Run Ray on TPU, Part 1: The foundations- Google Developers Blog

In 30 Sekunden

Was passiert ist

Ray 2.55 now treats Google Cloud TPUs as first-class accelerators with official APIs, letting Python developers scale distributed workloads on TPU slices via Google Kubernetes Engine.

Warum es zählt

Matters for engineers already using Ray with GPUs who want to run the same code on TPUs, or those building distributed AI workloads needing TPU compute.

Achtung

TPU chips must stay on one intact slice via dedicated interconnect; the slice_placement_group API is marked alpha, so its surface may change between releases.