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Save MihailCosmin/affa6b1b71b43787e9228c25fe15aeba to your computer and use it in GitHub Desktop.
#!/bin/bash | |
### steps #### | |
# verify the system has a cuda-capable gpu | |
# download and install the nvidia cuda toolkit and cudnn | |
# setup environmental variables | |
# verify the installation | |
### | |
### to verify your gpu is cuda enable check | |
lspci | grep -i nvidia | |
### If you have previous installation remove it first. | |
sudo apt purge nvidia* -y | |
sudo apt remove nvidia-* -y | |
sudo rm /etc/apt/sources.list.d/cuda* | |
sudo apt autoremove -y && sudo apt autoclean -y | |
sudo rm -rf /usr/local/cuda* | |
# system update | |
sudo apt update && sudo apt upgrade -y | |
# install other import packages | |
sudo apt install g++ freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libglu1-mesa libglu1-mesa-dev | |
# first get the PPA repository driver | |
sudo add-apt-repository ppa:graphics-drivers/ppa | |
sudo apt update | |
# find recommended driver versions for you | |
ubuntu-drivers devices | |
# install nvidia driver with dependencies | |
sudo apt install libnvidia-common-515 libnvidia-gl-515 nvidia-driver-515 -y | |
# reboot | |
sudo reboot now | |
# verify that the following command works | |
nvidia-smi | |
sudo wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin | |
sudo mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600 | |
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/3bf863cc.pub | |
sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/ /" | |
# Update and upgrade | |
sudo apt update && sudo apt upgrade -y | |
# installing CUDA-11.8 | |
sudo apt install cuda-11-8 -y | |
# setup your paths | |
echo 'export PATH=/usr/local/cuda-11.8/bin:$PATH' >> ~/.bashrc | |
echo 'export LD_LIBRARY_PATH=/usr/local/cuda-11.8/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc | |
source ~/.bashrc | |
sudo ldconfig | |
# install cuDNN v11.8 | |
# First register here: https://developer.nvidia.com/developer-program/signup | |
CUDNN_TAR_FILE="cudnn-linux-x86_64-8.7.0.84_cuda11-archive.tar.xz" | |
sudo wget https://developer.download.nvidia.com/compute/redist/cudnn/v8.7.0/local_installers/11.8/cudnn-linux-x86_64-8.7.0.84_cuda11-archive.tar.xz | |
sudo tar -xvf ${CUDNN_TAR_FILE} | |
sudo mv cudnn-linux-x86_64-8.7.0.84_cuda11-archive cuda | |
# copy the following files into the cuda toolkit directory. | |
sudo cp -P cuda/include/cudnn.h /usr/local/cuda-11.8/include | |
sudo cp -P cuda/lib/libcudnn* /usr/local/cuda-11.8/lib64/ | |
sudo chmod a+r /usr/local/cuda-11.8/lib64/libcudnn* | |
# Finally, to verify the installation, check | |
nvidia-smi | |
nvcc -V | |
# install Pytorch (an open source machine learning framework) | |
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118 |
I ran into the same error very early on. Try my recipe at the link below on a fresh Ubuntu copy. The recipe was tested on different PC, but using the same GPU. Good luck!
https://github.com/Kidney-Science/install_RTXA4000_Driver_CUDA_cudNN_Ubuntu_22
Thank you so much, this script is marvelous !
Gosh, you saved my day. I finally solved my computing env. Thank you very much.
I ran into the same error very early on. Try my recipe at the link below on a fresh Ubuntu copy. The recipe was tested on different PC, but using the same GPU. Good luck! https://github.com/Kidney-Science/install_RTXA4000_Driver_CUDA_cudNN_Ubuntu_22
Your link doesn't work. It takes me to a 404 page.
I've been STRUGGLING with my QEMU KVM VM's that seemingly out of nowhere refused to see my GPU's.
After a few days of fiddling around I eventually figured out a solution.
- Turn off Secure Boot in the VM bios
- Purge all nvidia related stuff
- Install version 520 of the graphics driver
- Install CUDA 11.8
I created a script to make my life easier:
IMPORTANT!
Script:
#!/bin/bash
#install graphics driver 520 specifically
sudo apt purge nvidia* -y
sudo apt autoremove -y && sudo apt autoclean -y
sudo apt update && sudo apt upgrade -y
sudo apt install g++ freeglut3-dev build-essential libx11-dev libxmu dev libxi-dev libglu1-mesa libglu1-mesa-dev
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt update
sudo apt install libnvidia-common-520 libnvidia-gl-520 nvidia-driver-520 -y
#install cuda 11.8
sudo wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin
sudo mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600
sudo wget https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda-repo-ubuntu2204-11-8-local_11.8.0-520.61.05-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu2204-11-8-local_11.8.0-520.61.05-1_amd64.deb
sudo cp /var/cuda-repo-ubuntu2204-11-8-local/cuda-*-keyring.gpg /usr/share/keyrings/
sudo apt-get update
sudo apt-get -y install cuda
rm cuda-ubuntu2204.pin
rm cuda-repo-ubuntu2204-11-8-local_11.8.0-520.61.05-1_amd64.deb
echo "Install completed! Run: 'sudo reboot now' and then after reboot run 'nvidia-smi' and 'nvtop' to confirm that the GPU is recognized."
- Copy and paste the above into a file called `tryfixgpu.sh
- Then run
sudo chmod +x tryfixgpu.sh
- Then run the script
sudo ./tryfixgpu.sh
Install version 520 of the graphics driver
you sh installing 535
The following NEW packages will be installed:
dctrl-tools dkms libnvidia-cfg1-535 libnvidia-common-520 libnvidia-common-535 libnvidia-decode-535
libnvidia-encode-535 libnvidia-extra-535 libnvidia-fbc1-535 libnvidia-gl-520 libnvidia-gl-535
nvidia-compute-utils-535 nvidia-dkms-535 nvidia-driver-520 nvidia-driver-535 nvidia-firmware-535-535.183.01
nvidia-kernel-common-535 nvidia-kernel-source-535 nvidia-prime nvidia-settings nvidia-utils-535 pkg-config
python3-xkit screen-resolution-extra xserver-xorg-video-nvidia-535
you sh installing 535
Weird. For me it’s installing 520
I get this error even after trying the fixen given by @filmo and @mkabatek.
I have even tried to install 515, 525, 535.
i have installed ubuntu 20.04
can anyone please help. @MihailCosmin @filmo @mkabatek