RAMSES-yOMP: Performance Optimizations for the Astrophysical Hydrodynamic Simulation Code RAMSES
San Han, Yohan Dubois, Jaehyun Lee, Juhan Kim, Corentin Cadiou,, Sukyoung K. Yi

TL;DR
RAMSES-yOMP enhances the astrophysical simulation code RAMSES by integrating hybrid MPI and OpenMP parallelism, significantly improving performance, memory efficiency, and enabling larger, higher-resolution simulations.
Contribution
The paper introduces RAMSES-yOMP, a modified version of RAMSES that incorporates OpenMP for hybrid parallelism, addressing scalability and efficiency issues in large-scale astrophysical simulations.
Findings
Achieved a 2x performance increase in simulations.
Reduced memory usage by 75%.
Lowered storage requirements by 30%.
Abstract
Developing an efficient code for large, multiscale astrophysical simulations is crucial in preparing 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 Multi-Processing into the MPI parallelization to take advantage of both the shared and distributed memory models. Utilizing this hybrid parallelism in high-resolution benchmark…
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Taxonomy
TopicsAdvanced Data Storage Technologies · Meteorological Phenomena and Simulations · Scientific Research and Discoveries
