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Main Authors: An, Yifu, Chen, Yuxi, Zhou, Hongyang, Gaenko, Alexander, Tóth, Gábor
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2501.06717
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author An, Yifu
Chen, Yuxi
Zhou, Hongyang
Gaenko, Alexander
Tóth, Gábor
author_facet An, Yifu
Chen, Yuxi
Zhou, Hongyang
Gaenko, Alexander
Tóth, Gábor
contents BATSRUS, our state-of-the-art extended magnetohydrodynamic code, is the most used and one of the most resource-consuming models in the Space Weather Modeling Framework. It has always been our objective to improve its efficiency and speed with emerging techniques, such as GPU acceleration. To utilize the GPU nodes on modern supercomputers, we port BATSRUS to GPUs with the OpenACC API. Porting the code to a single GPU requires rewriting and optimizing the most used functionalities of the original code into a new solver, which accounts for around 1% of the entire program in length. To port it to multiple GPUs, we implement a new message passing algorithm to support its unique block-adaptive grid feature. We conduct weak scaling tests on as many as 256 GPUs and find good performance. The program has 50-60% parallel efficiency on up to 256 GPUs, and up to 95% efficiency within a single node (4 GPUs). Running large problems on more than one node has reduced efficiency due to hardware bottlenecks. We also demonstrate our ability to run representative magnetospheric simulations on GPUs. The performance for a single A100 GPU is about the same as 270 AMD "Rome" CPU cores, and it runs 3.6 times faster than real time. The simulation can run 6.9 times faster than real time on four A100 GPUs.
format Preprint
id arxiv_https___arxiv_org_abs_2501_06717
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle BATSRUS GPU: Faster-than-Real-Time Magnetospheric Simulations with a Block-Adaptive Grid Code
An, Yifu
Chen, Yuxi
Zhou, Hongyang
Gaenko, Alexander
Tóth, Gábor
Instrumentation and Methods for Astrophysics
Solar and Stellar Astrophysics
Computational Physics
Space Physics
BATSRUS, our state-of-the-art extended magnetohydrodynamic code, is the most used and one of the most resource-consuming models in the Space Weather Modeling Framework. It has always been our objective to improve its efficiency and speed with emerging techniques, such as GPU acceleration. To utilize the GPU nodes on modern supercomputers, we port BATSRUS to GPUs with the OpenACC API. Porting the code to a single GPU requires rewriting and optimizing the most used functionalities of the original code into a new solver, which accounts for around 1% of the entire program in length. To port it to multiple GPUs, we implement a new message passing algorithm to support its unique block-adaptive grid feature. We conduct weak scaling tests on as many as 256 GPUs and find good performance. The program has 50-60% parallel efficiency on up to 256 GPUs, and up to 95% efficiency within a single node (4 GPUs). Running large problems on more than one node has reduced efficiency due to hardware bottlenecks. We also demonstrate our ability to run representative magnetospheric simulations on GPUs. The performance for a single A100 GPU is about the same as 270 AMD "Rome" CPU cores, and it runs 3.6 times faster than real time. The simulation can run 6.9 times faster than real time on four A100 GPUs.
title BATSRUS GPU: Faster-than-Real-Time Magnetospheric Simulations with a Block-Adaptive Grid Code
topic Instrumentation and Methods for Astrophysics
Solar and Stellar Astrophysics
Computational Physics
Space Physics
url https://arxiv.org/abs/2501.06717