Performance Evaluation & Benchmarking of AI Systems

AI systems, comprising application and computing components, demand efficient performance for optimal operation. Application systems focus on solving domain problems using AI techniques, while computing systems handle data-driven models. Effective performance engineering involves a deep understanding of both areas, from hardware architecture to software design. This knowledge is crucial for various roles within the AI ecosystem, including sales, marketing, computer architecture, and software development. Despite its significance, performance engineering is often overlooked leading to suboptimal system design and operation. This abstract explores the importance of performance engineering and benchmarking in ensuring the efficiency and effectiveness of AI systems. This session will provide a clear understanding and practical framework for effectively utilizing oneAPI. Without a solid grasp of best practices and strategies in this evolving field, practitioners may struggle to optimize performance and fully leverage the capabilities of their computing systems This session will delve into the critical aspects of AI computing systems, focusing on performance engineering, optimization strategies, and benchmarking.