Could Someone Give me Advise on Optimizing Performance on Clear Linux for AI/ML Workloads?

General Discussion
1

Hello there,

I recently transitioned to Clear Linux from another distribution due to its reputation for performance and efficiency; especially in the realm of data science and machine learning. Although; I am still navigating through some challenges and would greatly appreciate any guidance you can provide.

While I have noticed some performance improvements, I feel there is more potential that I’m not tapping into. Are there specific optimizations or configurations I should be aware of?

Setting up CUDA and cuDNN has been somewhat tricky. I followed the official NVIDIA instructions; but I am uncertain if it’s fully optimized for Clear Linux. Any tips or detailed guides on ensuring optimal setup would be valuable.

Occasionally; I encounter memory management issues where certain processes consume more resources than expected; leading to sluggish performance. Are there any Clear Linux specific tools or best practices for managing system resources efficiently?

Also; I have gone through this post; https://community.clearlinux.org/t/what-makes-clear-linux-perform-much-better-compared-to-other-distros-uipath/ which definitely helped me out a lot.

I am really excited about leveraging Clear Linux to its fullest potential and would love to hear about your experiences; recommendations; or any resources you could point me to.

Thank you in advance for your help and assistance.

2

Hi @samzyann !

Install the Nvidia driver and CUDA using @marioroy 's repo.

Python version management can be done with:

  1. miniconda
  2. If you don’t like conda, you can install pyenv with a lot of hassle because the bundles require a long time to download.

sudo swupd bundle-add devpkg-ncurses sqlite devpkg-openssl tcl-basic devpkg-readline devpkg-bzip2 devpkg-sqlite-autoconf devpkg-libffi devpkg-xz user-basic-dev

curl https://pyenv.run | bash

Add the following to ~/.bashrc

echo 'export PYENV_ROOT="$HOME/.pyenv"' >> ~/.bashrc
echo 'command -v pyenv >/dev/null || export PATH="$PYENV_ROOT/bin:$PATH"' >> ~/.bashrc
echo 'eval "$(pyenv init -)"' >> ~/.bashrc

Perhaps you can do a tutorial on installing cudNN and TensorRT libraries! :grin: