Update on Performance Analysis of Different Computational Architectures: Molecular Dynamics in Application to Protein-Protein Interactions

Vladimir A. Fedorov; Ekaterina G. Kholina; Ilya B. Kovalenko; Nikita B. Gudimchuk; Philipp S. Orekhov; Artem A. Zhmurov

doi:10.14529/jsfi200405

Authors

Vladimir A. Fedorov Lomonosov Moscow State University, Moscow
Ekaterina G. Kholina Lomonosov Moscow State University, Moscow
Ilya B. Kovalenko Lomonosov Moscow State University, Moscow Federal Research and Clinical Center of Specialized Medical Care and Medical Technologies, Federal Medical and Biological Agency of Russia, Moscow Astrakhan State University, Astrakhan Scientific and Technological Center of Unique Instrumentation of the RAS, Moscow Center for Theoretical Problems of Physicochemical Pharmacology, RAS, Moscow
Nikita B. Gudimchuk Lomonosov Moscow State University, Moscow Center for Theoretical Problems of Physicochemical Pharmacology, RAS, Moscow
Philipp S. Orekhov Lomonosov Moscow State University, Moscow Moscow Institute of Physics and Technology, Dolgoprudny
Artem A. Zhmurov KTH Royal Institute of Technology, Science for Life Laboratory, Stockholm

DOI:

https://doi.org/10.14529/jsfi200405

Abstract

Molecular dynamics has proved itself as a powerful computer simulation method to study dynamics, conformational changes, and interactions of biological macromolecules and their complexes. In order to achieve the best performance and efficiency, it is crucial to benchmark various hardware platforms for the simulations of realistic biomolecular systems with different size and timescale. Here, we compare performance and scalability of a number of commercially available computing architectures using all-atom and coarse-grained molecular dynamics simulations of water and the Ndc80-microtubule protein complex in the GROMACS-2019.4 package. We report typical single-node performance of various combinations of modern CPUs and GPUs, as well as multiple-node performance of the “Lomonosov-2” supercomputer. These data can be used as the practical guidelines for choosing optimal hardware for molecular dynamics simulations.

References

Abraham, M.J., Murtola, T., Schulz, R., et al.: GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1-2, 19–25 (2015), DOI: 10.1016/j.softx.2015.06.001

Abraham, M., van der Spoel, D., Lindahl, E., et al.: The GROMACS development team GROMACS User Manual, version 2019. http://www.gromacs.org (2019)

Fedorov, V.A., Kholina, E.G., Kovalenko, I.B., et al.: Performance analysis of different computational architectures: Molecular dynamics in application to protein assemblies, illustrated by microtubule and electron transfer proteins. Supercomputing Frontiers and Innovations 5(4), 111–114 (2018), DOI: 10.14529/jsfi180414

Fedorov, V.A., Orekhov, P.S., Kholina, E.G., et al.: Mechanical properties of tubulin intra- and inter-dimer interfaces and their implications for microtubule dynamic instability. PLoS computational biology 15(8), e1007327 (2019), DOI: 10.1371/journal.pcbi.1007327

Feenstra, K.A., Hess, B., Berendsen, H.J.C.: Improving efficiency of large time-scale molecular dynamics simulations of hydrogen-rich systems. Journal of Computational Chemistry 20(8), 786–798 (1999), DOI: 10.1002/(SICI)1096-987X(199906)20:8¡786::AIDJCC5¿3.0.CO;2-B

Kholina, E.G., Kovalenko, I.B., Bozdaganyan, M.E., et al.: Cationic antiseptics facilitate pore formation in model bacterial membranes. The Journal of Physical Chemistry B 124(39), 8593–8600 (2020), DOI: 10.1021/acs.jpcb.0c07212

Marrink, S.J., Risselada, H.J., Yefimov, S., et al.: The MARTINI force field: coarse grained model for biomolecular simulations. The journal of physical chemistry B 111(27), 7812–7824 (2007), DOI: 10.1021/jp071097f

Monticelli, L., Kandasamy, S.K., Periole, X., et al.: The MARTINI coarse-grained force field: extension to proteins. Journal of chemical theory and computation 4(5), 819–834 (2008), DOI: 10.1021/ct700324x

Pа́ll, S., Zhmurov, A., Bauer, P., et al.: Heterogeneous parallelization and acceleration of molecular dynamics simulations in GROMACS. The Journal of Chemical Physics 153(13), 134110 (2020), DOI: 10.1063/5.0018516

Parrinello, M., Rahman, A.: Polymorphic transitions in single crystals: A new molecular dynamics method. Journal of Applied physics 52(12), 7182–7190 (1981), DOI: 10.1063/1.328693

Voevodin, V.V., Antonov, A.S., Nikitenko, D.A., et al.: Supercomputer Lomonosov-2: large scale, deep monitoring and fine analytics for the user community. Supercomputing Frontiers and Innovations 6(2), 4–11 (2019), DOI: 10.14529/jsfi190201

Yesylevskyy, S.O., Schäfer, L.V., Sengupta, D., et al.: Polarizable water model for the coarsegrained MARTINI force field. PLoS Comput Biol 6(6), e1000810 (2010), DOI: 10.1371/journal.pcbi.1000810