328 lines
15 KiB
Plaintext
328 lines
15 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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/*! \file
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\brief Unit tests for thread-level GEMM
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*/
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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_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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#if defined(CUTLASS_ARCH_MMA_SM80_SUPPORTED)
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////////////////////////////////////////////////////////////////////////////////
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/// F32 <= F16 * I8 + F32 (Upcast on Operand B)
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////////////////////////////////////////////////////////////////////////////////
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TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_f16_i8, 128x128x64_64x64x64_16x8x16) {
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using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
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using ElementA = cutlass::half_t;
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using ElementB = int8_t;
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using ElementC = float;
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using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementA>::value, 64>;
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using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementB>::value, 64>;
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using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
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Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
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cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
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test::gemm::warp::TransformTestbed<MmaTensorOp,
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cutlass::gemm::GemmShape<128, 128, 64> >()
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.run();
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}
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TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_f16_i8, 64x64x64_64x64x64_16x8x16) {
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using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
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using ElementA = cutlass::half_t;
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using ElementB = int8_t;
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using ElementC = float;
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using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementA>::value, 64>;
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using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementB>::value, 64>;
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using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
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Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
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cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
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test::gemm::warp::TransformTestbed<MmaTensorOp,
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cutlass::gemm::GemmShape<64, 64, 64> >()
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.run();
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}
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////////////////////////////////////////////////////////////////////////////////
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/// F32 <= I8 * F16 + F32 (Upcast on Operand A)
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////////////////////////////////////////////////////////////////////////////////
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TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_i8_f16, 128x128x64_64x64x64_16x8x16) {
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using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
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using ElementA = int8_t;
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using ElementB = cutlass::half_t;;
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using ElementC = float;
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using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementA>::value, 64>;
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using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementB>::value, 64>;
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using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
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Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
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cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
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test::gemm::warp::TransformTestbed<MmaTensorOp,
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cutlass::gemm::GemmShape<128, 128, 64> >()
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.run();
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}
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TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_i8_f16, 64x64x64_64x64x64_16x8x16) {
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using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
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using ElementA = int8_t;
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using ElementB = cutlass::half_t;
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using ElementC = float;
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using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementA>::value, 64>;
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using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementB>::value, 64>;
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using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
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Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
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cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
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test::gemm::warp::TransformTestbed<MmaTensorOp,
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cutlass::gemm::GemmShape<64, 64, 64> >()
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.run();
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}
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////////////////////////////////////////////////////////////////////////////////
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/// F32 <= F16 * U8 + F32 (Upcast on Operand B)
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////////////////////////////////////////////////////////////////////////////////
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TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_f16_u8, 64x64x64_64x64x64_16x8x16) {
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using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
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using ElementA = cutlass::half_t;
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using ElementB = uint8_t;
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using ElementC = float;
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using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementA>::value, 64>;
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using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementB>::value, 64>;
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using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
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Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
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cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
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test::gemm::warp::TransformTestbed<MmaTensorOp,
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cutlass::gemm::GemmShape<64, 64, 64> >()
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.run();
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}
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TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_f16_u8, 128x128x64_64x64x64_16x8x16) {
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using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
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using ElementA = cutlass::half_t;
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using ElementB = uint8_t;
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using ElementC = float;
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using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementA>::value, 64>;
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using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementB>::value, 64>;
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using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
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Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
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cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
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test::gemm::warp::TransformTestbed<MmaTensorOp,
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cutlass::gemm::GemmShape<128, 128, 64> >()
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.run();
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}
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////////////////////////////////////////////////////////////////////////////////
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/// F32 <= U8 * F16 + F32 (Upcast on Operand A)
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////////////////////////////////////////////////////////////////////////////////
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TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_u8_f16, 64x64x64_64x64x64_16x8x16) {
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using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
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using ElementA = uint8_t;
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using ElementB = cutlass::half_t;
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using ElementC = float;
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using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementA>::value, 64>;
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using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementB>::value, 64>;
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using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
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Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
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cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
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test::gemm::warp::TransformTestbed<MmaTensorOp,
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cutlass::gemm::GemmShape<64, 64, 64> >()
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.run();
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}
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TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_u8_f16, 128x128x64_64x64x64_16x8x16) {
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using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
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using ElementA = uint8_t;
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using ElementB = cutlass::half_t;
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using ElementC = float;
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using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementA>::value, 64>;
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using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementB>::value, 64>;
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using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
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Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
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cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
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test::gemm::warp::TransformTestbed<MmaTensorOp,
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cutlass::gemm::GemmShape<128, 128, 64> >()
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.run();
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}
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////////////////////////////////////////////////////////////////////////////////
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/// F32 <= B16 * U8 + F32 (Upcast on Operand B)
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////////////////////////////////////////////////////////////////////////////////
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TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_bf16_u8, 64x64x64_64x64x64_16x8x16) {
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using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
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using ElementA = cutlass::bfloat16_t;
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using ElementB = uint8_t;
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using ElementC = float;
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using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementA>::value, 64>;
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using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementB>::value, 64>;
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using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
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Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
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cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
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test::gemm::warp::TransformTestbed<MmaTensorOp,
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cutlass::gemm::GemmShape<64, 64, 64> >()
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.run();
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}
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////////////////////////////////////////////////////////////////////////////////
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/// F32 <= U8 * BF16 + F32 (Upcast on Operand A)
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////////////////////////////////////////////////////////////////////////////////
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TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_u8_bf16, 64x64x64_64x64x64_16x8x16) {
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using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
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using ElementA = uint8_t;
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using ElementB = cutlass::bfloat16_t;
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using ElementC = float;
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using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementA>::value, 64>;
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using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementB>::value, 64>;
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using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
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Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
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cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
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test::gemm::warp::TransformTestbed<MmaTensorOp,
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cutlass::gemm::GemmShape<64, 64, 64> >()
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.run();
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}
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////////////////////////////////////////////////////////////////////////////////
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/// F32 <= I8 * BF16 + F32 (Upcast on Operand A)
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////////////////////////////////////////////////////////////////////////////////
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TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_bf16_i8, 64x64x64_64x64x64_16x8x16) {
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using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
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using ElementA = cutlass::bfloat16_t;
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using ElementB = int8_t;
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using ElementC = float;
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using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementA>::value, 64>;
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using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementB>::value, 64>;
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using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
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Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
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cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
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test::gemm::warp::TransformTestbed<MmaTensorOp,
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cutlass::gemm::GemmShape<64, 64, 64> >()
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.run();
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}
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////////////////////////////////////////////////////////////////////////////////
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/// F32 <= B16 * I8 + F32 (Upcast on Operand B)
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////////////////////////////////////////////////////////////////////////////////
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TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_i8_bf16, 64x64x64_64x64x64_16x8x16) {
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using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
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using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
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using ElementA = int8_t;
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using ElementB = cutlass::bfloat16_t;
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using ElementC = float;
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using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementA>::value, 64>;
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using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
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cutlass::sizeof_bits<ElementB>::value, 64>;
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using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
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Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
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cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
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test::gemm::warp::TransformTestbed<MmaTensorOp,
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cutlass::gemm::GemmShape<64, 64, 64> >()
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.run();
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}
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#endif // if defined(CUTLASS_ARCH_MMA_SM80_SUPPORTED)
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