MS3: Convergence of Artificial Intelligence and High-Performance Computing for Computational Fluid Dynamics (AI + HPC4CFD PT. 3)

Guillaume Houzeaux, Corentin Lapeyre, and Mario Rüttgers

Abstract

Artificial Intelligence (AI) technologies are penetrating into all sectors of research and industry. They automate and accelerate processes, and uncover new unseen relations in huge datasets. The successful AI+HPC4CFD ParCFD 2022 and 2023 mini-symposia already impressively showed that the Computational Fluid Dynamics (CFD) community drastically benefits from these technologies. AI methods and notably deep learning techniques are used to develop new models for CFD, e.g., reduced-order models, surrogates, and closure models aiming at efficiently modeling complex physics that are otherwise expensive to compute. Furthermore, reinforcement learning algorithms can be used for flow control applications, while receiving feedback from CFD solvers after an action. The quality of these methods is often a function of both the quantity and the accuracy of the underlying data used for training as well as the physical constraints imposed on the training. The generation and processing of high fidelity simulation data necessitates the application of High-Performance Computing (HPC) systems, with an increasing number CFD solvers running on both CPU and GPU partitions. Modular and heterogeneous systems with accelerator and/or specialized AI-components as blueprints for upcoming Exascale systems have the potential to deal with the demands of complex and intertwined simulations and AI-data processing workflows. This minisymposium aims at continuing the successful 2022 and 2023 AI+HPC4CFD minisymposia. It will gather experts in the fields of development and application of parallel CFD methods incorporating novel AI methods, and pure AI method developers contributing to the fields of CFD and HPC alike. It will again offer a platform for discussion and exchange in the context of the convergence of AI and HPC with respect to parallel CFD methods that could benefit from the power of next-generation Exascale computing systems.

Guillaume Houzeaux - Barcelona Supercomputing Center (BSC)

Since 2005, Dr. Guillaume Houzeaux is the leader of the team ”Physical and Numerical Modeling” at Barcelona Supercom- puting Center, Spain. His research focusses on High Performance Computational Mechanics. He is one of the main architects of Alya HPC simulation code, with application in aeronautics, combustion, wind energy and biomedicine.

Corentin Lapeyre - Nvidia, France

Dr. Corentin Lapeyre is a research scientist and engineer with a background in computational physics and artificial intelligence. He spent 6 years as an academic researcher at CERFACS, a french high-performance computing lab, supervising a dozen PhD students as well as postdocs. There, he built a scientific machine learning team, and worked closely with the aerospace and energy industries. Recently, he joined Nvidia’s Strategic Researcher Engagement team to facilitate the adoption of accelerated computing technologies to boost science and R&D.

Mario Rüttgers - Jülich Supercomputing Centre , Forschungszentrum Jülich GmbH

Dr. Mario Rüttgers is a member of the Simulation and Data Laboratory “Highly Scalable Fluids & Solids Engineering” (SDL FSE) of JSC since 2019. In 2023, he received his Ph.D. degree at the Institute of Aerodynamics and Chair of Fluid Mechanics, RWTH Aachen University. His research focuses on combining computational fluid dynamics and machine learning techniques.