Meeting the Challenges of Modeling Astrophysical Thermonuclear Explosions: Castro, Maestro, and the AMReX Astrophysics Suite
Journal Article
·
· Journal of Physics. Conference Series
- Stony Brook Univ., NY (United States). Dept. of Physics and Astronomy
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Center for Computational Sciences and Engineering
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Center for Computational Sciences and Engineering
- Michigan State Univ., East Lansing, MI (United States). Dept. of Physics and Astronomy
- NVIDIA Corporation, Santa Clara, CA (United States)
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
We describe the AMReX suite of astrophysics codes and their application to modeling problems in stellar astrophysics. Maestro is tuned to efficiently model subsonic convective flows while Castro models the highly compressible flows associated with stellar explosions. Both are built on the block-structured adaptive mesh refinement library AMReX. Together, these codes enable a thorough investigation of stellar phenomena, including Type Ia supernovae and X-ray bursts. We describe these science applications and the approach we are taking to make these codes performant on current and future many-core and GPU-based architectures.
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); National Science Foundation (NSF); National Aeronautics and Space Administration (NASA)
- Grant/Contract Number:
- AC02-05CH11231; FG02-87ER40317; AC05-00OR22725
- OSTI ID:
- 1459408
- Journal Information:
- Journal of Physics. Conference Series, Vol. 1031, Issue 1; ISSN 1742-6588
- Publisher:
- IOP PublishingCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Cited by: 16 works
Citation information provided by
Web of Science
Web of Science
AMReX: a framework for block-structured adaptive mesh refinement
|
journal | May 2019 |
Observational Predictions for Sub-Chandrasekhar Mass Explosions: Further Evidence for Multiple Progenitor Systems for Type Ia Supernovae
|
journal | March 2019 |
Numerical Stability of Detonations in White Dwarf Simulations
|
journal | April 2019 |
Preparing Nuclear Astrophysics for Exascale | preprint | January 2020 |
Performance comparison of CFD-DEM solver MFiX-Exa, on GPUs and CPUs | preprint | January 2021 |
Similar Records
MAESTROeX: A Massively Parallel Low Mach Number Astrophysical Solver
MAESTRO: AN ADAPTIVE LOW MACH NUMBER HYDRODYNAMICS ALGORITHM FOR STELLAR FLOWS
MAESTRO, CASTRO, and SEDONA -- Petascale Codes for Astrophysical Applications
Journal Article
·
2019
· The Astrophysical Journal (Online)
·
OSTI ID:1601217
+2 more
MAESTRO: AN ADAPTIVE LOW MACH NUMBER HYDRODYNAMICS ALGORITHM FOR STELLAR FLOWS
Journal Article
·
2010
· Astrophysical Journal, Supplement Series
·
OSTI ID:21454854
+3 more
MAESTRO, CASTRO, and SEDONA -- Petascale Codes for Astrophysical Applications
Conference
·
2017
·
OSTI ID:1393631
+6 more