Title

AWS re:Invent 2022 - How to maximize HPC productivity, performance, and portability (PRT220)

Summary

• Presenter: John Linford from NVIDIA, a technical product manager for CPU software.
• Topic: Maximizing high-performance computing (HPC) productivity, performance, and portability on AWS using NVIDIA HPC SDK.
• Key Points:
  • NVIDIA is known for GPUs but also offers CPUs, DPUs, and software.
  • NVIDIA HPC SDK is an all-in-one solution for building HPC applications on various hardware types, making it suitable for AWS's diverse EC2 instances.
  • The SDK includes compilers, programming models, libraries, and tools for scientific computing.
  • It supports ARM, x86, and PowerPC CPUs with or without GPUs, making it highly portable.
  • The SDK is free to use and supports AWS Graviton2 and Graviton3.
  • NVIDIA is also working on optimized math libraries for ARM CPUs, which will benefit AWS Graviton users.
  • Demonstrations showed the SDK's capabilities on EC2 instances, highlighting the performance and price advantages of different AWS instances when using the SDK.
• Demonstration:
  • Installation of NVIDIA HPC SDK on AWS Graviton3 instance.
  • Performance comparison of MiniWeather and Lulash applications across various AWS instances using different programming models.

Insights

• Productivity: The NVIDIA HPC SDK simplifies the development process by providing a unified development environment that works across different hardware configurations. This allows developers to focus on coding at a high level without worrying about hardware-specific optimizations.
• Performance: The SDK's compilers and libraries are optimized for performance, with continuous improvements over time. This means that applications built with the SDK can benefit from performance gains without additional code changes.
• Portability: The SDK's support for multiple CPU architectures and its ability to target both CPUs and GPUs with the same code base make it highly portable. This is particularly beneficial in cloud environments like AWS, where there is a wide variety of instance types.
• Cost-Effectiveness: The demonstration highlighted that using the NVIDIA HPC SDK can lead to significant price performance advantages, especially when using instances like AWS Graviton3 or GPU instances. This can be a key consideration for organizations looking to optimize their cloud spending.
• Future Developments: The upcoming optimized math libraries for ARM CPUs, which will support AWS Graviton3, indicate NVIDIA's commitment to expanding the capabilities of the SDK. This will likely further enhance the performance and portability of HPC applications on AWS.
• Strategic Insights: The talk suggests that organizations should consider their specific application requirements and choose the appropriate AWS instance type and programming model to maximize performance and cost-efficiency. The NVIDIA HPC SDK provides the flexibility to make these choices without being locked into a particular hardware configuration.