NHR PerfLab Seminar: The Artificial Scientist: In-Transit Machine Learning of Plasma Simulations (May 6, online)
Speaker: Sunita Chandrasekaran, Department of Computer and Information Sciences, University of Delaware
Date and time: Tuesday, May 6, 2025, 2:00 p.m. CEST
Zoom: https://go-nhr.de/perflab-seminar
Abstract
With the rapid advancements in the computer architecture space, the migration of legacy applications to new architectures remains a continuous challenge. To effectively navigate this ever-evolving hardware landscape, software and toolchains must evolve in tandem, staying ahead of the curve in terms of architectural innovation. While this synchronization between hardware and software is inherently complex, it is essential for fully harnessing the potential of advanced hardware platforms. In this context, a marriage between HPC and AI is gaining increasing prominence. By effectively orchestrating the workflow of HPC and AI, we can not only accelerate scientific progress but also achieve significant gains in computational efficiency. One promising strategy to further optimize large-scale workflows is to stream simulation data directly into machine learning (ML) frameworks. This approach bypasses traditional file system bottlenecks, allowing for the transformation of data in transit—asynchronously with both the simulation process and model training.
This talk will explore these strategies in detail, demonstrating the synergy between hardware innovation and software adaptation. Using real-world scientific applications as a case study, Plasma-in-Cell on GPU, i.e. PIConGPU will showcase how these techniques can be applied at scale to drive both scientific and computational advancements.
Short Bio
Sunita Chandrasekaran is an Associate Professor with the Department of Computer and Information Sciences at the University of Delaware, USA and runs the Computational Research Programming Lab. She co-directs the AI Center of Excellence. She also leads the NSF Democratization Access to RSE (DARSE) program at UD. Her research spans high performance computing, exascale computing, machine learning and interdisciplinary science. She is a member of the DOE Advanced Scientific Computing Advisory Committee (ASCAC) committee and the Vice Chair for the State of Delaware AI commission. She has held various leadership positions in HPC conferences and workshops over the past several years.
For a list of past and upcoming NHR PerfLab seminar events, please see: https://hpc.fau.de/research/nhr-perflab-seminar-series/