Simulating many-engine spacecraft: Exceeding 1 quadrillion degrees of freedom via information geometric regularization
Benjamin Wilfong, Anand Radhakrishnan, Henry Le Berre, Daniel J. Vickers, Tanush Prathi, Nikolaos Tselepidis, Benedikt Dorschner, Reuben Budiardja, Brian Cornille, Stephen Abbott, Florian Schäfer, Spencer H. Bryngelson
公開日: 2025/5/12
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.