BATSRUS GPU: Faster-than-real-time Magnetospheric Simulations with a Block-adaptive Grid Code

Abstract Block-Adaptive-Tree Solar-wind Roe-type Upwind Scheme (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 (four 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 (2.1 128-core nodes), 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.

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Publication Details

Journal
The Astrophysical Journal
Published
2025-03-07
DOI
https://doi.org/10.3847/1538-4357/adaf15
Primary Topic
Geophysics and Gravity Measurements
Type
article
Field-Weighted Citation Impact
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article

BATSRUS GPU: Faster-than-real-time Magnetospheric Simulations with a Block-adaptive Grid Code

Hongyang Zhou, Yuxi Chen, G. Tóth, Alexander Gaenko et al.
The Astrophysical Journal
Geophysics and Gravity Measurements
article

BATSRUS GPU: Faster-than-real-time Magnetospheric Simulations with a Block-adaptive Grid Code

Hongyang Zhou, Yuxi Chen, G. Tóth, Alexander Gaenko, Yong-Ho An
article en

Abstract

Abstract Block-Adaptive-Tree Solar-wind Roe-type Upwind Scheme (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 (four 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 (2.1 128-core nodes), 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.

The Astrophysical JournalVol. 981(2)
Openalex Percentile: Top 97%
Geophysics and Gravity Measurements
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BATSRUS GPU: Faster-than-real-time Magnetospheric Simulations with a Block-adaptive Grid Code — Hongyang Zhou, Yuxi Chen, et al. · The Astrophysical Journal (2025) | TGRS Research Map | TGRS