Unlocking New Pose in HPC - Containerization, Cloud, and GPU-based Workloads

Overview

Join us as we delve into the cutting-edge techniques in high-performance computing (HPC). This insightful event will provide an in-depth exploration of containerization and the role of cloud and GPU-based workloads.

Learn how Kubernetes is revolutionizing resource management in HPC, enhancing the efficiency and scalability of your AI projects.

Discover the benefits of GPU virtualization and gain insights into custom scheduling and monitoring that ensure optimal performance and deployment.

This presentation, available on YouTube, is geared toward professionals and enthusiasts in the fields of artificial intelligence and high-performance computing. Don't miss this opportunity to broaden your understanding and leverage the latest innovations in technology.

Syllabus

• Introduction to HPC and AI Workloads
Overview of HPC and its relevance to AI
Introduction to GPU-based workloads
The role of cloud computing in HPC
• Fundamentals of Containerization
Basics of containers and their benefits in HPC
Container orchestration tools overview
• Deep Dive into Kubernetes
Kubernetes architecture and components
Setting up a Kubernetes cluster for HPC
Deploying and managing applications with Kubernetes
Resource management techniques in Kubernetes
• GPU Virtualization and Utilization
Understanding GPU architecture and capabilities
Tools and techniques for GPU virtualization
Best practices for maximizing GPU utilization in HPC
• Custom Scheduling in HPC
Introduction to custom schedulers in Kubernetes
Designing custom scheduling algorithms for optimized performance
Hands-on exercises with Kubernetes scheduling
• Monitoring and Performance Tuning
Monitoring tools and techniques for Kubernetes
Analyzing performance bottlenecks in GPU-based workloads
Techniques for effective performance tuning
• Cloud Integration with HPC
Exploring cloud service providers and their offerings for HPC
Design patterns for hybrid cloud HPC environments
Case studies of successful cloud-enabled HPC deployments
• Case Studies and Real-World Applications
Analyzing real-world AI applications using HPC
Lessons learned from deploying AI workloads in HPC clusters
• Future Trends and Innovations in HPC
Emerging technologies and their potential impact
Research directions in AI and HPC integration
• Course Conclusion
Recap of key concepts learned
Final project: designing a scalable AI workload deployment strategy using Kubernetes and cloud resources.

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Subjects

Conference Talks