[Subproject Application]: CNCF Batch & HPC System Initiative

### Subproject Name

HPC with Kubernetes

### Parent Group

TAG Workloads Foundation

### Mission/Purpose

Innovate with and around Kubernetes to enable running of batch AI/Inference/HPC workloads in the cloud

### Scope

This Subproject will involve improving data-aware scheduling in Kubernetes, benchmarking different workloads with existing and new scheduling mechanisms, and creating well-defined definitions that can be consumed by the HPC and Kubernetes communities.

### Goals and Objectives

We will work on multiple initiatives to make batch-type workloads work more natively in the cloud. These include the following already-started interest groups: data-aware scheduling with API spec, benchmarking AI systems in the cloud, user stories around batch workloads in the cloud, and clear definitions around this space.

### Proposed Leads

Alex Scammon, Marlow Warnicke, and Abhishek Malvankar

### Initial Participants/Contributors

G-Research, SchedMD, IBM Research ....

### Benefits to CNCF

Batch workloads are becoming increasingly important, especially around training and multi-node inference.This group is a cohesive group of people trying to make these work more natively in the cloud.

### Alignment with Parent Group

We handle high-performance workloads and all the projects therein.

### Proposed Communication Channels

_No response_

### Proposed Initial Deliverables (if applicable)

_No response_

### Potential Future Work/Evolution

_No response_

### Sponsoring CNCF Project or TOC Member (if applicable)

_No response_

### Additional Information

_No response_