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SC2024顶会

Enabling 13K-Atom Excited-State GW Calculations via Low-Rank Approximations and HPC on the New Sunway Supercomputer

Wentiao Wu, Zhengbang Zhou, Qingcai Jiang, Junwei Feng, Xinming Qin, Huanhuan Ma, Zhenwei Cao, Junshi Chen, Sheng Chen, Xinyong Meng, Bingkun Hou, Yuanfan Xiong

2024年份
3被引次数

摘要

GW approximation is a powerful approach to accurately describe the excited-state of semiconductors. However, GW incurs high computational cost O(N4)\mathcal{O}\left(N^{4}\right) and large memory usage O(N3)\mathcal{O}\left(N^{3}\right), limiting its applications to thousands of (2,742) atoms even on leadership supercomputers. Herein we present a massively parallel implementation of accurate and efficient cubic-scaling plane-wave GW calculations by using low-rank approximations and high-performance computing on leadership supercomputers. By using a series of low rank approximations, we can reduce the expensive GW calculations to the cubic-scaling computational cost O(N3)\mathcal{O}\left(N^{3}\right) and quadratic memory usage O(N2)\mathcal{O}\left(N^{2}\right). With the help of parallel and communication optimization, the plane-wave GW calculations gain an overall speedup of over 70x and efficiently scale up to 13,824 atoms within a few minutes using 449,280 cores on new Sunway supercomputer. This accomplishment paves the way for excited-state quantum mechanical material simulations at mesoscopic scale (10K atoms) and for the design of next-generation semiconductor devices.

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