Enterprise AI
Now generally available: GKE dynamic slicing for higher resilience, and efficiency for TPUs
Dynamic slicing targets resilience and TPU efficiency for large-scale AI workloads
Running large-scale AI workloads on TPU and Google Kubernetes Engine (GKE) requires infrastructure that adapts as fast as your models change.
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Google Cloud AI Blog
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6 min
Google Cloud AI Blog
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Making GKE dynamic slicing generally available gives teams a way to adapt infrastructure for large-scale TPU workloads. Greater resilience and TPU efficiency could help keep changing AI workloads running effectively.
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