Repository to demo GPU Partitioning with Time Slicing, MPS, MIG and others with Red Hat OpenShift AI and NVIDIA GPU Operator . Check also the OpenShift GPU Partitioning Methods Docs if you want to know more. Table of Contents GPU Partitioning Overview Time-Slicing Multi-Instance GPU (MIG) Multi-Process Service (MPS) - Not yet available Pros and Cons of GPU Partitioning Methods Requirements Usage Time-Slicing MIG-Single MIG-Mixed MPS NO GPU Partitioning - Default Validate and Check GPU Partitioning Testing with LLMs Install Nvidia GPU Operator from Staging / Development Other Interesting Links 0. Why GPU Partitioning? GPU partitioning can help optimize GPU resource utilization across your clusters, though it might not be necessary if you have a single GPU with sufficient memory for your specific needs. By partitioning GPUs, we can allocate the right-sized GPU resources to each workload, ensuring that each application gets exactly what it needs to perform efficiently.…