Abstract
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 must be treated self-consistently with gravity for end-to-end modeling of structure formation. Exascale computing enables simulations that span survey-scale volumes while incorporating key astrophysical processes that shape complex cosmic structures. We present results from CRK-HACC, a cosmological hydrodynamics code built for extreme scalability. Using separation-of-scale techniques, GPU-resident tree solvers, in situ analysis pipelines, and multi-tiered I/O, CRK-HACCexecuted 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. Frontier-E marks a significant advance in predictive modeling for next-generation cosmological science.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2025 |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 25-35 |
| Number of pages | 11 |
| ISBN (Electronic) | 9798400714665 |
| DOIs | |
| State | Published - Nov 15 2025 |
| Event | 2025 International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2025 - St. Louis, United States Duration: Nov 16 2025 → Nov 21 2025 |
Publication series
| Name | Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2025 |
|---|
Conference
| Conference | 2025 International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2025 |
|---|---|
| Country/Territory | United States |
| City | St. Louis |
| Period | 11/16/25 → 11/21/25 |
Funding
The authors thank Nicholas Malaya, Noah Wolfe, Brian Cornille, Karl W. Schulz, and the AMD performance and application teams, as well as John Pennycook, Zhiqiang Ma, Varsha Madananth, and the Intel performance team. We acknowledge the staff at the Oak Ridge and Argonne Leadership Computing Facilities and at NERSC for their support. This research was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. DOE Office of Science and NNSA and by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research and Office of High Energy Physics, Scientific Discovery through Advanced Computing (SciDAC) program. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725; the Argonne Leadership Computing Facility (Contract No. DE-AC02-06CH11357); and the National Energy Research Scientific Computing Center (Contract No. DEAC02-05CH11231). CAFG is supported by NSF (AST-2108230, AST-2307327), NASA (21-ATP21-0036, 23-ATP23-0008), and STScI (JWST-AR-03252.001-A). Lastly, NF thanks his mother for help in improving the clarity and readability of the paper.
Keywords
- GPU acceleration
- cosmology
- exascale computing
- high-performance computing
- hydrodynamics
- in situ analysis
- parallel I/O
- particle methods
- performance portability
- scalability
- simulation
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