Efficient Multi-Cluster GPU Workload Management with Karmada and Volcano

Explore efficient multi-cluster GPU workload management using Karmada and Volcano in this informative conference talk. Discover solutions to critical challenges faced when running AI/ML workloads on large-scale, heterogeneous GPU environments across multiple Kubernetes clusters. Learn about intelligent GPU workload scheduling, cluster failover support for seamless workload migration, two-level scheduling consistency and efficiency, and balancing utilization and QoS for resource sharing among workloads with different priorities. Gain insights into addressing resource fragmentation, operational costs, and cross-resource scheduling in cloud native AI platforms spanning multiple data centers and diverse GPU types.