HAMi is a CNCF Incubation project for heterogeneous GPU virtualization in Kubernetes, supporting 10+ GPU/NPU vendors.

Attendees set up HAMi on their laptop - with or without a GPU - and trace how the device plugin intercepts GPU requests, allocates vGPU resources, and integrates with the scheduler.

We follow the HAMi architecture and GPU virtualization model (project-hami.io/docs/core-concepts/gpu-virtualization), then explore the DRA integration path. Laptop with Go, kind, and a GitHub account required.

This hands-on workshop takes you from a bare cluster to a working GPU sharing setup. You'll deploy HAMi (CNCF Incubation), schedule fractional GPU workloads, and understand how scheduler policies like binpack, spread, and topology awareness change allocation behavior. Then you'll see how third-party schedulers (KAI Scheduler, Volcano) compose with HAMi's isolation layer.