Difference between revisions of "Nvidia Drivers and CUDA"

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*sudo systemctl set-default graphical.target
 
*sudo systemctl set-default graphical.target
 
*sudo reboot now
 
*sudo reboot now
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[[Category:AI & Machine Learning]]

Latest revision as of 13:44, 28 November 2022

Installing NVIDIA Driver (Ubuntu 16.04)

wget http://us.download.nvidia.com/XFree86/Linux-x86_64/410.57/NVIDIA-Linux-x86_64-410.57.run
chmod +x NVIDIA-Linux-x86_64–410.57.run
sudo ./NVIDIA-Linux-x86_64–410.57.run --no-x-check


Installing CUDA 10.0 on Ubuntu 16.04

General Info

check nvidia drivers and cuda version:

nvcc --version 
nvidia-smi
  • nvidia-settings


Download the latest version of CUDA which is compatible with your version of drivers installed. For example, if you have installed a driver of 410 version, CUDA 10 can be installed, for 375 CUDA 8 should be installed. CUDA 10.0 (10.0.130) >= 410.48 driver

  • Avoid CUDA 10.1!!! It conflicts with tensorflow-gpu


Steps:

1. Uninstall previous versions of CUDA

sudo apt-get --purge remove cuda-10.1
sudo apt-get remove nvidia-cuda-toolkit

2. Then install:

sudo dpkg -i cuda-repo-ubuntu1604-10-0-local-10.0.130-410.48_1.0-1_amd64.deb
sudo apt-key add /var/cuda-repo-10-0-local-10.0.130-410.48/7fa2af80.pub
sudo apt-get update
sudo apt-get install cuda-10-0


Steps and installation file downloaded from here: https://developer.nvidia.com/cuda-10.0-download-archive?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1604&target_type=deblocal

3. Specify your cuda path (cuda 10.0 example)

sudo nano /home/interactionstation/.bashrc

locate the two lines regarding cuda9 (in case it was previously installed), comment them out and include instead:

export PATH=/usr/local/cuda-10.0/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-10.0/lib64:$LD_LIBRARY_PATH

4. Save the file


5. Restart the computer


Installing cuDNN (for ubuntu 16.04, cuda 10-0)

1.Download the following:

- runtime:

https://developer.nvidia.com/compute/machine-learning/cudnn/secure/7.6.4.38/Production/10.0_20190923/Ubuntu16_04-x64/libcudnn7-dev_7.6.4.38-1%2Bcuda10.0_amd64.deb

- developer

https://developer.nvidia.com/compute/machine-learning/cudnn/secure/7.6.4.38/Production/10.0_20190923/Ubuntu16_04-x64/libcudnn7_7.6.4.38-1%2Bcuda10.0_amd64.deb

- samples

https://developer.nvidia.com/compute/machine-learning/cudnn/secure/7.6.4.38/Production/10.0_20190923/Ubuntu16_04-x64/libcudnn7-doc_7.6.4.38-1%2Bcuda10.0_amd64.deb

2. and then, navigate to your <cudnnpath> directory containing cuDNN Debian file.

3. Install the runtime library, for example:

sudo dpkg -i runtimefile.deb

4. Install the developer library, for example:

sudo dpkg -i devlib.deb

5. Install the code samples and the cuDNN Library User Guide, for example:

sudo dpkg -i codesamples.deb


More info: https://medium.com/@muskulpesent/install-cuda-on-ubuntu-16-04-67ec087f8561 https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1604&target_type=deblocal

Installing CUDA 9.0 on Ubuntu 16.04 (Old! Using 10.0, Nov 2019)

Resources used:

  • ==Installing nvidia drivers on Ubuntu 16.04 (deprecated!) ==
  • Set Ubuntu to boot on console mode. Type:
  • sudo apt-get install systemd
  • sudo systemctl set-default multi-user.target
  • sudo reboot now
  • Login and in console mode, type:
  • sudo add-apt-repository ppa:graphics-drivers/ppa
  • sudo apt update
  • sudo apt upgrade
  • For GeForce 1070Ti (07/2018), type:
  • sudo apt-get install nvidia-390
  • Re-set Ubuntu to boot on graphical mode. Type:
  • sudo systemctl set-default graphical.target
  • sudo reboot now