Google Cloud Platform Blog: GPUs as a service with Kubernetes Engine are now generally available

Google Cloud Platform Blog

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GPUs as a service with Kubernetes Engine are now generally available

Tuesday, June 19, 2018

By Yoshi Tamura, Product Manager, Google Kubernetes Engine[Editor's note: This is one of many posts on enterprise features enabled by Kubernetes Engine 1.10. For the full coverage, follow along here.]Google Kubernetes EngineintroducedPreemptible GPUshereOcado “GPU-attached nodes combined with Kubernetes provide a powerful, cost-effective and flexible environment for enterprise-grade machine learning. Ocado chose Kubernetes for its scalability, portability, strong ecosystem and huge community support. It’s lighter, more flexible and easier to maintain compared to a cluster of traditional VMs. It also has great ease-of-use and the ability to attach hardware accelerators such as GPUs and TPUs, providing a huge boost over traditional CPUs.”
— Martin Nikolov, Research Software Engineer, Ocado

Node Pools allow your existing cluster to use GPUs whenever you need.

Cluster Autoscaler automatically creates nodes with GPUs whenever pods requesting GPUs are scheduled, and scale down to zero when GPUs are no longer consumed by any active pods.

Taint and toleration technology ensures that only pods that request GPUs will be scheduled on the nodes with GPUs, and prevents pods that do not require GPUs from running on them.