Simulating many-engine spacecraft: Exceeding 1 quadrillion degrees of freedom via information geometric regularization
arXiv:2505.07392 · doi: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 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.
11 pages, 8 figures, 4 tables. SC25 ACM Gordon Bell Prize Finalist
References in corpus (4)
- Method for portable, scalable, and performant GPU-accelerated simulation of multiphase compressible flow
- Simulation of humpback whale bubble-net feeding models
- Conditional moment methods for polydisperse cavitating flows
- Hybrid quadrature moment method for accurate and stable representation of non-Gaussian processes and their dynamics