fb335f6a5f
CUTLASS 2.0 Substantially refactored for - Better performance, particularly for native Turing Tensor Cores - Robust and durable templates spanning the design space - Encapsulated functionality embodying modern C++11 programming techniques - Optimized containers and data types for efficient, generic, portable device code Updates to: - Quick start guide - Documentation - Utilities - CUTLASS Profiler Native Turing Tensor Cores - Efficient GEMM kernels targeting Turing Tensor Cores - Mixed-precision floating point, 8-bit integer, 4-bit integer, and binarized operands Coverage of existing CUTLASS functionality: - GEMM kernels targeting CUDA and Tensor Cores in NVIDIA GPUs - Volta Tensor Cores through native mma.sync and through WMMA API - Optimizations such as parallel reductions, threadblock rasterization, and intra-threadblock reductions - Batched GEMM operations - Complex-valued GEMMs Note: this commit and all that follow require a host compiler supporting C++11 or greater.
493 lines
18 KiB
Plaintext
493 lines
18 KiB
Plaintext
/***************************************************************************************************
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* Copyright (c) 2017-2019, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without modification, are permitted
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* provided that the following conditions are met:
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* * Redistributions of source code must retain the above copyright notice, this list of
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* conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright notice, this list of
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* conditions and the following disclaimer in the documentation and/or other materials
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* provided with the distribution.
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* * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used
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* to endorse or promote products derived from this software without specific prior written
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* permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
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* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
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* FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
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* OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
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* STRICT LIABILITY, OR TOR (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 "mma_pipelined_testbed.h"
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#if defined(CUTLASS_ARCH_MMA_SM70_SUPPORTED)
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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_gemm_threadblock_congruous, tensor_op_64x64x32_64x64x32_8x8x4) {
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using ElementA = cutlass::half_t;
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using LayoutA = cutlass::layout::ColumnMajor;
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using ElementB = cutlass::half_t;
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using LayoutB = cutlass::layout::RowMajor;
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using ElementC = float;
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using LayoutC = cutlass::layout::ColumnMajor;
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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<8, 8, 4>;
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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, ElementA, LayoutA,
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ElementB, LayoutB, ElementC, LayoutC,
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cutlass::arch::OpClassTensorOp>;
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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>(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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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_gemm_threadblock_congruous, tensor_op_128x128x32_64x64x32_8x8x4) {
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using ElementA = cutlass::half_t;
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using LayoutA = cutlass::layout::ColumnMajor;
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using ElementB = cutlass::half_t;
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using LayoutB = cutlass::layout::RowMajor;
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using ElementC = float;
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using LayoutC = cutlass::layout::ColumnMajor;
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cutlass::gemm::GemmCoord problem_size(128, 128, 128);
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using ThreadblockShape = cutlass::gemm::GemmShape<128, 128, 32>;
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using WarpShape = cutlass::gemm::GemmShape<64, 64, 32>;
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using InstructionShape = cutlass::gemm::GemmShape<8, 8, 4>;
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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, ElementA, LayoutA,
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ElementB, LayoutB, ElementC, LayoutC,
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cutlass::arch::OpClassTensorOp>;
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dim3 grid(1, 1);
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dim3 block(32, 4, 1);
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test::gemm::threadblock::Testbed<MmaCore>(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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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_gemm_threadblock_congruous, tensor_op_64x64x32_32x32x32_8x8x4) {
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using ElementA = cutlass::half_t;
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using LayoutA = cutlass::layout::ColumnMajor;
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using ElementB = cutlass::half_t;
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using LayoutB = cutlass::layout::RowMajor;
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using ElementC = float;
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using LayoutC = cutlass::layout::ColumnMajor;
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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<32, 32, 32>;
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using InstructionShape = cutlass::gemm::GemmShape<8, 8, 4>;
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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, ElementA, LayoutA,
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ElementB, LayoutB, ElementC, LayoutC,
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cutlass::arch::OpClassTensorOp>;
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dim3 grid(1, 1);
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dim3 block(32, 4, 1);
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test::gemm::threadblock::Testbed<MmaCore>(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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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_gemm_threadblock_congruous, tensor_op_128x64x32_64x32x32_8x8x4) {
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using ElementA = cutlass::half_t;
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using LayoutA = cutlass::layout::ColumnMajor;
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using ElementB = cutlass::half_t;
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using LayoutB = cutlass::layout::RowMajor;
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using ElementC = float;
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using LayoutC = cutlass::layout::ColumnMajor;
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cutlass::gemm::GemmCoord problem_size(128, 64, 128);
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using ThreadblockShape = cutlass::gemm::GemmShape<128, 64, 32>;
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using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>;
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using InstructionShape = cutlass::gemm::GemmShape<8, 8, 4>;
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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, ElementA, LayoutA,
