoutC>::Type;
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test::gemm::warp::Testbed<WmmaTensorOp, cutlass::gemm::GemmShape<8, 32, 16> >().run();
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}
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#endif //CUTLASS_ARCH_WMMA_SM72_ENABLED
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