1 change: 1 addition & 0 deletions 1 cuda.spec Original file line numberDiff line numberDiff line change @@ -1,4 +1,5 @@ ### RPM external cuda 11.2.0 ## INITENV +PATH LD_LIBRARY_PATH %i/lib64 %define driversversion 460.27.04 0 comments on commit 3c037d5 Please sign in to...
# libnvrtc.so.11.1. See https://github.com/NVIDIA/TensorRT/issues/1064. # TODO(b/187962120): Remove when upgrading to TensorRT 8. ENV LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/cuda-11.1/lib64" 0 comments on commitc17efed Pleasesign into comment....
LD_LIBRARY_PATH=/usr/local/${CUDA_VERSION}/lib64/:/usr/local/${TRT_VERSION}/lib/ SHELL ["/bin/bash", "-c"] COPY ./libcudnn8_8.2.1.32-1+cuda10.2_ub18_amd64.deb ./libcudnn8_8.2.1.32-1+cuda10.2_ub18_amd64.deb ADD ./${TRT_VERSION}.Linux.x86_64-gnu.${CUDA_VERSION}.cudn...
assert(gpu_arch_str &&"Device action expected to have associated a GPU architecture!"); CudaArch gpu_arch = StringToCudaArch(gpu_arch_str);if(II.getType() == types::TY_PP_Asm && !shouldIncludePTX(Args, gpu_arch_str))continue;// We need to pass an Arch of the form "sm_XX" for...
export PATH=/usr/local/cuda-X.Y/bin:$PATH export LD_LIBRARY_PATH=/usr/local/cuda-X.Y/lib64:$LD_LIBRARY_PATH 其中,X.Y应该替换为你的CUDA版本号。 没有正确安装cuDNN: cuDNN(CUDA Deep Neural Network library)是用于深度学习模型的加速库,也是PyTorch的依赖项之一。确保cuDNN正确安装,并且与你的CUD...
cuda/include -fomit-frame-pointer -O3 -funroll-loops -W -Wall -fopenmp -mt_mpi -m64 -lmpi_mt -o /root/hpl-2.0_FERMI_v15/bin/CUDA/xhpl HPL_pddriver.o HPL_pdinfo.o HPL_pdtest.o /root/hpl-2.0_FERMI_v15/lib/CUDA/libhpl.a -L /root/hpl-2.0_FERMI_v15/src/cuda ...
cuda/include -fomit-frame-pointer -O3 -funroll-loops -W -Wall -fopenmp -mt_mpi -m64 -lmpi_mt -o /root/hpl-2.0_FERMI_v15/bin/CUDA/xhpl HPL_pddriver.o HPL_pdinfo.o HPL_pdtest.o /root/hpl-2.0_FERMI_v15/lib/CUDA/libhpl.a -L /root/hpl-2.0_FERMI_v15/src/cuda -ldgemm -L...
Generating CUDA Code from MATLAB: Accelerating Embedded Vision and Deep Learning Algorithms on GPUs Read white paper Select a Web Site Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select...
检查CUDA版本: bash nvcc --version 你应该能看到CUDA编译器的版本信息。 运行CUDA Samples(如果安装了): bash cd /usr/local/cuda-<version>/samples/<path_to_sample> make ./<sample_executable> 替换<version>、<path_to_sample>和<sample_executable>为实...