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ElementB, LayoutB, ElementC, LayoutC,
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cutlass::arch::OpClassTensorOp>;
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dim3 grid(1, 1);
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dim3 block(32, 4, 1);
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test::gemm::threadblock::Testbed<MmaCore>(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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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_gemm_threadblock_congruous, tensor_op_128x64x64_64x32x64_8x8x4) {
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using ElementA = cutlass::half_t;
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using LayoutA = cutlass::layout::ColumnMajor;
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using ElementB = cutlass::half_t;
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using LayoutB = cutlass::layout::RowMajor;
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using ElementC = float;
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using LayoutC = cutlass::layout::ColumnMajor;
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cutlass::gemm::GemmCoord problem_size(128, 64, 128);
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using ThreadblockShape = cutlass::gemm::GemmShape<128, 64, 64>;
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using WarpShape = cutlass::gemm::GemmShape<64, 32, 64>;
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using OperatorShape = cutlass::gemm::GemmShape<8, 8, 4>;
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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, OperatorShape, ElementA, LayoutA, ElementB,
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LayoutB, ElementC, LayoutC, cutlass::arch::OpClassTensorOp>;
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dim3 grid(1, 1);
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dim3 block(32, 4, 1);
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test::gemm::threadblock::Testbed<MmaCore>(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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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_gemm_threadblock_congruous, tensor_op_64x128x32_32x64x32_8x8x4) {
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using ElementA = cutlass::half_t;
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using LayoutA = cutlass::layout::ColumnMajor;
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using ElementB = cutlass::half_t;
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using LayoutB = cutlass::layout::RowMajor;
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using ElementC = float;
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using LayoutC = cutlass::layout::ColumnMajor;
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cutlass::gemm::GemmCoord problem_size(64, 128, 128);
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using ThreadblockShape = cutlass::gemm::GemmShape<64, 128, 32>;
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using WarpShape = cutlass::gemm::GemmShape<32, 64, 32>;
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using InstructionShape = cutlass::gemm::GemmShape<8, 8, 4>;
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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, ElementA, LayoutA,
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ElementB, LayoutB, ElementC, LayoutC,
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cutlass::arch::OpClassTensorOp>;
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dim3 grid(1, 1);
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dim3 block(32, 4, 1);
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test::gemm::threadblock::Testbed<MmaCore>(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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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_gemm_threadblock_congruous, tensor_op_256x128x32_32x64x32_8x8x4) {
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using ElementA = cutlass::half_t;
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using LayoutA = cutlass::layout::ColumnMajor;
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using ElementB = cutlass::half_t;
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using LayoutB = cutlass::layout::RowMajor;
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using ElementC = float;
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using LayoutC = cutlass::layout::ColumnMajor;
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cutlass::gemm::GemmCoord problem_size(256, 128, 128);
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using ThreadblockShape = cutlass::gemm::GemmShape<256, 128, 32>;
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using WarpShape = cutlass::gemm::GemmShape<64, 64, 32>;
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using InstructionShape = cutlass::gemm::GemmShape<8, 8, 4>;
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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, ElementA, LayoutA,
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ElementB, LayoutB, ElementC, LayoutC,
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cutlass::arch::OpClassTensorOp>;
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dim3 grid(1, 1);
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dim3 block(32, 8, 1);
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test::gemm::threadblock::Testbed<MmaCore>(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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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_gemm_threadblock_crosswise, tensor_op_64x64x32_64x64x32_8x8x4) {
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using ElementA = cutlass::half_t;
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using LayoutA = cutlass::layout::RowMajor;
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using ElementB = cutlass::half_t;
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using LayoutB = cutlass::layout::ColumnMajor;
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using ElementC = cutlass::half_t;
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using LayoutC = cutlass::layout::ColumnMajor;
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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<8, 8, 4>;
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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, ElementA, LayoutA,
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ElementB, LayoutB, ElementC, LayoutC,
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cutlass::arch::OpClassTensorOp>;
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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>(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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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_gemm_threadblock_crosswise, tensor_op_128x128x32_64x64x32_8x8x4) {
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using ElementA = cutlass::half_t;
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using LayoutA = cutlass::layout::RowMajor;
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using ElementB = cutlass::half_t;
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using LayoutB = cutlass::layout::ColumnMajor;
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using ElementC = cutlass::half_t;
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using LayoutC = cutlass::layout::ColumnMajor;
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cutlass::gemm::GemmCoord problem_size(128, 128, 128);
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using ThreadblockShape = cutlass::gemm::GemmShape<128, 128, 32>;
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using WarpShape = cutlass::gemm::GemmShape<64, 64, 32>;
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using InstructionShape = cutlass::gemm::GemmShape<8, 8, 4>;
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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, ElementA, LayoutA,
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ElementB, LayoutB, ElementC, LayoutC,
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cutlass::arch::OpClassTensorOp>;
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dim3 grid(1, 1);
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dim3 block(32, 4, 1);
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test::gemm::threadblock::Testbed<MmaCore>(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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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_gemm_threadblock_crosswise, tensor_op_256x128x32_64x64x32_8x8x4) {
