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CRUX: A topology-aware load balancer for mesh-based fluid dynamics codes on GPU clusters — arXiv:2608.30080

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.30080
License (as archived): CC0-1.0
Archived: 2026-10-17T10:32:15.628Z
SHA-256 of the archived text: 1ff324a6ba4aab0416f627d4abe65839b097ffd86ed98494bca45d209a14656d
Stable URL of this page: https://metraipolis.com/documento/dc_197b72d58844

How to cite

CRUX: A topology-aware load balancer for mesh-based fluid dynamics codes on GPU clusters — arXiv:2608.30080 — arXiv (en), https://arxiv.org/abs/2608.30080 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_197b72d58844 (Metraipolis archive dc_197b72d58844, sha256 1ff324a6ba4aab0416f627d4abe65839b097ffd86ed98494bca45d209a14656d)

BibTeX

@misc{dc197b72d58844,
  title = {CRUX: A topology-aware load balancer for mesh-based fluid dynamics codes on GPU clusters — arXiv:2608.30080},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.30080},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_197b72d58844; sha256 1ff324a6ba4aab0416f627d4abe65839b097ffd86ed98494bca45d209a14656d},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.30080. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

The rapid growth of computational power has revolutionized numerical simulations, profoundly enhancing our understanding of fluids and plasmas. Computational fluid dynamics (CFD) simulations, which solve partial differential equations governing fluid or plasma motion on discretized grids, have been central to this progress. Recent advances have pushed the resolution and runtime of legacy numerical models to unprecedented levels while enabling newer codes to incorporate increasingly sophisticated physics. However, further scaling of these simulations has become a significant challenge, largely due to the comparatively modest improvements in networking capabilities relative to the rapid growth of floating-point performance in modern GPU-accelerated clusters. In this article, we introduce a novel load-balancing routine CRUX designed to scale efficiently for the most demanding CFD grids in astrophysics. Unlike traditional approaches based on space-filling curves, our method dynamically accounts for computational cost disparities among mesh blocks evolved with different timesteps while minimizing communication overhead. It is also able to take into account heterogeneous hardware. Through an extensive suite of benchmarks featuring up to 5,400 GPUs on OLCF Frontier and ALCF Aurora, we demonstrate that our load-balancing algorithm outperforms space-filling curve methods across all key metrics, including load uniformity, memory consumption, and communication efficiency, making it a robust solution for next-generation CFD simulations.

Tema degli esploratori: fisica e astronomia (retro-catalogo arXiv: annunci del 2026-09-01 in astro-ph.IM).
Categorie arXiv: Instrumentation and Methods for Astrophysics (astro-ph.IM).
Pagina del lavoro: https://arxiv.org/abs/2608.30080 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-17T10:18:17.116Z dalla pagina https://arxiv.org/catchup/astro-ph.IM/2026-09-01?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).