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Programming Novel AI Accelerators for Scientific Computing

DescriptionScientific applications are increasingly adopting artificial intelligence (AI) techniques to advance science. There are specialized hardware accelerators designed and built to run AI applications efficiently. With a wide diversity in the hardware architectures and software stacks of these systems, it is challenging to understand the differences between these accelerators, their capabilities, programming approaches, and how they perform, particularly for scientific applications. In this tutorial, we will cover an overview of the AI accelerators landscape, focusing on SambaNova, Cerebras, Graphcore, Groq, and Intel Gaudi systems along with architectural features and details of their software stacks. Through hands-on exercises, attendees will gain practical experience in refactoring code and running models on these systems, focusing on use cases of pre-training and fine-tuning open-source large language models (LLMs) and deploying AI inference solutions relevant to scientific contexts. The tutorial will provide attendees with an understanding of the key capabilities of emerging AI accelerators and their performance implications for scientific applications.

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