Pushing the Limit of Quantum Mechanical Simulation to the Raman Spectra of a Biological System with 100 Million Atoms

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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:SC24: International Conference for High Performance Computing, Networking, Storage and Analysis s. 1 - 12
Hlavní autoři: Shang, Honghui, Liu, Ying, Wu, Zhikun, Chen, Zhenchuan, Liu, Jinfeng, Shao, Meiyue, Li, Yingzhou, Kan, Bowen, Cui, Huimin, Feng, Xiaobing, Zhang, Yunquan, Truhlar, Donald G., An, Hong, He, Xiao, Yang, Jinlong
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 17.11.2024
Témata:
all-electron quantum perturbation simulation
Atoms
Biological system modeling
Biological systems
Computational modeling
heterogeneous architectures
High performance computing
Perturbation methods
Quantum computing
Quantum mechanics
Raman scattering
Raman spectra
scalability
Supercomputers
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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.
DOI:10.1109/SC41406.2024.00011