Could Someone Give me Advice on Optimizing Clear Linux for Scientific Computing Workflows?

General Discussion
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Hello there,

I am new to Clear Linux and excited to explore its potential for scientific computing tasks. I have read about its performance optimizations; and I would like to leverage it for my specific use cases; which include running computational simulations; data analysis with Python; and some light GPU-based machine learning workloads. Although; I am unsure about the best ways to set up and optimize Clear Linux for these purposes.

Are there specific bundles or software stacks you would recommend for Python-based data analysis NumPy; SciPy; pandas; etc. and simulation tools?

Clear Linux is known for its aggressive optimization does this benefit scientific libraries like BLAS, LAPACK; or TensorFlow out of the box; or are there additional tweaks I should consider?

I will be using an NVIDIA GPU for some machine learning tasks. What is the current state of NVIDIA driver support in Clear Linux; and are there any caveats I should be aware of?

Also, I have gone through this post; https://community.clearlinux.org/t/what-other-things-contribute-to-optimising-clear-linux-especially-for-web-browsers-devops which definitely helped me out a lot.

Are there any specific configurations; tools; or best practices within Clear Linux that have significantly boosted performance or usability for your scientific workflows?

Thank you in advance for your help and assistance.

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This might be a naive reply, but my impression is that Clr is already optimized to heck for all recent intel cpus. Things like gpu accelleration are usually inside packages like numpy not the os so I’m not sure about that one. however. I’ve noticed that |CL| (as it is styled) is already very optimized where other distros would avoid doing them because it breaks wide compatibility. So from one newb to another just try our your workloads and see if they’re faster!

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I agree with @cellarroot . Just keep in mind tha CL uses the -O3 optimization flag as default.

A good advice is to use Intel OneApi suit. It does not recognize Intel CL ( ??? ) but it works fine.

A couple years ago I found in github how the devs compiled the openblas packages for CL. If I find it again I will post it here.