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using ElementA = cutlass::half_t;
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using LayoutA = cutlass::layout::RowMajor;
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using ElementB = cutlass::half_t;
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using LayoutB = cutlass::layout::ColumnMajor;
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using ElementC = cutlass::half_t;
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using LayoutC = cutlass::layout::ColumnMajor;
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cutlass::gemm::GemmCoord problem_size(256, 128, 128);
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using ThreadblockShape = cutlass::gemm::GemmShape<256, 128, 32>;
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using WarpShape = cutlass::gemm::GemmShape<64, 64, 32>;
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using InstructionShape = cutlass::gemm::GemmShape<8, 8, 4>;
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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, ElementA, LayoutA,
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ElementB, LayoutB, ElementC, LayoutC,
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cutlass::arch::OpClassTensorOp>;
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dim3 grid(1, 1);
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dim3 block(32, 8, 1);
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test::gemm::threadblock::Testbed<MmaCore>(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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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_gemm_threadblock_crosswise, tensor_op_64x64x32_32x32x32_8x8x4) {
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using ElementA = cutlass::half_t;
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using LayoutA = cutlass::layout::RowMajor;
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using ElementB = cutlass::half_t;
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using LayoutB = cutlass::layout::ColumnMajor;
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using ElementC = cutlass::half_t;
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using LayoutC = cutlass::layout::ColumnMajor;
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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<32, 32, 32>;
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using InstructionShape = cutlass::gemm::GemmShape<8, 8, 4>;
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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, ElementA, LayoutA,
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ElementB, LayoutB, ElementC, LayoutC,
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cutlass::arch::OpClassTensorOp>;
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dim3 grid(1, 1);
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dim3 block(32, 4, 1);
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test::gemm::threadblock::Testbed<MmaCore>(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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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_gemm_threadblock_crosswise, tensor_op_128x64x32_64x32x32_8x8x4) {
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using ElementA = cutlass::half_t;
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using LayoutA = cutlass::layout::RowMajor;
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using ElementB = cutlass::half_t;
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using LayoutB = cutlass::layout::ColumnMajor;
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using ElementC = cutlass::half_t;
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using LayoutC = cutlass::layout::ColumnMajor;
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cutlass::gemm::GemmCoord problem_size(128, 64, 128);
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using ThreadblockShape = cutlass::gemm::GemmShape<128, 64, 32>;
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using WarpShape = cutlass::gemm::GemmShape<64, 32, 32>;
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using InstructionShape = cutlass::gemm::GemmShape<8, 8, 4>;
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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, ElementA, LayoutA,
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ElementB, LayoutB, ElementC, LayoutC,
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cutlass::arch::OpClassTensorOp>;
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dim3 grid(1, 1);
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dim3 block(32, 4, 1);
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test::gemm::threadblock::Testbed<MmaCore>(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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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_gemm_threadblock_crosswise, tensor_op_128x64x64_64x32x64_8x8x4) {
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using ElementA = cutlass::half_t;
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using LayoutA = cutlass::layout::RowMajor;
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using ElementB = cutlass::half_t;
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using LayoutB = cutlass::layout::ColumnMajor;
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using ElementC = float;
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using LayoutC = cutlass::layout::ColumnMajor;
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cutlass::gemm::GemmCoord problem_size(128, 64, 128);
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using ThreadblockShape = cutlass::gemm::GemmShape<128, 64, 64>;
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using WarpShape = cutlass::gemm::GemmShape<64, 32, 64>;
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using OperatorShape = cutlass::gemm::GemmShape<8, 8, 4>;
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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, OperatorShape, ElementA, LayoutA, ElementB,
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LayoutB, ElementC, LayoutC, cutlass::arch::OpClassTensorOp>;
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dim3 grid(1, 1);
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dim3 block(32, 4, 1);
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test::gemm::threadblock::Testbed<MmaCore>(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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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_gemm_threadblock_crosswise, tensor_op_64x128x32_32x64x32_8x8x4) {
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using ElementA = cutlass::half_t;
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using LayoutA = cutlass::layout::RowMajor;
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using ElementB = cutlass::half_t;
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using LayoutB = cutlass::layout::ColumnMajor;
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using ElementC = cutlass::half_t;
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using LayoutC = cutlass::layout::ColumnMajor;
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|
|
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cutlass::gemm::GemmCoord problem_size(64, 128, 128);
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|
|
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using ThreadblockShape = cutlass::gemm::GemmShape<64, 128, 32>;
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using WarpShape = cutlass::gemm::GemmShape<32, 64, 32>;
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using InstructionShape = cutlass::gemm::GemmShape<8, 8, 4>;
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|
|
|
float alpha = 1.f;
|
|
float beta = 0.0f;
|
|
|
|
// Define the MmaCore components
|
|
using MmaCore = typename cutlass::gemm::threadblock::DefaultMmaCore<
|
|
ThreadblockShape, WarpShape, InstructionShape, ElementA, LayoutA,
|
|
ElementB, LayoutB, ElementC, LayoutC,
|
|
cutlass::arch::OpClassTensorOp>;
|
|
|
|
dim3 grid(1, 1);
|
|
dim3 block(32, 4, 1);
|
|
|
|
test::gemm::threadblock::Testbed<MmaCore>(problem_size.m(), problem_size.n(),
|
|
problem_size.k(), alpha, beta)
|
|
.run(grid, block);
|
|
}
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|
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#endif // CUTLASS_ARCH_MMA_SM70_SUPPORTED
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