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

TL;DR

This paper introduces an advanced simulation method using information geometric regularization, enabling the modeling of spacecraft fluid flows at unprecedented scales exceeding one quadrillion degrees of freedom with significant efficiency improvements.

Contribution

The authors develop an optimized CFD implementation that leverages information geometric regularization to simulate multi-engine spacecraft flows at unprecedented scale, surpassing existing records.

Findings

Simulated flow at 200 trillion grid points and 1 quadrillion degrees of freedom.

Achieved a 4x speedup over optimized baselines.

Demonstrated near-ideal weak and strong scaling on top supercomputers.

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.