Organization

Argonne National Laboratory
Presenters / Organizers
Riccardo Balin
Shivam Barwey
Franck Cappello
Anshu Dubey
Sam Foreman
Rinku Gupta
Aidan Hamilton
Valerie Hayot-Sasson
Robert Jacob
Xiao-Yong Jin
Murat Keceli
Tom Klosterman
Michael Kruse
Bethany Lusch
Gina M. Magnotti
Vijay Mahadevan
Romit Maulik
Sudeepta Mondal
Bogdan Nicolae
Jared O'Neal
James Osborn
Arvind Ramanathan
Johann Rudi
Ashka Shah
Filippo Simini
Rick Stevens
Roberto Torelli
Alvaro Vazquez-Mayagoitia
Venkatram Vishwanath
Klaus Weide
Session Chairs
Ramesh Balakrishnan
Riccardo Balin
Anshu Dubey
Rinku Gupta
Vijay Mahadevan
Arvind Ramanathan
Presentations
Minisymposium
A Scale Separation Approach: A Machine-Learned Surrogate Model for an Injector Coupled with Spray Simulations
Computer Science, Machine Learning, and Applied Mathematics 

Paper
Causal Discovery and Optimal Experimental Design for Genome-Scale Biological Network Recovery
Life Sciences
Minisymposium
Code and Community: Challenges and Opportunities
Computer Science, Machine Learning, and Applied Mathematics 

Minisymposium
Current State-Of-The-Art Coupling Algorithms, Hurdles, and Approaches for Next-Generation Earth System Models
Climate, Weather and Earth Sciences
Minisymposium
General Discussion
Computer Science, Machine Learning, and Applied Mathematics 

Minisymposium
Generative Modeling and Smarter Sampling for Lattice Gauge Theories
Computer Science, Machine Learning, and Applied Mathematics 

Minisymposium
Graph Neural Networks for Interpretable Data-Based Modeling of Fluid Flows
Computer Science, Machine Learning, and Applied Mathematics 

Minisymposium
Group Discussion: How Large Language Models Will Influence Autonomous Discovery
Life Sciences
Keynote
Public Lecture
IK02 - A View of Post-Exascale Computational Science and the Emerging Mix of HPC, AI, and Quantum
Minisymposium
LLVM’s OpenMP Loop Transformations to Enhance Locality in OpenMP Loop Scheduling
Computer Science, Machine Learning, and Applied Mathematics 

Minisymposium
MiniGAP: A Proxy App for ML Prediction of Molecular Properties
Computer Science, Machine Learning, and Applied Mathematics 

Minisymposium
Online Learning of Sub-Grid Stress Models for Large Eddy Simulation of Wall Bounded Turbulent Flows
Computer Science, Machine Learning, and Applied Mathematics 

Poster
P34 - Interpretable Compression of Fluid Flows Using Graph Neural Networks
Minisymposium
Performance Portability Using a Tool-Chain to Exploit Separation of Concerns
Computer Science, Machine Learning, and Applied Mathematics 

Minisymposium
Scalable GPU-Accelerated Incremental Checkpointing of Sparsely Updated Data
Computer Science, Machine Learning, and Applied Mathematics 

Paper
Scalable Riemann Solvers with the Discontinuous Galerkin Method for Hyperbolic Network Simulation
Physics
Computer Science, Machine Learning, and Applied Mathematics 

Sessions
Minisymposium
MS1A - Machine Learning Techniques for Modeling Under-Resolved Phenomena in Massively Parallel Simulations: Algorithms/Frameworks/Applications (Part 1/2)
Computer Science, Machine Learning, and Applied Mathematics 

Minisymposium
MS1B - Performance Portability Solutions beyond C++ to Support Future Workflows (Part 1/2)
Computer Science, Machine Learning, and Applied Mathematics 

Minisymposium
MS1C - Robust, Accurate, and Scalable Algorithms for Coupling in Earth System Models
Climate, Weather and Earth Sciences
Minisymposium
MS1H - Code as Community
Computer Science, Machine Learning, and Applied Mathematics 

Minisymposium
MS2A - Machine Learning Techniques for Modeling Under-Resolved Phenomena in Massively Parallel Simulations: Algorithms/Frameworks/Applications (Part 2/2)
Computer Science, Machine Learning, and Applied Mathematics 

Minisymposium
MS2B - Performance Portability Solutions beyond C++ to Support Future Workflows (Part 2/2)
Computer Science, Machine Learning, and Applied Mathematics 

Minisymposium
MS2G - Large Language Models for Autonomous Discovery
Life Sciences