Petascale molecular dynamics simulation using the fast multipole method on K computer

Abstract
In this paper, we report all-atom simulations of molecular crowding - a result from the full node simulation on the "K computer", which is a 10-PFLOPS supercomputer in Japan. The capability of this machine enables us to perform simulation of crowded cellular environments, which are more realistic compared to conventional MD simulations where proteins are simulated in isolation. Living cells are "crowded" because macromolecules comprise ∼30% of their molecular weight. Recently, the effects of crowded cellular environments on protein stability have been revealed through in-cell NMR spectroscopy. To measure the performance of the "K computer", we performed all-atom classical molecular dynamics simulations of two systems: target proteins in a solvent, and target proteins in an environment of molecular crowders that mimic the conditions of a living cell. Using the full system, we achieved 4.4 PFLOPS during a 520 million-atom simulation with cutoff of 28 Å. Furthermore, we discuss the performance and scaling of fast multipole methods for molecular dynamics simulations on the "K computer", as well as comparisons with Ewald summation methods. © 2014 Elsevier B.V. All rights reserved.

Citation
Ohno, Y., Yokota, R., Koyama, H., Morimoto, G., Hasegawa, A., Masumoto, G., … Taiji, M. (2014). Petascale molecular dynamics simulation using the fast multipole method on K computer. Computer Physics Communications, 185(10), 2575–2585. doi:10.1016/j.cpc.2014.06.004

Acknowledgements
This work was partially supported by the Integrated Simulation of Living Matter Project, commissioned by the Ministry of Education, Culture, Sports, Science and Technology, Japan. This work was partially supported in part by the Japan Science and Technology Agency (JST) Core Research of Evolutional Science and Technology (CREST) research programs "Highly Productive, High Performance Application Frameworks for Post Petascale Computing". Part of the results is obtained by using the K computer at the RIKEN Advanced Institute for Computational Science (early access and HPCI systems research project: Proposal number hp120068). We thank the Next-Generation Supercomputer R&D Center, especially Kazuo Minami, Akiyoshi Kuroda and Masaaki Terai (in the Application Development Team) for their outstanding support. We appreciate Mikio Hondou and Hikaru Inoue, from Fujitsu Co. Ltd., for their optimization support. We also thank the RIKEN Integrated Cluster of Clusters (RICC) for the computer resources used for our code development and calculations. We gratefully acknowledge the exceptional support provided by the late Takayuki Shigetani at RIKEN Advanced Center for Computing and Communication (ACCC). We also thank Toru Takinaka at NEC Informatec Systems, Ltd. for the supporting code development.

Publisher
Elsevier BV

Journal
Computer Physics Communications

DOI
10.1016/j.cpc.2014.06.004

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