Efficient Multi-Cluster GPU Workload Management with Karmada and Volcano
Offered By: CNCF [Cloud Native Computing Foundation] via YouTube
Course Description
Overview
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.
Syllabus
Efficient Multi-Cluster GPU Workload Management with Karmada and Volcano - Kevin Wang, Huawei
Taught by
CNCF [Cloud Native Computing Foundation]
Related Courses
Моделирование биологических молекул на GPU (Biomolecular modeling on GPU)Moscow Institute of Physics and Technology via Coursera Practical Deep Learning For Coders
fast.ai via Independent GPU Architectures And Programming
Indian Institute of Technology, Kharagpur via Swayam Perform Real-Time Object Detection with YOLOv3
Coursera Project Network via Coursera Getting Started with PyTorch
Coursera Project Network via Coursera