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High performance computing for first-principles Kohn-Sham density functional theory towards exascale supercomputers

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Abstract

High performance computing (HPC) plays an essential role in enabling first-principles calculations based on the Kohn–Sham density functional theory (KS-DFT) for investigating quantum structural and electronic properties of large-scale molecules and solids in condensed matter physics, quantum chemistry and materials science. This review focuses on recent advances for HPC software development in large-scale KS-DFT calculations containing tens of thousands of atoms on modern heterogeneous supercomputers, especially for the HPC software with independent intellectual property rights supported on the Chinese domestic exascale supercomputers. We first introduce three various types of DFT software developed on modern heterogeneous supercomputers, involving PWDFT (Plane-Wave Density Functional Theory), HONPAS (Hefei Order-N Packages for Ab initio Simulations) and DGDFT (Discontinuous Galerkin Density Functional Theory), respectively based on three different types of basis sets (plane waves, numerical atomic orbitals and adaptive local basis functions). Then, we describe the theoretical algorithms and parallel implementation of these three software on modern heterogeneous supercomputers in detail. Finally, we conclude this review and propose several promising research fields for future large-scale KS-DFT calculations towards exascale supercomputers.

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Acknowledgements

This work is partly supported by the National Natural Science Foundation of China (21688102, 21803066, 22003061, 22173093), by the Hefei National Laboratory for Physical Sciences at the Microscale (KF2020003), the Chinese Academy of Sciences Pioneer Hundred Talents Program (KJ2340000031), the Anhui Initiative in Quantum Information Technologies (AHY090400), the CAS Project for Young Scientists in Basic Research (YSBR-005), the Strategic Priority Research Program of Chinese Academy of Sciences (XDC01040100), the Fundamental Research Funds for the Central Universities (WK2340000091, WK2060000018), the Hefei National Laboratory for Physical Sciences at the Microscale (SK2340002001), the Research Start-Up Grants (KY2340000094) and the Academic Leading Talents Training Program (KY2340000103) from University of Science and Technology of China. The authors thank the Hefei Advanced Computing Center, the Supercomputing Center of Chinese Academy of Sciences (SunRising-1), the Supercomputing Center of USTC, the National Supercomputing Center in Wuxi, Tianjin, Shanghai, and Guangzhou for the computational resources.

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  1. Xinming Qin and Junshi Chen contributed equally to this work.

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  1. Hefei National Laboratory for Physical Sciences at the Microscale, Department of Chemical Physics, and Anhui Center for Applied Mathematics, University of Science and Technology of China, Hefei, 230026, Anhui, China

    Xinming Qin, Zhaolong Luo, Lingyun Wan, Jielan Li, Shizhe Jiao, Zhenlin Zhang, Wei Hu & Jinlong Yang

  2. School of Computer Science and Technology, University of Science and Technology of China, Hefei, 230026, Anhui, China

    Junshi Chen, Qingcai Jiang & Hong An

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Qin, X., Chen, J., Luo, Z. et al. High performance computing for first-principles Kohn-Sham density functional theory towards exascale supercomputers. CCF Trans. HPC 5, 26–42 (2023). https://doi.org/10.1007/s42514-022-00120-0

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