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| Journal Article | FZJ-2020-00305 |
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2019
Washington, DC
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Please use a persistent id in citations: doi:10.1021/acs.jctc.9b00424
Abstract: We present a highly scalable DFT-based QM/MM implementation developed within MiMiC, a recently introduced multiscale modeling framework that uses a loose-coupling strategy in conjunction with a multiple-program multiple-data (MPMD) approach. The computation of electrostatic QM/MM interactions is parallelized exploiting both distributed- and shared-memory strategies. Here, we use the efficient CPMD and GROMACS programs as QM and MM engines, respectively. The scalability is demonstrated through large-scale benchmark simulations of realistic biomolecular systems employing non-hybrid and hybrid GGA exchange–correlation functionals. We show that the loose-coupling strategy adopted in MiMiC, with its inherent high flexibility, does not carry any significant computational overhead compared to a tight-coupling scheme. Furthermore, we demonstrate that the adopted parallelization strategy enables scaling up to 13,000 CPU cores with efficiency above 70%, thus making DFT-based QM/MM MD simulations using hybrid functionals at the nanosecond scale accessible.
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