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#!/bin/bash | |
## This gist contains instructions about cuda v11.2 and cudnn8.1 installation in Ubuntu 20.04 for Pytorch 1.8 & Tensorflow 2.7.0 | |
### steps #### | |
# verify the system has a cuda-capable gpu | |
# download and install the nvidia cuda toolkit and cudnn | |
# setup environmental variables | |
# verify the installation | |
### | |
### If you have previous installation remove it first. | |
sudo apt-get purge nvidia* | |
sudo apt remove nvidia-* | |
sudo rm /etc/apt/sources.list.d/cuda* | |
sudo apt-get autoremove && sudo apt-get autoclean | |
sudo rm -rf /usr/local/cuda* | |
### to verify your gpu is cuda enable check | |
lspci | grep -i nvidia | |
### gcc compiler is required for development using the cuda toolkit. to verify the version of gcc install enter | |
gcc --version | |
# system update | |
sudo apt-get update | |
sudo apt-get upgrade | |
# install other import packages | |
sudo apt-get 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 | |
# install nvidia driver with dependencies | |
sudo apt install libnvidia-common-470 | |
sudo apt install libnvidia-gl-470 | |
sudo apt install nvidia-driver-470 | |
sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/7fa2af80.pub | |
echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64 /" | sudo tee /etc/apt/sources.list.d/cuda.list | |
sudo apt-get update | |
# installing CUDA-11.2 | |
sudo apt install cuda-11-2 | |
# setup your paths | |
echo 'export PATH=/usr/local/cuda-11.2/bin:$PATH' >> ~/.bashrc | |
echo 'export LD_LIBRARY_PATH=/usr/local/cuda-11.2/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc | |
source ~/.bashrc | |
sudo ldconfig | |
# install cuDNN v8.1 | |
# in order to download cuDNN you have to be regeistered here https://developer.nvidia.com/developer-program/signup | |
# then download cuDNN v8.1 form https://developer.nvidia.com/cudnn | |
CUDNN_TAR_FILE="cudnn-11.2-linux-x64-v8.1.1.33.tgz" | |
wget https://developer.nvidia.com/compute/machine-learning/cudnn/secure/8.1.1.33/11.2_20210301/cudnn-11.2-linux-x64-v8.1.1.33.tgz | |
tar -xzvf ${CUDNN_TAR_FILE} | |
# copy the following files into the cuda toolkit directory. | |
sudo cp -P cuda/include/cudnn.h /usr/local/cuda-11.2/include | |
sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda-11.2/lib64/ | |
sudo chmod a+r /usr/local/cuda-11.2/lib64/libcudnn* | |
# Finally, to verify the installation, check | |
nvidia-smi | |
nvcc -V | |
# install Pytorch (an open source machine learning framework) | |
# I choose version 1.8.0 because it is stable and compatible with CUDA 11.2 Toolkit and cuDNN 8.1 | |
pip3 install pytorch==1.8.0 torchvision==0.9.0 |
I just discovered all these commands, so sorry that the script stopped working now. Apparently the links have changed. I will try to create an updated one when I install it in a new system.
Line 49 is not working sudo apt install cuda-11-2
Change line 44 to:
sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/3bf863cc.pub
its work for me
Line 64 gives error : gzip: stdin: not in gzip format
tar: Child returned status 1
tar: Error is not recoverable: exiting now
can any one help?
Line 64 gives error : gzip: stdin: not in gzip format tar: Child returned status 1 tar: Error is not recoverable: exiting now
can any one help?
This worked for me:
Using wget is not working since, you need to login to nvidia-developer to download the zip file from the archive.
Create an account in nvidia-developer and download manually.
I only succeeded by installing the CUDA toolkit part from .tgz (and not installing the driver from that non-apt package)