We study the simulation of stellar mergers, which requires complex simulations with high computational demands. We have developed Octo-Tiger, a finite volume grid-based hydrodynamics simulation code with Adaptive Mesh Refinement which is unique in conserving both linear and angular momentum to machine precision. To face the challenge of increasingly complex, diverse, and heterogeneous HPC systems, Octo-Tiger relies on high-level programming abstractions. We use HPX with its futurization capabilities to ensure scalability both between nodes and within, and present first results replacing MPI with libfabric achieving up to a 2.8x speedup. We extend Octo-Tiger to heterogeneous GPU-accelerated supercomputers, demonstrating node-level performance and portability. We show scalability up to full system runs on Piz Daint. For the scenario's maximum resolution, the compute-critical parts (hydrodynamics and gravity) achieve 68.1% parallel efficiency at 2048 nodes.
@article{arxiv.1908.03121,
title = {From Piz Daint to the Stars: Simulation of Stellar Mergers using High-Level Abstractions},
author = {Gregor Daiß and Parsa Amini and John Biddiscombe and Patrick Diehl and Juhan Frank and Kevin Huck and Hartmut Kaiser and Dominic Marcello and David Pfander and Dirk Pflüger},
journal= {arXiv preprint arXiv:1908.03121},
year = {2019}
}