Heterogeneous AI Computing Virtualization Middleware (HAMi), formerly known as k8s-vGPU-scheduler, is an "all-in-one" chart designed to manage Heterogeneous AI Computing Devices in a k8s cluster. It includes everything you would expect, such as:

Device sharing: Each task can allocate a portion of a device instead of the entire device, allowing a device to be shared among multiple tasks.

Device Memory Control: Devices can be allocated a specific device memory size (e.g., 3000M) or a percentage of the whole GPU's memory (e.g., 50%), ensuring it does not exceed the specified boundaries.

Device Type Specification: You can specify the type of device to use or avoid for a particular task by setting annotations, such as "nvidia.com/use-gputype" or "nvidia.com/nouse-gputype".

Easy to use: You don't need to modify your task YAML to use our scheduler. All your jobs will be automatically supported after installation. Additionally, you can specify a resource name other than "nvidia.com/gpu" if you prefer.