March 2026

Conference Paper

Simulating many-engine spacecraft: Exceeding 1 quadrillion degrees of freedom via information geometric regularization

By:
Wilfong, Benjamin; Radhakrishnan, Anand; Le Berre, Henry; J vickers, Daniel; Prathi, Tanush; Tselepidis, Nikolaos; Dorschner, Benedikt; Budiardja, Reuben D; Cornille, Brian; Abbott, Stephen; Schäfer, Florian; Bryngelson, Spencer
Page Number:
14-24
Book Title:
SC '25: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
Publication Date:
March 2026
Publisher Location:
Association for Computing Machinery, New York, New York, United States of America
Conference Name:
2025 International Conference for High Performance Computing, Networking, Storage, and Analysis (SC '25)
Conference Location:
St. Louis, Missouri, United States of America
Conference Sponsor:
IEEE
View DOI Listing:
https://doi.org/10.1145/3712285.3771783

Abstract

We present an optimized implementation of the recently proposed information geometric regularization (IGR) for unprecedented scale simulation of compressible fluid flows applied to multi-engine spacecraft boosters. We improve upon state-of-the-art computational fluid dynamics (CFD) techniques in terms of computational cost, memory footprint, and energy-to-solution metrics. Unified memory on coupled CPU–GPU or APU platforms increases problem size with negligible overhead. Mixed half/single-precision storage and computation are used on well-conditioned numerics. We simulate flow at 200 trillion grid points and 1 quadrillion degrees of freedom, exceeding the current record by a factor of 20. A factor of 4 wall-time speedup is achieved over optimized baselines. Ideal weak scaling is observed on OLCF Frontier, LLNL El Capitan, and CSCS Alps using the full systems. Strong scaling is near ideal at extreme conditions, including 80% efficiency on CSCS Alps with an 8 node baseline and stretching to the full system.


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