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

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Název: RAMSES-yOMP: Performance Optimizations for the Astrophysical Hydrodynamic Simulation Code RAMSES
Autoři: Han, San, Dubois, Yohan, Lee, Jaehyun, Kim, Juhan, Cadiou, Corentin, Yi, Sukyoung K.
Přispěvatelé: Lund University, Faculty of Science, Department of Physics, Astrophysics, Lunds universitet, Naturvetenskapliga fakulteten, Fysiska institutionen, Astrofysik, Originator
Zdroj: Astrophysical Journal. 978(1)
Témata: Natural Sciences, Physical Sciences, Fusion, Plasma and Space Physics, Naturvetenskap, Fysik, plasma och rymdfysik, Computer and Information Sciences, Computer graphics and computer vision, Data- och informationsvetenskap (Datateknik), Datorgrafik och datorseende, Other Physics Topics, Annan fysik
Popis: 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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  Data: RAMSES-yOMP: Performance Optimizations for the Astrophysical Hydrodynamic Simulation Code RAMSES
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  Data: <searchLink fieldCode="AR" term="%22Han%2C+San%22">Han, San</searchLink><br /><searchLink fieldCode="AR" term="%22Dubois%2C+Yohan%22">Dubois, Yohan</searchLink><br /><searchLink fieldCode="AR" term="%22Lee%2C+Jaehyun%22">Lee, Jaehyun</searchLink><br /><searchLink fieldCode="AR" term="%22Kim%2C+Juhan%22">Kim, Juhan</searchLink><br /><searchLink fieldCode="AR" term="%22Cadiou%2C+Corentin%22">Cadiou, Corentin</searchLink><br /><searchLink fieldCode="AR" term="%22Yi%2C+Sukyoung+K%2E%22">Yi, Sukyoung K.</searchLink>
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  Data: <i>Astrophysical Journal</i>. 978(1)
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  Data: 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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