A3 Book section, Chapters in research books
GROMEX : A Scalable and Versatile Fast Multipole Method for Biomolecular Simulation (2020)


Kohnke, Bartosz; Ullmann, Thomas R.; Beckmann, Andreas; Kabadshow, Ivo; Haensel, David; Morgenstern, Laura; Dobrev, Plamen; Groenhof, Gerrit; Kutzner, Carsten; Hess, Berk; Dachsel, Holger et al. (2020). GROMEX : A Scalable and Versatile Fast Multipole Method for Biomolecular Simulation. In Bungartz, H, Reiz, S, Uekermann, B, Neumann, P, Nagel, WE (Eds.) Software for Exascale Computing - SPPEXA 2016-2019, Lecture Notes in Computational Science and Engineering, 136. Cham: Springer International Publishing, 517-543. DOI: 10.1007/978-3-030-47956-5_17


JYU authors or editors


Publication details

All authors or editors: Kohnke, Bartosz; Ullmann, Thomas R.; Beckmann, Andreas; Kabadshow, Ivo; Haensel, David; Morgenstern, Laura; Dobrev, Plamen; Groenhof, Gerrit; Kutzner, Carsten; Hess, Berk; et al.

Parent publication: Software for Exascale Computing - SPPEXA 2016-2019

Parent publication editors: Bungartz, H, Reiz, S, Uekermann, B, Neumann, P, Nagel, WE

ISBN: 978-3-030-47955-8

eISBN: 978-3-030-47956-5

Journal or series: Lecture Notes in Computational Science and Engineering

ISSN: 1439-7358

eISSN: 2197-7100

Publication year: 2020

Number in series: 136

Pages range: 517-543

Publisher: Springer International Publishing

Place of Publication: Cham

Publication country: Switzerland

Publication language: English

DOI: http://doi.org/10.1007/978-3-030-47956-5_17

Open Access: Publication channel is not openly available


Abstract

Atomistic simulations of large biomolecular systems with chemical variability such as constant pH dynamic protonation offer multiple challenges in high performance computing. One of them is the correct treatment of the involved electrostatics in an efficient and highly scalable way. Here we review and assess two of the main building blocks that will permit such simulations: (1) An electrostatics library based on the Fast Multipole Method (FMM) that treats local alternative charge distributions with minimal overhead, and (2) A $λ$-dynamics module working in tandem with the FMM that enables various types of chemical transitions during the simulation. Our $λ$-dynamics and FMM implementations do not rely on third-party libraries but are exclusively using C++ language features and they are tailored to the specific requirements of molecular dynamics simulation suites such as GROMACS. The FMM library supports fractional tree depths and allows for rigorous error control and automatic performance optimization at runtime. Near-optimal performance is achieved on various SIMD architectures and on GPUs using CUDA. For exascale systems, we expect our approach to outperform current implementations based on Particle Mesh Ewald (PME) electrostatics, because FMM avoids the communication bottlenecks caused by the parallel fast Fourier transformations needed for PME.


Keywords: biomolecules; simulation; electrostatics


Contributing organizations


Ministry reporting: Yes


Last updated on 2020-04-08 at 11:39