Part of the TPC Seminar Series

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Abstract:

Large-scale vision foundation models demand substantial computing resources. In this talk, we highlight the challenges of scaling Vision Transformer (ViT) architectures to enable hardware efficiency, multi-modality support, and computational scalability. We present approaches to enhance both efficiency and scalability, key enablers for accelerating AI-driven scientific discovery on supercomputers at HPC facilities.

Biography:

Mohamed Wahib is a team leader of the “High Performance Artificial Intelligence Systems Research Team” at RIKEN Center for Computational Science (R-CCS), Kobe, Japan. Prior to that he worked as a senior scientist at AIST/TokyoTech Open Innovation Laboratory, Tokyo, Japan. He received his Ph.D. in Computer Science from Hokkaido University, Japan. His research interests revolve around the central topic of high-performance programming systems, in the context of HPC and AI. He is actively working on several projects including AI-based science, as well as high-level frameworks for programming traditional scientific applications.