Abstract
MiMiC is a framework for performing multiscale simulations in which loosely coupled external programs describe individual subsystems at different resolutions and levels of theory. To make it highly efficient and flexible, we adopt an interoperable approach based on a multiple-program multiple-data (MPMD) paradigm, serving as an intermediary responsible for fast data exchange and interactions between the subsystems. The main goal of MiMiC is to avoid interfering with the underlying parallelization of the external programs, including the operability on hybrid architectures (e.g., CPU/GPU), and keep their setup and execution as close as possible to the original. At the moment, MiMiC offers an efficient implementation of electrostatic embedding quantum mechanics/molecular mechanics (QM/MM) that has demonstrated unprecedented parallel scaling in simulations of large biomolecules using CPMD and GROMACS as QM and MM engines, respectively. However, as it is designed for high flexibility with general multiscale models in mind, it can be straightforwardly extended beyond QM/MM. In this article, we illustrate the software design and the features of the framework, which make it a compelling choice for multiscale simulations in the upcoming era of exascale high-performance computing.
| Original language | English |
|---|---|
| Article number | 022501 |
| Journal | Journal of Chemical Physics |
| Volume | 161 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jul 14 2024 |
| Externally published | Yes |
Funding
The authors are grateful to Viacheslav Bolnykh for his essential foundational contributions during the initial phase of the project. The authors also thank Till Kirsch, Michele Cascella, and J\u00FCrgen Gauss for the CFOUR interface and Maria Gabriella Chiariello, Florian Schackert, and Wenping Lyu for their contributions to the studies showed in Sec. VI. B.R., D.M., E.I., and P.C. acknowledge the Helmholtz European Partnering program (Innovative high-performance computing approaches for molecular neuromedicine) for funding. P.C. acknowledges the Deutsche Forschungsgemeinschaft (DFG) RU2518 DynIon and the computing time granted by the JARA Vergabegremium on the JARA partition of the supercomputer JURECA at Forschungszentrum J\u00FClich. U.R. acknowledges funding from the Swiss National Science Foundation via the NCCR MUST and individual Grants Nos. 200020-185092 and 200020-219440, as well as computing time from the Swiss National Computing Centre CSCS. J.M.H.O. gratefully acknowledges the financial support from VILLUM FONDEN (Grant No. VIL29478). The authors are grateful to Viacheslav Bolnykh for his essential foundational contributions during the initial phase of the project. The authors also thank Till Kirsch, Michele Cascella, and J\u00FCrgen Gauss for the CFOUR interface and Maria Gabriella Chiariello, Florian Schackert, and Wenping Lyu for their contributions to the studies showed in Sec. . B.R., D.M., E.I., and P.C. acknowledge the Helmholtz European Partnering program (Innovative high-performance computing approaches for molecular neuromedicine) for funding. P.C. acknowledges the Deutsche Forschungsgemeinschaft (DFG) RU2518 DynIon and the computing time granted by the JARA Vergabegremium on the JARA partition of the supercomputer JURECA at Forschungszentrum J\u00FClich. U.R. acknowledges funding from the Swiss National Science Foundation via the NCCR MUST and individual Grants Nos. 200020-185092 and 200020-219440, as well as computing time from the Swiss National Computing Centre CSCS. J.M.H.O. gratefully acknowledges the financial support from VILLUM FONDEN (Grant No. VIL29478).
| Funders | Funder number |
|---|---|
| Forschungszentrum Jülich | |
| Swiss National Computing Centre | |
| Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung | |
| Deutsche Forschungsgemeinschaft | RU2518 |
| Deutsche Forschungsgemeinschaft | |
| NCCR MUST | 200020-185092, 200020-219440 |
| Villum Fonden | VIL29478 |
| Villum Fonden |