skip to main content
10.1145/3581784.3613210acmconferencesArticle/Chapter ViewAbstractPublication PagesscConference Proceedingsconference-collections
research-article
Open Access

Enabling Real World Scale Structural Superlubricity All-Atom Simulation on the Next-Generation Sunway Supercomputer

Authors Info & Claims
Published:11 November 2023Publication History

ABSTRACT

Molecular dynamics (MD) simulation can provide an affordable way for inspecting microscopic phenomena, which is a powerful complement to real-world experiments. But the spatial scale of MD simulations is usually magnitudes smaller than experiment systems. In this paper, we present our work, redesigning the widely used inter-layer potential in structural superlubricity. By carrying out a specialized neighbor list for inter-layer potential computation, the total memory access amount is reduced significantly. Besides, a simple but efficient vectorization strategy is implemented based on the new neighbor list. In the extreme case, our work can scale to 38 million cores to achieve a sustainable performance of 61 PFLOPS, enabling a simulation of a superlubricity system of 32 μm2 with 7.2 billion atoms at 4.75 ns/day, which is 11,834 times of reported largest scale simulation in superlubricity systems in contact area and almost ten times faster in time-to-solution. Furthermore, we have done a simulation at 9 μm2 which results in consistency with real-world experiments and verified some theoretical predictions in the mesoscopic scale.

