EXTENDED ABSTRACT: High-performance computing is a powerful tool for accelerating first-principles density functional theory calculations in material simulations on modern supercomputers. In this report, we introduce the development of plane-wave software PWDFT, atomic orbital linear-scaling software HONPAS, and discontinuous finite element low-scaling software DGDFT, along with the advanced highperformance parallel numerical algorithms employed. PWDFT is a standard pseudopotential plane-wave high-performance computing software that utilizes advanced iterative diagonalization algorithms and low-rank decomposition approximation algorithms, making it suitable for high-performance parallel computing involving thousands of atoms. It supports GPU-CUDA and DCU-HIP accelerated computations, with performance significantly surpassing that of VASP. HONPAS uses a strictly localized numerical atomic orbital basis set, primarily aimed at hybrid functional linear-scaling calculations for systems with thousands of atoms. It employs multi-level MPI dynamic parallelism, scalable to tens of thousands of cores. DGDFT is based on the discontinuous Galerkin method and uses adaptive localized basis functions generated dynamically during the self-consistent field iteration process. Its accuracy rivals that of standard planewave basis sets. Furthermore, the DGDFT method adopts a two-level parallelization strategy and heterogeneous acceleration, demonstrating high scalability. It can utilize nearly 40 million cores on the next-generation Sunway supercomputer while maintaining a parallel efficiency of 60%, making it suitable for studying the electronic structure properties of complex metallic systems containing millions of atoms.
REFERENCES:
[1] Xinming Qin, Wei Hu*, Jinlong Yang, et al, CCF Transactions on High Performance Computing 5, 26 (2023).
[2] Wei Hu, Xinming Qin, Weile Jia, Hong An*, Jinlong Yang*, et al, Sci. Bull. 66, 111 (2021).
[3] Wei Hu, Xinming Qin Hong An*, Jinlong Yang*, et al, SC22, ACM Gordon Bell Prize Finalist (2022)
Wei Hu obtained the B.S. degree (2007) and the Ph.D. degree (2013) supervised by Prof. Jinlong Yang, from the University of Science and Technology of China (USTC), postdoc in the Lawrence Berkeley National Laboratory (LBNL) (2014-2018) with Prof. Chao Yang (LBNL) and Prof. Lin Lin (UC Berkeley). Wei Hu became a professor (2018-present) at the Hefei National Research Center for Physical Sciences at the Microscale of USTC. He was a recipient of Chinese Academy of Sciences Pioneer Hundred Talents Program Scholarship (2018), Chinese Chemical Society Tang Au-Chin Young Investigator Award in Theoretical Chemistry (2020). He focuses on the development of low-scaling algorithms