As the demand for GPU-accelerated workloads grows, Kubernetes has become essential for managing containerized applications that rely on GPUs. However, scheduling GPU resources introduces unique challenges, such as inefficient resource utilization, vendor-specific differences, and the need for fine-grained resource management.

Starting with how GPUs have become an integral part of modern clusters, we will dive deep into the key components of GPU scheduling in Kubernetes, architecture and scheduling policiy of native Kube scheduler and some of the prominent challenges it face as of today. This talk further explores how MIG enables partitioning of single GPU to multiple instances, DRA enhances GPU management in kubernetes and the concept of Fractional GPUs - how these transform the whole process of managing and scheduling GPUs in K8 clusters

Attendees will gain insights into how these work in Kubernetes along with best practices for managing GPU resources in large-scale environments.