Design, development, and analysis of a compressible fluid dynamics solver capable of exceeding one quadrillion degrees of freedom

This talk presents 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. The work improves 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 on NVIDIA and AMD architectures. Mixed half/single-precision storage and computation on well-conditioned numerics is used. The resulting solver is capable of simulating flow at 200 trillion grid points and 1 quadrillion degrees of freedom, exceeding the current record by a factor of 20. This talk describes the tools and languages used to develop fast and portable code that leverages coupled CPU-GPU and APU architectures and summarizes performance results that demonstrate real-world usability and meaningful improvement over the current state-of-the-art