Run Ray on TPU, Part 2: Ray AI libraries
This second installment explores how Ray’s higher-level libraries—Serve, Data, and Train—abstract the complexities of running AI workloads on Google's TPU slices. Ray Serve uses a simple topology configuration to correctly gang-schedule large multi-host models, while Ray Data eliminates…
No discussion yet. Be the first to share your thoughts!