Simulating many-engine spacecraft: Exceeding 1 quadrillion degrees of freedom via information geometric regularization
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arXiv
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| Main Authors: | , , , , , , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866914172977020928 |
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| author | Wilfong, Benjamin Radhakrishnan, Anand Berre, Henry Le Vickers, Daniel J. Prathi, Tanush Tselepidis, Nikolaos Dorschner, Benedikt Budiardja, Reuben Cornille, Brian Abbott, Stephen Schäfer, Florian Bryngelson, Spencer H. |
| author_facet | Wilfong, Benjamin Radhakrishnan, Anand Berre, Henry Le Vickers, Daniel J. Prathi, Tanush Tselepidis, Nikolaos Dorschner, Benedikt Budiardja, Reuben Cornille, Brian Abbott, Stephen Schäfer, Florian Bryngelson, Spencer H. |
| contents | 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 along 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 on well-conditioned numerics is used. 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 seen 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2505_07392 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Simulating many-engine spacecraft: Exceeding 1 quadrillion degrees of freedom via information geometric regularization Wilfong, Benjamin Radhakrishnan, Anand Berre, Henry Le Vickers, Daniel J. Prathi, Tanush Tselepidis, Nikolaos Dorschner, Benedikt Budiardja, Reuben Cornille, Brian Abbott, Stephen Schäfer, Florian Bryngelson, Spencer H. Computational Physics Computational Engineering, Finance, and Science Fluid Dynamics 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 along 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 on well-conditioned numerics is used. 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 seen 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. |
| title | Simulating many-engine spacecraft: Exceeding 1 quadrillion degrees of freedom via information geometric regularization |
| topic | Computational Physics Computational Engineering, Finance, and Science Fluid Dynamics |
| url | https://arxiv.org/abs/2505.07392 |