After completing the HAMi installation, the cluster is no longer an ordinary Kubernetes cluster, it becomes an AI infrastructure platform with GPU virtualization capabilities. This document breaks down the responsibilities and dependencies of every layer and every component in the cluster after installation.
When you use a GPU on a server, you are not dealing with a single piece of software or hardware. Instead, you are working with an entire software stack built around NVIDIA GPUs. From the lowest-level physical hardware to the highest-level Kubernetes scheduling, it can be roughly divided into 5 layers:
Before using a GPU, you first need to verify that the GPU driver is properly loaded into the kernel. This document explains how to check GPU driver status and understand the architecture of NVIDIA kernel modules.