References

  1. Michael P Allen et al. 2004. Introduction to molecular dynamics simulation. Computational soft matter: from synthetic polymers to proteins 23, 1 (2004), 1--28.Google ScholarGoogle Scholar
  2. Diana Berman, Sanket A Deshmukh, Subramanian KRS Sankaranarayanan, Ali Erdemir, and Anirudha V Sumant. 2015. Macroscale superlubricity enabled by graphene nanoscroll formation. Science 348, 6239 (2015), 1118--1122.Google ScholarGoogle Scholar
  3. Gerd Binnig, Calvin F Quate, and Ch Gerber. 1986. Atomic force microscope. Physical review letters 56, 9 (1986), 930.Google ScholarGoogle Scholar
  4. Gerd Binnig and Heinrich Rohrer. 2000. Scanning tunneling microscopy. IBM Journal of research and development 44, 1/2 (2000), 279.Google ScholarGoogle Scholar
  5. Gerd Binnig, Heinrich Rohrer, Ch Gerber, and Edmund Weibel. 1982. Surface studies by scanning tunneling microscopy. Physical review letters 49, 1 (1982), 57.Google ScholarGoogle Scholar
  6. Martin Dienwiebel, Gertjan S Verhoeven, Namboodiri Pradeep, Joost WM Frenken, Jennifer A Heimberg, and Henny W Zandbergen. 2004. Superlubricity of graphite. Physical review letters 92, 12 (2004), 126101.Google ScholarGoogle Scholar
  7. Wenqian Dong, Letian Kang, Zhe Quan, Kenli Li, Keqin Li, Ziyu Hao, and Xiang-Hui Xie. 2016. Implementing molecular dynamics simulation on sun-way taihulight system. In 2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS). IEEE, 443--450.Google ScholarGoogle Scholar
  8. Xiaohui Duan, Ping Gao, Meng Zhang, Tingjian Zhang, Hongsong Meng, Yuxuan Li, Bertil Schmidt, Haohuan Fu, Lin Gan, Wei Xue, Weiguo Liu, and Guangwen Yang. 2020. Cell-List based Molecular Dynamics on Many-Core Processors: A Case Study on Sunway TaihuLight Supercomputer. In SC20: International Conference for High Performance Computing, Networking, Storage and Analysis. 1--12. Google ScholarGoogle ScholarCross RefCross Ref
  9. Xiaohui Duan, Ping Gao, Tingjian Zhang, Meng Zhang, Weiguo Liu, Wusheng Zhang, Wei Xue, Haohuan Fu, Lin Gan, Dexun Chen, et al. 2018. Redesigning LAMMPS for peta-scale and hundred-billion-atom simulation on Sunway TaihuLight. In SC18: International Conference for High Performance Computing, Networking, Storage and Analysis. IEEE, 148--159.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Xiaohui Duan, Qi Shao, Junben Weng, Bertil Schmidt, Lin Gan, Guohui Li, Haohuan Fu, Wei Xue, Weiguo Liu, and Guangwen Yang. 2023. Bio-ESMD: A Data Centric Implementation for Large-Scale Biological System Simulation on Sunway TaihuLight Supercomputer. IEEE Transactions on Parallel and Distributed Systems 34, 3 (2023), 881--893. Google ScholarGoogle ScholarCross RefCross Ref
  11. Xiaohui Duan, Meng Zhang, Weiguo Liu, Haohuan Fu, Lin Gan, Wei Xue, and Guangwen Yang. 2020. Tuning a general purpose software cache library for TaihuLight's SW26010 processor. CCF Transactions on High Performance Computing 2, 2 (2020), 164--182.Google ScholarGoogle ScholarCross RefCross Ref
  12. Jean-Luc Fattebert, Daniel Osei-Kuffuor, Erik W Draeger, Tadashi Ogitsu, and William D Krauss. 2016. Modeling dilute solutions using first-principles molecular dynamics: computing more than a million atoms with over a million cores. In SC'16: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. IEEE, 12--22.Google ScholarGoogle ScholarCross RefCross Ref
  13. Zhicheng Feng, Yuanpeng Yao, Jianxin Liu, Bozhao Wu, Ze Liu, and Wengen Ouyang. 2023. Registry-Dependent Potential for Interfaces of Water with Graphene. The Journal of Physical Chemistry C 127, 18 (2023), 8704--8713. Google ScholarGoogle ScholarCross RefCross Ref
