High-speed and low-power molecular dynamics processing unit (MDPU) with ab initio accuracy

Molecular dynamics (MD) is an indispensable atomistic-scale computational tool widely-used in various disciplines. In the past decades, nearly all ab initio MD and machine-learning MD have been based on the general-purpose central/graphics processing units (CPU/GPU), which are well-known to suffer f...

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Veröffentlicht in:npj computational materials 2024-11, Vol.10 (1), p.253-10, Article 253
Hauptverfasser: Mo, Pinghui, Zhang, Yujia, Zhao, Zhuoying, Sun, Hanhan, Li, Junhua, Guan, Dawei, Ding, Xi, Zhang, Xin, Chen, Bo, Shi, Mengchao, Zhang, Duo, Lu, Denghui, Wang, Yinan, Huang, Jianxing, Liu, Fei, Li, Xinyu, Chen, Mohan, Cheng, Jun, Liang, Bin, E, Weinan, Dai, Jiayu, Zhang, Linfeng, Wang, Han, Liu, Jie
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Sprache:eng
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Zusammenfassung:Molecular dynamics (MD) is an indispensable atomistic-scale computational tool widely-used in various disciplines. In the past decades, nearly all ab initio MD and machine-learning MD have been based on the general-purpose central/graphics processing units (CPU/GPU), which are well-known to suffer from their intrinsic “memory wall” and “power wall” bottlenecks. Consequently, nowadays MD calculations with ab initio accuracy are extremely time-consuming and power-consuming, imposing serious restrictions on the MD simulation size and duration. To solve this problem, here we propose a special-purpose MD processing unit (MDPU), which could reduce MD time and power consumption by about 10 3 times (10 9 times) compared to state-of-the-art machine-learning MD (ab initio MD) based on CPU/GPU, while keeping ab initio accuracy. With significantly-enhanced performance, the proposed MDPU may pave a way for the accurate atomistic-scale analysis of large-size and/or long-duration problems which were impossible/impractical to compute before.
ISSN:2057-3960
2057-3960
DOI:10.1038/s41524-024-01422-3