Cosmological Hydrodynamics at Exascale: A Trillion-Particle Leap in Capability
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , , , , , , , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866912627055132672 |
|---|---|
| author | Frontiere, Nicholas Emberson, J. D. Buehlmann, Michael Rangel, Esteban M. Habib, Salman Heitmann, Katrin Larsen, Patricia Morozov, Vitali Pope, Adrian Faucher-Giguère, Claude-André Georgiadou, Antigoni Lebrun-Grandié, Damien Prokopenko, Andrey |
| author_facet | Frontiere, Nicholas Emberson, J. D. Buehlmann, Michael Rangel, Esteban M. Habib, Salman Heitmann, Katrin Larsen, Patricia Morozov, Vitali Pope, Adrian Faucher-Giguère, Claude-André Georgiadou, Antigoni Lebrun-Grandié, Damien Prokopenko, Andrey |
| contents | Resolving the most fundamental questions in cosmology requires simulations that match the scale, fidelity, and physical complexity demanded by next-generation sky surveys. To achieve the realism needed for this critical scientific partnership, detailed gas dynamics, along with a host of astrophysical effects, must be treated self-consistently with gravity for end-to-end modeling of structure formation. As an important step on this roadmap, exascale computing enables simulations that span survey-scale volumes while incorporating key subgrid processes that shape complex cosmic structures. We present results from CRK-HACC, a cosmological hydrodynamics code built for the extreme scalability requirements set by modern cosmological surveys. Using separation-of-scale techniques, GPU-resident tree solvers, in situ analysis pipelines, and multi-tiered I/O, CRK-HACC executed Frontier-E: a four trillion particle full-sky simulation, over an order of magnitude larger than previous efforts. The run achieved 513.1 PFLOPs peak performance, processing 46.6 billion particles per second and writing more than 100 PB of data in just over one week of runtime. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_03557 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Cosmological Hydrodynamics at Exascale: A Trillion-Particle Leap in Capability Frontiere, Nicholas Emberson, J. D. Buehlmann, Michael Rangel, Esteban M. Habib, Salman Heitmann, Katrin Larsen, Patricia Morozov, Vitali Pope, Adrian Faucher-Giguère, Claude-André Georgiadou, Antigoni Lebrun-Grandié, Damien Prokopenko, Andrey Distributed, Parallel, and Cluster Computing Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics Performance Computational Physics Resolving the most fundamental questions in cosmology requires simulations that match the scale, fidelity, and physical complexity demanded by next-generation sky surveys. To achieve the realism needed for this critical scientific partnership, detailed gas dynamics, along with a host of astrophysical effects, must be treated self-consistently with gravity for end-to-end modeling of structure formation. As an important step on this roadmap, exascale computing enables simulations that span survey-scale volumes while incorporating key subgrid processes that shape complex cosmic structures. We present results from CRK-HACC, a cosmological hydrodynamics code built for the extreme scalability requirements set by modern cosmological surveys. Using separation-of-scale techniques, GPU-resident tree solvers, in situ analysis pipelines, and multi-tiered I/O, CRK-HACC executed Frontier-E: a four trillion particle full-sky simulation, over an order of magnitude larger than previous efforts. The run achieved 513.1 PFLOPs peak performance, processing 46.6 billion particles per second and writing more than 100 PB of data in just over one week of runtime. |
| title | Cosmological Hydrodynamics at Exascale: A Trillion-Particle Leap in Capability |
| topic | Distributed, Parallel, and Cluster Computing Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics Performance Computational Physics |
| url | https://arxiv.org/abs/2510.03557 |