This is free software see the source for copying conditions. You cannot install the whole devtoolset-8 collection, but the toolchain is enough, then each time you need to build using cuda, you start by scl run devtoolset-8 bash Install the appropriate gcc version from developer toolset. You will need to tell CUDA to use it instead of using the default g++ this can be done for the cuda-samples with: export HOST_COMPILER=cuda-g++ GCC8 Works up to Fedora 32 for cuda-10.1 and later (up to CUDA 11).Install an older gcc for dedicated for CUDA from COPR (Recommended on Fedora). When using a later version of Fedora than what is supported by the NVIDIA CUDA Official repository, you might be unable to compile. It can be a good idea to keep using the rawhide drivers by default. To ease the installation in stable Fedora branches, you can follow this guideline: See also We usually package the such driver in RPM Fusion for rawhide. Sometime with recent CUDA releases, a newer/beta driver version is required. Please verify to have a compatible compiler. This repository contains a legacy version of CUDA 6.5 that will works with the NVIDIA 340xx seriesįedora 20 (and later) sudo yum install install This requires to login with the NVIDIA CUDA program subscription. You can download the TensorRT component using the appropriate version from Sudo yum install libcudnn7 libcudnn7-devel libnccl libnccl-devel Sudo dnf install libcudnn7 libcudnn7-devel libnccl libnccl-devel RHEL/CentOS 7 sudo yum-config-manager -add-repo RHEL/CentOS 8 sudo dnf config-manager -add-repo ![]() ![]() These repositories contain versions of CUDA that are parallel installables along with another version.įedora 35 and later (if using a compatible compiler, see also sudo dnf config-manager -add-repo This Howto provides a way to install the official NVIDIA packages for CUDA.
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