Extreme Scalability of DFT-Based QM/MM MD Simulations Using MiMiC

03 May 2019, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


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 GGA and hybrid 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 of 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.


Multiscale models
multiscale modeling
Molecular Dynamics


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