Here is a detailed summary of the video transcript in Markdown format, broken down into sections for better readability:
Introduction
- The session is about "Driving Innovation and Results with High-Performance Computing on AWS".
- The speaker, Shas Tali, leads the worldwide go-to-market teams for advanced computing, including high-performance computing, accelerated computing, and quantum computing workloads.
- The session will cover common HPC workloads, key HPC services on AWS, customer journeys, and the convergence of HPC and AI workloads.
Common HPC Workloads
- HPC is used across various industries, such as automotive, aerospace, healthcare, life sciences, weather and climate, semiconductor design, energy, financial services, and academic research.
- These workloads have different compute and throughput characteristics, including tightly coupled and loosely coupled workloads, as well as accelerated computing and visualization workloads.
AWS HPC Services
- The HPC stack on AWS includes compute, storage, networking, orchestration, and applications.
- AWS offers a wide range of EC2 instance types, including custom-built HPC instances like HPC 7A, HPC 7G, and HPC 6ID, as well as GPU instances like P5 and G6.
- The Elastic Fabric Adapter (EFA) provides low-latency, high-bandwidth networking for HPC applications.
- Storage options include file systems like FSx for Lustre and FSx for NetApp ONTAP.
- Orchestration services include AWS Batch, AWS ParallelCluster, and AWS Parallel Computing Service.
- Visualization and remote desktop capabilities are provided through services like NICE DCV.
Security and Compliance
- AWS provides a secure infrastructure for running mission-critical HPC workloads, with a focus on security, identity, detection, networking, data protection, and compliance.
Customer Journeys
Merck's Journey
- Merck's HPC team has been in place since the early 1990s, with mature workloads on-premises.
- Merck's goals for moving to the cloud include enabling user adoption, improving metrics and cost transparency, and reducing technical debt.
- Merck's approach includes customizing Open OnDemand for user access, replicating their on-premises environment for a lift-and-shift migration, and leveraging cloud services for data lifecycle management and notebook workloads.
Physics X's Journey
- Physics X is building AI to accelerate innovation in the design, manufacturing, and operation of complex physical products and machines.
- They use large physics models (LPMs) to learn the behavior of physical processes, allowing for faster iterations and more design exploration compared to traditional CAE simulations.
- Physics X's architecture on AWS includes using AWS ParallelCluster with Slurm for HPC workloads and AWS Batch for machine learning workloads, leveraging services like EFA and FSx for Lustre.
Convergence of HPC and AI
- The convergence of HPC and AI is evident in weather and climate modeling, where physics-based simulations are being combined with ML-infused models like Amazon's Predix, NVIDIA's Earth Forecast, and others.
- AWS has collaborated with NVIDIA to optimize the Earth2 platform for running weather and climate modeling on AWS, leveraging real-time weather predictions for downstream applications like energy trading.
Conclusion
- AWS has a robust partner ecosystem of ISVs, hardware partners, and consulting partners to support customers in their HPC and advanced computing journeys.
- AWS has been recognized as the best cloud HPC platform for seven consecutive years at the Supercomputing Conference.