#GPUs and TPUs

This comprehensive guide features a wide range of JAX libraries, projects, and resources suited for researchers in high-performance machine learning using GPUs and TPUs. It includes neural network libraries such as Flax, Haiku, and Objax, along with specialized tools like Jraph for graph neural networks and NumPyro for probabilistic programming. The guide also highlights pioneering libraries like FedJAX for federated learning and Levanter for scalable model deployment. Discover models, projects, tutorials, videos, and community resources that make this an essential resource for maximizing the use of JAX.