When I had issues, I would purge nvidia* and re-get it. Run with -override to override compiler choice chmod +x cuda_9.0.176_384.81_linux-runĪfter installing the package, I would get errors with nvidia-smi, so I suggest running the command again to verify it works. Sudo apt-get install g++ freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libglu1-mesa libglu1-mesa-dev Sudo apt install nvidia-384 nvidia-384-dev Get content sudo add-apt-repository ppa:graphics-drivers/ppa Update initramfs disk sudo update-initramfs -u Getting this installed took more time than I would like to admit, and while the above answer is a good template, I had some additional steps required for my fresh install of Ubuntu 17.10: blacklist nouveau sudo vim /etc/modprobe.d/nfĪdd the following: # this one might not be required for x86 32 bit users. You may like to set up gcc/g++ symlinks after the cuda install. /bin/x86_64/linux/release/smokeParticles Test the CUDA 9 installation using the SDKīuild your favorite CUDA sample and run it: cd ~/NVIDIA_CUDA-9.0_Samples/5_Simulations/smokeParticles Sudo ln -s /usr/bin/g++-6 /usr/local/cuda/bin/g++ Set up symlinks for gcc/g++: sudo ln -s /usr/bin/gcc-6 /usr/local/cuda/bin/gcc Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 384.81?ĭo you want to install a symbolic link at /usr/local/cuda? We install CUDA with the following configurations: You are attempting to install on an unsupported configuration. Make the downloaded file executable and run it using sudo: chmod +x cuda_9.0.176_384.81_linux-run Note that the default gcc version is still 7.2 can be checked by running gcc -v again.įrom the CUDA Toolkit Archive, select one of the "runfile (local)" installation packages to download a version of CUDA 9, such as wget Thus, we install it: sudo apt install gcc-6 We notice that the default gcc/g++ version on 17.10 is 7.2.0 (Ubuntu 7.2.0-8ubuntu3)ĬUDA 9 requires gcc 6. We install a number of build/dev packages which we require later: sudo apt-get install g++ freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libglu1-mesa libglu1-mesa-dev Preparation for installing of CUDA 9 + SDK We should see an output which lists the NVIDIA 384 driver and our discrete NVIDIA GPU - similar to summarized table below: +-+ We verify the installation by running: nvidia-smi Then we install the most recent NVIDIA driver using apt: sudo apt install nvidia-384 nvidia-384-dev Alternatively, we can add the graphics drivers repository manually: sudo add-apt-repository ppa:graphics-drivers/ppa Note: This is a condensed version (easier to copy-paste-follow) of instructions I found here.First we install a fresh Ubuntu 17.10 on a computer with an NVIDIA GPU and select "Install third-party software" during the process. If you need to use other versions check compatibility with tensorflow first here Step 2 - shell commands to copy-paste I would recommend these exact file versions. CUDA is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). Required files you can find on the nvidia developper site I also recommend you follow the steps bellow on a clean install of Ubuntu 18.04 Step 1 - Requirements I would recommend the second option as it’s the easiest and I tested it countless times on various setups Build Tensorflow from source to support CUDA 9.1.Problem is that Ubuntu 18.04 supports CUDA 9.1 but there is no official support for CUDA 9.0. sudo apt-get install g++ freeglut3-dev build-essential libx11-dev. The current version of Tensorflow (1.12 as of this writting) supports CUDA 9.0. Problem is that Ubuntu 18.04 supports CUDA 9.1 but there is no official support for.
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