Parallelizing molecular dynamics programs for distributed memory machines

CHARMM (Chemistry at Harvard Macromolecular Mechanics) is a program that is widely used to model and simulate macromolecular systems. CHARMM has been parallelized by using the CHAOS runtime support library on distributed memory architectures. This implementation distributes both data and computations over processors. This data parallel strategy should make it possible to simulate very large molecules on large numbers of processors. In order to minimize communication among processors and to balance computational load, a variety of partitioning approaches are employed to distribute the atoms and computations over processors. In this implementation, atoms are partitioned based on geometrical positions and computational load by using unweighted or weighted recursive coordinate bisection. The experimental results reveal that taking computational load into account is essential. The performance of two iteration partitioning algorithms, atom decomposition and force decomposition, is also compared. A new irregular force decomposition algorithm is introduced and implemented. The CHAOS library is designed to facilitate parallelization of irregular applications. This library (1) couples partitioners to the application programs, (2) remaps data and partitions work among processors, and (3) optimizes interprocessor communications. This paper presents an application of CHAOS that can be used to support efficient execution of irregular problems on distributed memory machines