Making Puzzle Pieces Fit or Reshaping MiMiC for Multiscale Simulations with CP2K and More

MiMiC is a framework for modeling large-scale chemical processes that require treatment at multiple resolutions. It does not aim to implement single-handedly all methods required to treat individual subsystems, but instead, it relegates this task to specialized computational chemistry software while it serves as an intermediary between these external programs and computes the interactions between the subsystems. MiMiC minimizes issues typically associated with molecular dynamics performed with multiple programs by adopting a multiple-program multiple-data paradigm combined with a loose-coupling model. In this work, we present the addition of a new client program, CP2K, to the MiMiC ecosystem. Moreover, to align the implementation of MiMiC with its modular philosophy, we performed a major refactoring of the entire framework. This endeavor unlocks its full flexibility and reduces any future efforts for introducing new programs to a minimum. Furthermore, by thorough timing analysis, we verify that the introduced changes do not affect the performance of MiMiC or CP2K, and neither are they a source of significant computational overheads that would be detrimental to simulation efficiency. Finally, we demonstrate the benefits of the framework's modular design, by performing a QM/MM MD simulation combining CP2K with previously interfaced OpenMM, with no additional implementation effort required.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2025-05-06
DOI
https://doi.org/10.1021/acs.jcim.5c00409
Citations
4
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
2.07

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Making Puzzle Pieces Fit or Reshaping MiMiC for Multiscale Simulations with CP2K and More

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article

Making Puzzle Pieces Fit or Reshaping MiMiC for Multiscale Simulations with CP2K and More

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article en
4 citations

Abstract

MiMiC is a framework for modeling large-scale chemical processes that require treatment at multiple resolutions. It does not aim to implement single-handedly all methods required to treat individual subsystems, but instead, it relegates this task to specialized computational chemistry software while it serves as an intermediary between these external programs and computes the interactions between the subsystems. MiMiC minimizes issues typically associated with molecular dynamics performed with multiple programs by adopting a multiple-program multiple-data paradigm combined with a loose-coupling model. In this work, we present the addition of a new client program, CP2K, to the MiMiC ecosystem. Moreover, to align the implementation of MiMiC with its modular philosophy, we performed a major refactoring of the entire framework. This endeavor unlocks its full flexibility and reduces any future efforts for introducing new programs to a minimum. Furthermore, by thorough timing analysis, we verify that the introduced changes do not affect the performance of MiMiC or CP2K, and neither are they a source of significant computational overheads that would be detrimental to simulation efficiency. Finally, we demonstrate the benefits of the framework's modular design, by performing a QM/MM MD simulation combining CP2K with previously interfaced OpenMM, with no additional implementation effort required.

Journal of Chemical Information and ModelingVol. 65(10)
Debre Tabor University (ET), École Polytechnique Fédérale de Lausanne (CH), Technical University of Denmark (DK)
Villum Fonden, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Openalex Percentile: Top 14%
Machine Learning in Materials Science
2.07
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