johndpope/LinuxCUDAtoolkits.md

## LinuxCUDAtoolkits.md

      
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              LinuxCUDAtoolkits.md
            
          
    Remove previous NVIDIA drivers if needed:

sudo dpkg -P $(dpkg -l | grep nvidia-driver | awk '{print $2}')
sudo apt autoremove
sudo lshw -C display
NVIDIA Apmere cards including 3070, 3080 and 3090 dos not work with CUDA 10.
You have to use CUDA 11.0 or higher.
Right now, the only way to do so is by installing tf-nightly or building yourself.
Works with TensorFlow version 2.5


##Install proper NVIDIA driver:
sudo ubuntu-drivers devices
sudo ubuntu-drivers autoinstall
Install CUDA toolkit: 11.4


wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin

sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600

sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub

sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/ /"

sudo apt-get update
sudo apt-get -y install cuda-11.4

Install CUDNN dynamic libraries:


Download CUDNN from : [GoogleDrive] (https://drive.google.com/file/d/1tepluwCf-5FgKQy8DvK4uivzSHZehkHa/view?usp=sharing)

 
 tar -xzvf cudnn-10.1-linux-x64-v7.6.5.32.tgz

 sudo cp cuda/include/cudnn*.h /usr/local/cuda/include
 
 sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda/lib64
 
 sudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*


OR use Anaconda:


Create virtual environment 'cuda':
conda create -n cuda -c nvidia -c conda-forge \ -c defaults python=3.8 codatoolkit=10.1


Install compatible version of CUDNN:
conda install -c anaconda cudnn=7.6.5


Update environment variable

vim ~/.bashrc

Append the following lines:


# CUDA related exports
export PATH=/usr/local/cuda-10.1/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-10.1/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

export PATH=/usr/local/cuda-11.2/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-11.2/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

# cubalas

export CPLUS_INCLUDE_PATH=$CPLUS_INCLUDE_PATH:/usr/local/cuda-10.2/targets/x86_64-linux/include/
export PATH=/usr/local/cuda-10.2/targets/x86_64-linux/include/${PATH:+:${PATH}}

export LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}"
export PATH="/usr/local/cuda/bin:${PATH:+:${PATH}}"
export LIBRARY_PATH="/usr/local/cuda-10.1/lib64:${LIBRARY_PATH:+:${LIBRARY_PATH}}


export PATH=/usr/local/cuda-11.1/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-11.1/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
"


Create CUDA library Path file and append the following text:
sudo touch /etc/profile.d/cuda.sh


CUDAVER=cuda-11.4

export CUDA_HOME=/usr/local/cuda
export PATH=/usr/local/$CUDAVER/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/$CUDAVER/lib:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=/usr/local/$CUDAVER/lib64:$LD_LIBRARY_PATH
export CUDA_PATH=/usr/local/$CUDAVER
export CUDA_ROOT=/usr/local/$CUDAVER
export CUDA_HOME=/usr/local/$CUDAVER
export CUDA_HOST_COMPILER=/usr/bin/gcc-9


Update changes to ENV valiable:
source ~/.bashrc
source /etc/profile.d/cuda.sh


The NVCC should have the following config:

nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2021 NVIDIA Corporation
Built on Wed_Jun__2_19:15:15_PDT_2021
Cuda compilation tools, release 11.4, V11.4.48
Build cuda_11.4.r11.4/compiler.30033411_0