  14. Haohuan Fu, Junfeng Liao, Nan Ding, Xiaohui Duan, Lin Gan, Yishuang Liang, Xinliang Wang, Jinzhe Yang, Yan Zheng, Weiguo Liu, Lanning Wang, and Guangwen Yang. 2017. Redesigning CAM-SE for Peta-Scale Climate Modeling Performance and Ultra-High Resolution on Sunway TaihuLight. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (Denver, Colorado) (SC '17). Association for Computing Machinery, New York, NY, USA, Article 1, 12 pages. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Ping Gao, Xiaohui Duan, Jiaxu Guo, Jin Wang, Zhenya Song, Lizhen Cui, Xiangxu Meng, Xin Liu, Wusheng Zhang, Ming Ma, et al. 2021. LMFF: efficient and scalable layered materials force field on heterogeneous many-core processors. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. 1--14.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Ping Gao, Xiaohui Duan, Bertil Schmidt, Wusheng Zhang, Lin Gan, Haohuan Fu, Wei Xue, Weiguo Liu, and Guangwen Yang. 2021. Optimization of reactive force field simulation: Refactor, parallelization, and vectorization for interactions. IEEE Transactions on Parallel and Distributed Systems 33, 2 (2021), 359--373.Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Ping Gao, Xiaohui Duan, Tingjian Zhang, Meng Zhang, Bertil Schmidt, Xun Zhang, Hongliang Sun, Wusheng Zhang, Lin Gan, Wei Xue, et al. 2020. Millimeter-Scale and Billion-Atom Reactive Force Field Simulation on Sunway Taihulight. IEEE Transactions on Parallel and Distributed Systems 31, 12 (2020), 2954--2967.Google ScholarGoogle ScholarCross RefCross Ref
  18. Stefan Grimme. 2011. Density functional theory with London dispersion corrections. Wiley Interdisciplinary Reviews: Computational Molecular Science 1, 2 (2011), 211--228.Google ScholarGoogle ScholarCross RefCross Ref
  19. Motohisa Hirano. 2003. Superlubricity: a state of vanishing friction. Wear 254, 10 (2003), 932--940.Google ScholarGoogle ScholarCross RefCross Ref
  20. Motohisa Hirano and Kazumasa Shinjo. 1993. Superlubricity and frictional anisotropy. Wear 168, 1--2 (1993), 121--125.Google ScholarGoogle ScholarCross RefCross Ref
  21. M. Hirano, K. Shinjo, R. Kaneko, and Y. Murata. 1997. Observation of Superlubricity by Scanning Tunneling Microscopy. Physical Review Letters 78, 8 (1997), 1448--1451.Google ScholarGoogle ScholarCross RefCross Ref
  22. Kenneth Holmberg, Peter Andersson, and Ali Erdemir. 2012. Global energy consumption due to friction in passenger cars. Tribology international 47 (2012), 221--234.Google ScholarGoogle ScholarCross RefCross Ref
  23. Kenneth Holmberg and Ali Erdemir. 2015. Global impact of friction on energy consumption, economy and environment. Fme Trans 43, 3 (2015), 181--5.Google ScholarGoogle Scholar
  24. K. Huang, H. Qin, S. Zhang, Q. Li, W. Ouyang, and Y. Liu. 2022. The Origin of Moiré-Level Stick-Slip Behavior on Graphene/h-BN Heterostructures. Advanced Functional Materials 32, 35 (2022).Google ScholarGoogle Scholar
  25. Weile Jia, Han Wang, Mohan Chen, Denghui Lu, Lin Lin, Roberto Car, E Weinan, and Linfeng Zhang. 2020. Pushing the limit of molecular dynamics with ab initio accuracy to 100 million atoms with machine learning. In SC20: International conference for high performance computing, networking, storage and analysis. IEEE, 1--14.Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Aleksey N Kolmogorov and Vincent H Crespi. 2000. Smoothest bearings: inter-layer sliding in multiwalled carbon nanotubes. Physical Review Letters 85, 22 (2000), 4727.Google ScholarGoogle ScholarCross RefCross Ref
  27. Aleksey N Kolmogorov and Vincent H Crespi. 2005. Registry-dependent inter-layer potential for graphitic systems. Physical Review B 71, 23 (2005), 235415.Google ScholarGoogle ScholarCross RefCross Ref
  28. T Kontorova and Jl Frenkel. 1938. On the theory of plastic deformation and twinning. II. Zh. Eksp. Teor. Fiz. 8 (1938), 1340--1348.Google ScholarGoogle Scholar
  29. Itai Leven, Ido Azuri, Leeor Kronik, and Oded Hod. 2014. Inter-layer potential for hexagonal boron nitride. The Journal of chemical physics 140, 10 (2014), 104106.Google ScholarGoogle ScholarCross RefCross Ref
  30. Itai Leven, Tal Maaravi, Ido Azuri, Leeor Kronik, and Oded Hod. 2016. Interlayer potential for graphene/h-BN heterostructures. Journal of chemical theory and computation 12, 6 (2016), 2896--2905.Google ScholarGoogle ScholarCross RefCross Ref
  31. Ze Liu, Jiarui Yang, Francois Grey, Jefferson Zhe Liu, Yilun Liu, Yibing Wang, Yanlian Yang, Yao Cheng, and Quanshui Zheng. 2012. Observation of microscale superlubricity in graphite. Physical review letters 108, 20 (2012), 205503.Google ScholarGoogle Scholar
  32. Tal Maaravi, Itai Leven, Ido Azuri, Leeor Kronik, and Oded Hod. 2017. Inter-layer potential for homogeneous graphene and hexagonal boron nitride systems: reparametrization for many-body dispersion effects. The Journal of Physical Chemistry C 121, 41 (2017), 22826--22835.Google ScholarGoogle ScholarCross RefCross Ref
