TY - GEN
T1 - Pushing the Limit of Quantum Mechanical Simulation to the Raman Spectra of a Biological System with 100 Million Atoms
AU - Shang, Honghui
AU - Liu, Ying
AU - Wu, Zhikun
AU - Chen, Zhenchuan
AU - Liu, Jinfeng
AU - Shao, Meiyue
AU - Li, Yingzhou
AU - Kan, Bowen
AU - Cui, Huimin
AU - Feng, Xiaobing
AU - Zhang, Yunquan
AU - Truhlar, Donald G.
AU - An, Hong
AU - He, Xiao
AU - Yang, Jinlong
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024/11/17
Y1 - 2024/11/17
N2 - Raman spectroscopy offers invaluable insights into the chemical composition and structural characteristics of various materials, making it a powerful tool for structural analysis. However, accurate quantum mechanical simulations of Raman spectra for large systems, such as biological materials, have been limited due to immense computational costs and technical challenges. In this study, we developed efficient algorithms and optimized implementations on heterogeneous computing architectures to enable fast and highly scalable ab initio simulations of Raman spectra for large-scale biological systems with up to 100 million atoms. Our simulations have achieved nearly linear strong and weak scaling on two cutting-edge high-performance computing systems, with peak FP64 performances reaching 400 PFLOPS on 96,000 nodes of new Sunway supercomputer and 85 PFLOPS on 6,000 node of ORISE supercomputer. These advances provide promising prospects for extending quantum mechanical simulations to biological systems.
AB - Raman spectroscopy offers invaluable insights into the chemical composition and structural characteristics of various materials, making it a powerful tool for structural analysis. However, accurate quantum mechanical simulations of Raman spectra for large systems, such as biological materials, have been limited due to immense computational costs and technical challenges. In this study, we developed efficient algorithms and optimized implementations on heterogeneous computing architectures to enable fast and highly scalable ab initio simulations of Raman spectra for large-scale biological systems with up to 100 million atoms. Our simulations have achieved nearly linear strong and weak scaling on two cutting-edge high-performance computing systems, with peak FP64 performances reaching 400 PFLOPS on 96,000 nodes of new Sunway supercomputer and 85 PFLOPS on 6,000 node of ORISE supercomputer. These advances provide promising prospects for extending quantum mechanical simulations to biological systems.
KW - Raman spectra
KW - all-electron quantum perturbation simulation
KW - heterogeneous architectures
KW - scalability
UR - https://www.scopus.com/pages/publications/85215011572
U2 - 10.1109/SC41406.2024.00011
DO - 10.1109/SC41406.2024.00011
M3 - 会议稿件
AN - SCOPUS:85215011572
T3 - International Conference for High Performance Computing, Networking, Storage and Analysis, SC
BT - Proceedings of SC 2024
PB - IEEE Computer Society
T2 - 2024 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2024
Y2 - 17 November 2024 through 22 November 2024
ER -