Benchmarking with Supernovae: A Performance Study of the FLASH Code
<|reference_start|>Benchmarking with Supernovae: A Performance Study of the FLASH Code: Astrophysical simulations are computation, memory, and thus energy intensive, thereby requiring new hardware advances for progress. Stony Brook University recently expanded its computing cluster "SeaWulf" with an addition of 94 new nodes featuring Intel Sapphire Rapids Xeon Max series CPUs. We present a performance and power efficiency study of this hardware performed with FLASH: a multi-scale, multi-physics, adaptive mesh-based software instrument. We extend this study to compare performance to that of Stony Brook's Ookami testbed which features ARM-based A64FX-700 processors, and SeaWulf's AMD EPYC Milan and Intel Skylake nodes. Our application is a stellar explosion known as a thermonuclear (Type Ia) supernova and for this 3D problem, FLASH includes operators for hydrodynamics, gravity, and nuclear burning, in addition to routines for the material equation of state. We perform a strong-scaling study with a 220 GB problem size to explore both single- and multi-node performance. Our study explores the performance of different MPI mappings and the distribution of processors across nodes. From these tests, we determined the optimal configuration to balance runtime and energy consumption for our application.<|reference_end|>
@article{martin2024benchmarking,
    title={Benchmarking with Supernovae: A Performance Study of the FLASH Code},
    author={Joshua Martin, Catherine Feldman, Eva Siegmann, Tony Curtis, David
  Carlson, Firat Coskun, Daniel Wood, Raul Gonzalez, Robert J. Harrison, Alan
  C. Calder},
    journal={Practice and Experience in Advanced Research Computing 2024
  Article no.8},
    year={2024},
    doi={10.1145/3626203.3670536},
    archivePrefix={arXiv},
    eprint={2408.16084},
    primaryClass={cs.DC astro-ph.IM}
}