Tutorials
Hands-on tutorials for learning HAMi by doing. Each lab is a step-by-step exercise with real, captured outputs: you build a cluster, install HAMi, and verify GPU partitioning behavior yourself.
Concepts
Background knowledge that the labs build on.
- GPU Software Stack Overview: the 5 layers from hardware to Kubernetes scheduling
- Understanding GPU Drivers: kernel modules, NVML, and how to troubleshoot from the bottom up
- HAMi Cluster Architecture: every component in a HAMi cluster and what breaks without it
Labs
Build a GPU Kubernetes cluster from scratch on a cloud VM and install HAMi.
Learn the HAMi control plane on a laptop, no GPU required.
Run multiple Pods on one GPU with enforced VRAM and compute limits.
The same outcome through Kubernetes-native Dynamic Resource Allocation (experimental).
Simulate 8 A100 GPUs with HAMi scheduling features, no real GPU needed.
Each lab lists its own prerequisites. Labs 3 and 4 continue from the cluster Lab 1 builds, so a single session covers all three; Lab 2 runs on any laptop with no GPU required.
