/*************************************************************************************************** * Copyright (c) 2017-2021, NVIDIA CORPORATION. All rights reserved. * * Redistribution and use in source and binary forms, with or without modification, are permitted * provided that the following conditions are met: * * Redistributions of source code must retain the above copyright notice, this list of * conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright notice, this list of * conditions and the following disclaimer in the documentation and/or other materials * provided with the distribution. * * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used * to endorse or promote products derived from this software without specific prior written * permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND * FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; * OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, * STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * **************************************************************************************************/ #include "b2b_conv2d_fprop_implicit_gemm_s8ncxhwx_s8cxrskx_s8ncxhwx_tensor_op_s32_sm75.h" #include "b2b_conv2d_fprop_implicit_gemm_s8ncxhwx_s8cxrskx_s8ncxhwx_tensor_op_s32_sm80.h" #include "b2b_conv2d_fprop_implicit_gemm_f16nhwc_f16nhwc_f16nhwc_tensor_op_f16_sm75.h" #include "b2b_conv2d_fprop_implicit_gemm_f16nhwc_f16nhwc_f16nhwc_tensor_op_f16_sm80.h" int run() { cudaDeviceProp props; cudaError_t error = cudaGetDeviceProperties(&props, 0); if (error != cudaSuccess) { std::cerr << "cudaGetDeviceProperties() returned an error: " << cudaGetErrorString(error) << std::endl; return -1; } if (!(props.major * 10 + props.minor >= 75)) { std::cerr << "Turing Tensor Ops must be run on a machine with compute capability at least 75." << std::endl; // Returning zero so this test passes on older Toolkits. Its actions are no-op. return 0; } #if defined(CUTLASS_ARCH_MMA_SM80_SUPPORTED) std::cout << "Running on SM80" << std::endl; run_nonfused_conv2d_fprop_optimized_f16_sm80(); run_fused_conv2d_fprop_optimized_f16_sm80(); run_nonfused_conv2d_fprop_optimized_s8_sm80(); run_fused_conv2d_fprop_optimized_s8_sm80(); #elif defined(CUTLASS_ARCH_MMA_SM75_SUPPORTED) std::cout << "Running on SM75" << std::endl; run_nonfused_conv2d_fprop_optimized_f16_sm75(); run_fused_conv2d_fprop_optimized_f16_sm75(); run_nonfused_conv2d_fprop_optimized_s8_sm75(); run_fused_conv2d_fprop_optimized_s8_sm75(); #endif return 0; } int main() { bool notSupported = false; // Turing Tensor Core operations exposed with mma.sync are first available in CUDA 10.2. // // CUTLASS must be compiled with CUDA 10.2 Toolkit to run these examples. if (!(__CUDACC_VER_MAJOR__ > 10 || (__CUDACC_VER_MAJOR__ == 10 && __CUDACC_VER_MINOR__ >= 2))) { std::cerr << "Tensor Core operations used in this example must be compiled with CUDA 10.2 Toolkit or later." << std::endl; notSupported = true; } cudaDeviceProp props; cudaError_t error = cudaGetDeviceProperties(&props, 0); if (error != cudaSuccess) { std::cerr << "cudaGetDeviceProperties() returned an error: " << cudaGetErrorString(error) << std::endl; return -1; } if (!(props.major * 10 + props.minor >= 75)) { std::cerr << "Tensor Ops used in this example must be run on a machine with compute capability at least 75." << std::endl; notSupported = true; } if (notSupported) { // Returning zero so this test passes on older Toolkits. Its actions are no-op. return 0; } return run(); }