  33. Noa Marom, Jonathan Bernstein, Jonathan Garel, Alexandre Tkatchenko, Ernesto Joselevich, Leeor Kronik, and Oded Hod. 2010. Stacking and registry effects in layered materials: the case of hexagonal boron nitride. Physical review letters 105, 4 (2010), 046801.Google ScholarGoogle Scholar
  34. Wengen Ouyang, Davide Mandelli, Michael Urbakh, and Oded Hod. 2018. Nanoserpents: Graphene nanoribbon motion on two-dimensional hexagonal materials. Nano letters 18, 9 (2018), 6009--6016.Google ScholarGoogle Scholar
  35. W. Ouyang and M. Urbakh. 2022. Microscopic mechanisms of frictional aging. Journal of the Mechanics and Physics of Solids 166 (2022).Google ScholarGoogle Scholar
  36. Ludwig Prandtl. 1928. Ein Gedankenmodell zur kinetischen Theorie der festen Körper. ZAMM-Journal of Applied Mathematics and Mechanics/Zeitschrift für Angewandte Mathematik und Mechanik 8, 2 (1928), 85--106.Google ScholarGoogle ScholarCross RefCross Ref
  37. Cangyu Qu, Kunqi Wang, Jin Wang, Yujie Gongyang, Robert W Carpick, Michael Urbakh, and Quanshui Zheng. 2020. Origin of friction in superlubric graphite contacts. Physical Review Letters 125, 12 (2020), 126102.Google ScholarGoogle ScholarCross RefCross Ref
  38. Naruo Sasaki, Katsuyoshi Kobayashi, and Masaru Tsukada. 1996. Atomic-scale friction image of graphite in atomic-force microscopy. Physical Review B 54, 3 (1996), 2138.Google ScholarGoogle ScholarCross RefCross Ref
  39. Yiming Song, Davide Mandelli, Oded Hod, Michael Urbakh, Ming Ma, and Quanshui Zheng. 2018. Robust microscale superlubricity in graphite/hexagonal boron nitride layered heterojunctions. Nature materials 17, 10 (2018), 894--899.Google ScholarGoogle Scholar
  40. Chang Q Sun, Yi Sun, Yanguang Ni, Xi Zhang, Jisheng Pan, Xiao-Hui Wang, Ji Zhou, Long-Tu Li, Weitao Zheng, Shansheng Yu, et al. 2009. Coulomb repulsion at the nanometer-sized contact: a force driving superhydrophobicity, superfluidity, superlubricity, and supersolidity. The Journal of Physical Chemistry C 113, 46 (2009), 20009--20019.Google ScholarGoogle ScholarCross RefCross Ref
  41. Gertjan S Verhoeven, Martin Dienwiebel, and Joost WM Frenken. 2004. Model calculations of superlubricity of graphite. Physical Review B 70, 16 (2004), 165418.Google ScholarGoogle ScholarCross RefCross Ref
  42. Hao Wang, Xun Guo, Linfeng Zhang, Han Wang, and Jianming Xue. 2019. Deep learning inter-atomic potential model for accurate irradiation damage simulations. Applied Physics Letters 114, 24 (2019), 244101.Google ScholarGoogle ScholarCross RefCross Ref
  43. Jin Wang, Wei Cao, Yiming Song, Cangyu Qu, Quanshui Zheng, and Ming Ma. 2019. Generalized scaling law of structural superlubricity. Nano Letters 19, 11 (2019), 7735--7741.Google ScholarGoogle ScholarCross RefCross Ref
  44. W. Yan, L. Shui, W. Ouyang, and Z. Liu. 2022. Thermodynamic model of twisted bilayer graphene: Entropy matters. Journal of the Mechanics and Physics of Solids 167 (2022).Google ScholarGoogle Scholar
  45. Rufan Zhang, Zhiyuan Ning, Yingying Zhang, Quanshui Zheng, Qing Chen, Huanhuan Xie, Qiang Zhang, Weizhong Qian, and Fei Wei. 2013. Superlubricity in centimetres-long double-walled carbon nanotubes under ambient conditions. Nature nanotechnology 8, 12 (2013), 912--916.Google ScholarGoogle Scholar

Index Terms

  1. Enabling Real World Scale Structural Superlubricity All-Atom Simulation on the Next-Generation Sunway Supercomputer
        Index terms have been assigned to the content through auto-classification.

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          SC '23: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
          November 2023
          1428 pages
          ISBN:9798400701092
          DOI:10.1145/3581784

          Copyright © 2023 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 11 November 2023

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article

          Acceptance Rates

          Overall Acceptance Rate1,516of6,373submissions,24%
        • Article Metrics

          • Downloads (Last 12 months)241
          • Downloads (Last 6 weeks)46

          Other Metrics

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader