Long-range interactions & parallel scalability in molecular simulations

TL;DR

This study benchmarks electrostatic interaction methods in molecular simulations using GROMACS across various hardware architectures, revealing that particle-mesh Ewald performs well and providing guidance for optimizing computational efficiency.

Contribution

It provides a comprehensive performance analysis of electrostatic schemes on diverse computer architectures, aiding in the selection of optimal simulation configurations.

Findings

Particle-mesh Ewald (PME) performs well on most architectures.

Parallel scalability varies with network type and hardware.

Results help predict simulation speed and optimize hardware use.

Abstract

Typical biomolecular systems such as cellular membranes, DNA, and protein complexes are highly charged. Thus, efficient and accurate treatment of electrostatic interactions is of great importance in computational modelling of such systems. We have employed the GROMACS simulation package to perform extensive benchmarking of different commonly used electrostatic schemes on a range of computer architectures (Pentium-4, IBM Power 4, and Apple/IBM G5) for single processor and parallel performance up to 8 nodes - we have also tested the scalability on four different networks, namely Infiniband, GigaBit Ethernet, Fast Ethernet, and nearly uniform memory architecture, i.e., communication between CPUs is possible by directly reading from or writing to other CPUs' local memory. It turns out that the particle-mesh Ewald method (PME) performs surprisingly well and offers competitive performance unless parallel runs on PC hardware with older network infrastructure are needed. Lipid bilayers of sizes 128, 512 and 2048 lipid molecules were used as the test systems representing typical cases encountered in biomolecular simulations. Our results enable an accurate prediction of computational speed on most current computing systems, both for serial and parallel runs. These results should be helpful in, for example, choosing the most suitable configuration for a small departmental computer cluster.