Join us on August 27, 2025, for a webinar titled Methods, Tools, and Best Practices for Coupling Simulation and AI on ALCF Systems, presented by Riccardo Balin.
Coupling traditional HPC simulations with AI workloads can be challenging due to differences in programming languages, the need to use specialized AI framework libraries, data extraction and processing requirements, and the need for scalable workflows that make efficient use of the hardware. This talk will cover various methods and tools scientists can use on ALCF systems to overcome these challenges, providing both simple and real-world scientific examples that illustrate best practices for coupled HPC-AI workloads.
Riccardo Balin is an Assistant Computational Scientist in the Data Services and Workflows team at the Argonne Leadership Computing Facility. His research interests include workflows for coupling traditional HPC simulations with AI/ML training and inferencing, online (in situ) and scalable deep learning from ongoing simulations and experiments, and applying ML and data driven methods for turbulence modeling of complex aerodynamic flows.
He obtained a B.S./M.S. degree in Aerospace Engineering from the University of Colorado Boulder in 2016 and a Ph.D. in Computational Fluid Dynamics and Turbulence Modeling in 2020 from the same institution. He joined Argonne in 2021 as a postdoc under the Aurora Early Science Program supporting a project aiming to perform in situ scientific machine learning from exascale simulations of turbulent flows.
