RAMSES-yOMP: Performance Optimizations for the Astrophysical Hydrodynamic Simulation Code RAMSES

Abstract Developing an efficient code for large, multiscale astrophysical simulations is crucial in preparing for the upcoming era of exascale computing. RAMSES is an astrophysical simulation code that employs parallel processing based on the message-passing interface (MPI). However, it has limitations in computational and memory efficiency when using a large number of CPU cores. The problem stems from inefficiencies in workload distribution and memory allocation that inevitably occur when a volume is simply decomposed into domains equal to the number of working processors. We present RAMSES-yOMP, which is a modified version of RAMSES designed to improve parallel scalability. Major updates include the incorporation of open multiprocessing into the MPI parallelization to take advantage of both the shared and distributed memory models. Utilizing this hybrid parallelism in high-resolution benchmark simulations with full prescriptions for baryonic physics, we achieved an increase in performance by a factor of 2 in the total run-time, while using 75% less memory and 30% less storage than the original code, when using the same number of processors. These improvements allow us to perform larger or higher-resolution simulations than what was feasible previously.

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Publication Details

Journal
The Astrophysical Journal
Published
2024-12-27
DOI
https://doi.org/10.3847/1538-4357/ad98f4
Citations
4
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
1.51

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article

RAMSES-yOMP: Performance Optimizations for the Astrophysical Hydrodynamic Simulation Code RAMSES

San Han, Sukyoung K. Yi, Juhan Kim, Yohan Dubois et al.
4 citations
The Astrophysical Journal
Meteorological Phenomena and Simulations
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article

RAMSES-yOMP: Performance Optimizations for the Astrophysical Hydrodynamic Simulation Code RAMSES

San Han, Sukyoung K. Yi, Juhan Kim, Yohan Dubois, Corentin Cadiou, Jaehyun Lee
article en
4 citations

Abstract

Abstract Developing an efficient code for large, multiscale astrophysical simulations is crucial in preparing for the upcoming era of exascale computing. RAMSES is an astrophysical simulation code that employs parallel processing based on the message-passing interface (MPI). However, it has limitations in computational and memory efficiency when using a large number of CPU cores. The problem stems from inefficiencies in workload distribution and memory allocation that inevitably occur when a volume is simply decomposed into domains equal to the number of working processors. We present RAMSES-yOMP, which is a modified version of RAMSES designed to improve parallel scalability. Major updates include the incorporation of open multiprocessing into the MPI parallelization to take advantage of both the shared and distributed memory models. Utilizing this hybrid parallelism in high-resolution benchmark simulations with full prescriptions for baryonic physics, we achieved an increase in performance by a factor of 2 in the total run-time, while using 75% less memory and 30% less storage than the original code, when using the same number of processors. These improvements allow us to perform larger or higher-resolution simulations than what was feasible previously.

The Astrophysical JournalVol. 978(1)
National Research Foundation, Korea Institute of Science and Technology Information, National Research Foundation of Korea, Ministry of Science and ICT, South Korea, Korea Research Environment Open Network
Industry, innovation and infrastructure
Openalex Percentile: Top 18%
Meteorological Phenomena and Simulations
1.51
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RAMSES-yOMP: Performance Optimizations for the Astrophysical Hydrodynamic Simulation Code RAMSES — San Han, Sukyoung K. Yi, et al. · The Astrophysical Journal (2024) | TGRS Research Map | TGRS