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...
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| Published in: | SC24: International Conference for High Performance Computing, Networking, Storage and Analysis pp. 1 - 12 |
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| Main Authors: | , , , , , , , , , , , , , , |
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IEEE
17.11.2024
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Liu, Jinfeng Chen, Zhenchuan Li, Yingzhou Yang, Jinlong Feng, Xiaobing Wu, Zhikun Shao, Meiyue Kan, Bowen Zhang, Yunquan Liu, Ying Truhlar, Donald G. An, Hong Shang, Honghui Cui, Huimin He, Xiao |
| Author_xml | – sequence: 1 givenname: Honghui surname: Shang fullname: Shang, Honghui organization: University of Science and Technology of China,Key Laboratory of Precision and Intelligent Chemistry,Hefei,China – sequence: 2 givenname: Ying surname: Liu fullname: Liu, Ying organization: University of Chinese Academy of Sciences,State Key Lab of Processors, Chinese Academy of Science,Beijing,China – sequence: 3 givenname: Zhikun surname: Wu fullname: Wu, Zhikun organization: University of Chinese Academy of Sciences,State Key Lab of Processors, Chinese Academy of Science,Beijing,China – sequence: 4 givenname: Zhenchuan surname: Chen fullname: Chen, Zhenchuan organization: University of Chinese Academy of Sciences,State Key Lab of Processors, Chinese Academy of Science,Beijing,China – sequence: 5 givenname: Jinfeng surname: Liu fullname: Liu, Jinfeng organization: China Pharmaceutical University,Shool of Science,Nanjing,China – sequence: 6 givenname: Meiyue surname: Shao fullname: Shao, Meiyue organization: Fudan University,School of Data Science and MOE Key Laboratory for Computational Physical Sciences,Shanghai,China – sequence: 7 givenname: Yingzhou surname: Li fullname: Li, Yingzhou organization: Fudan University,School of Mathematical Sciences and MOE Key Laboratory for Computational Physical Sciences,Shanghai,China – sequence: 8 givenname: Bowen surname: Kan fullname: Kan, Bowen organization: University of Science and Technology of China,Key Laboratory of Precision and Intelligent Chemistry,Hefei,China – sequence: 9 givenname: Huimin surname: Cui fullname: Cui, Huimin organization: University of Chinese Academy of Sciences,State Key Lab of Processors, Chinese Academy of Science,Beijing,China – sequence: 10 givenname: Xiaobing surname: Feng fullname: Feng, Xiaobing organization: University of Chinese Academy of Sciences,State Key Lab of Processors, Chinese Academy of Science,Beijing,China – sequence: 11 givenname: Yunquan surname: Zhang fullname: Zhang, Yunquan organization: University of Chinese Academy of Sciences,Chinese Academy of Science,Beijing,China – sequence: 12 givenname: Donald G. surname: Truhlar fullname: Truhlar, Donald G. organization: University of Minnesota,Department of Chemistry,Minneapolis,MN,USA – sequence: 13 givenname: Hong surname: An fullname: An, Hong organization: University of Science and Technology of China,Key Laboratory of Precision and Intelligent Chemistry,Hefei,China – sequence: 14 givenname: Xiao surname: He fullname: He, Xiao organization: East China Normal University,Shanghai Frontiers Science Center of Molecule Intelligent Syntheses, School of Chemistry and Molecular Engineering,Shanghai,China – sequence: 15 givenname: Jinlong surname: Yang fullname: Yang, Jinlong organization: University of Science and Technology of China,Key Laboratory of Precision and Intelligent Chemistry,Hefei,China |
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| Snippet | Raman spectroscopy offers invaluable insights into the chemical composition and structural characteristics of various materials, making it a powerful tool for... |
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| SubjectTerms | 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 |
| Title | Pushing the Limit of Quantum Mechanical Simulation to the Raman Spectra of a Biological System with 100 Million Atoms |
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