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

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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Published
2025-11-12
DOI
https://doi.org/10.1145/3712285.3771783
Primary Topic
Computational Fluid Dynamics and Aerodynamics
Type
article
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article

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

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

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article en

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.

Oak Ridge National Laboratory (US), Georgia Institute of Technology (US), Courant Institute of Mathematical Sciences (US), Hewlett Packard Enterprise (United States) (US), Hewlett Packard Enterprise (Ireland) (IE), North Central College (US), New York University (US)
U.S. Department of Energy, Centro Svizzero di Calcolo Scientifico, National Supercomputing Centre Singapore, Office of Science, Oak Ridge National Laboratory
Openalex Percentile: Top 65%
Computational Fluid Dynamics and Aerodynamics
DOIOpen Access PDFOpenAlex
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