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dc.contributor.authorKohnke, Bartosz
dc.contributor.authorUllmann, Thomas R.
dc.contributor.authorBeckmann, Andreas
dc.contributor.authorKabadshow, Ivo
dc.contributor.authorHaensel, David
dc.contributor.authorMorgenstern, Laura
dc.contributor.authorDobrev, Plamen
dc.contributor.authorGroenhof, Gerrit
dc.contributor.authorKutzner, Carsten
dc.contributor.authorHess, Berk
dc.contributor.authorDachsel, Holger
dc.contributor.authorGrubmüller, Helmut
dc.contributor.editorBungartz, H
dc.contributor.editorReiz, S
dc.contributor.editorUekermann, B
dc.contributor.editorNeumann, P
dc.contributor.editorNagel, WE
dc.date.accessioned2021-01-07T10:53:09Z
dc.date.available2021-01-07T10:53:09Z
dc.date.issued2020
dc.identifier.citationKohnke, B., Ullmann, T. R., Beckmann, A., Kabadshow, I., Haensel, D., Morgenstern, L., Dobrev, P., Groenhof, G., Kutzner, C., Hess, B., Dachsel, H., & Grubmüller, H. (2020). GROMEX : A Scalable and Versatile Fast Multipole Method for Biomolecular Simulation. In H. Bungartz, S. Reiz, B. Uekermann, P. Neumann, & W. Nagel (Eds.), <i>Software for Exascale Computing - SPPEXA 2016-2019</i> (pp. 517-543). Springer International Publishing. Lecture Notes in Computational Science and Engineering, 136. <a href="https://doi.org/10.1007/978-3-030-47956-5_17" target="_blank">https://doi.org/10.1007/978-3-030-47956-5_17</a>
dc.identifier.otherCONVID_41682536
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/73546
dc.description.abstractAtomistic 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.en
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.language.isoeng
dc.publisherSpringer International Publishing
dc.relation.ispartofSoftware for Exascale Computing - SPPEXA 2016-2019
dc.relation.ispartofseriesLecture Notes in Computational Science and Engineering
dc.rightsCC BY 4.0
dc.titleGROMEX : A Scalable and Versatile Fast Multipole Method for Biomolecular Simulation
dc.typebookPart
dc.identifier.urnURN:NBN:fi:jyu-202101071027
dc.contributor.laitosKemian laitosfi
dc.contributor.laitosDepartment of Chemistryen
dc.type.urihttp://purl.org/eprint/type/BookItem
dc.relation.isbn978-3-030-47955-8
dc.type.coarhttp://purl.org/coar/resource_type/c_3248
dc.description.reviewstatuspeerReviewed
dc.format.pagerange517-543
dc.relation.issn1439-7358
dc.type.versionpublishedVersion
dc.rights.copyright© The Author(s) 2020
dc.rights.accesslevelopenAccessfi
dc.subject.ysosähköstatiikka
dc.subject.ysosimulointi
dc.subject.ysobiomolekyylit
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p13100
jyx.subject.urihttp://www.yso.fi/onto/yso/p4787
jyx.subject.urihttp://www.yso.fi/onto/yso/p27773
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1007/978-3-030-47956-5_17
jyx.fundinginformationThis work is supported by the German Research Foundation (DFG) Cluster of excellence Multiscale Imaging and under the DFG priority programme 1648 Software for Exascale Computing (SPPEXA).
dc.type.okmA3


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