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FMM-AutoOpt: A Python Tool for Automated GROMACS FMM Parameter Optimization
Louise J Persson1, Erik G Marklund1
1Department of Chemistry for Life Sciences, Uppsala University, SE-75123Uppsala, Sweden.
Abstract:
The fast multipole method (FMM) for computing Coulombic forces in molecular dynamics (MD) simulations offers benefits for a variety of systems, including nonperiodic configurations such as molecules in vacuum and large-scale systems where many other approaches encounter limitations. Because FMM parameters govern both simulation accuracy and computational performance, and because the optimal solution is highly system-dependent, we have developed FMM-AutoOpt for the automated benchmarking of FMM parameters with GROMACS. Relying solely on standard Python libraries and GROMACS FMM (Kohnke, B.; et al.J. Chem. Theory Comput.2020, 16, 6938-6949.), the tool is versatile and flexible, facilitating rapid parameter screening to ensure optimal performance and high simulation accuracy.
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