Ce qui s'est passé: Run Ray on TPU, Part 1: The foundations- Google Developers Blog

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.

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

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.

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

Google Developers · Publié le 20 juillet 2026 · 3 min de lecture

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Ce qui s'est passé: 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.
Pourquoi ça compte: 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.
Vigilance: 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.

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