Introduction to CUDA Programming for Python Developers

1. Rust-CUDA

   1 42 4,254 8.8 Rust

   Ecosystem of libraries and tools for writing and executing fast GPU code fully in Rust.

   

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3. optillm

   2 12 2,161 9.7 Python

   Optimizing inference proxy for LLMs

   

   It's definitely possible to focus on the CUDA/GPU side without diving deep into the math. Understanding parallel computing principles and memory optimization is key. I've found that focusing on specific use cases, like optimizing inference, can be a good way to learn. On that note, you might find https://github.com/codelion/optillm useful – it optimizes LLM inference and could give you practical experience with GPU utilization. What kind of AI applications are you most interested in optimizing?

4. clojurecuda

   3 1 184 5.2 Clojure

   Clojure library for CUDA development

   

   May I plug-in with ClojureCUDA, a high-level library that lets you write CUDA with almost no overhead, but write it interactive Clojure REPL.

   https://github.com/uncomplicate/clojurecuda

   There's also tons of free tutorials at https://dragan.rocks

5. deep-diamond

   4 17 435 6.1 Clojure

   A fast Clojure Tensor & Deep Learning library

   

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