A new parallel method for molecular dynamics simulation of macromolecular systems

Short{range molecular dynamics simulations of molecular systems are commonly parallelized by replicated{data methods, where each processor stores a copy of all atom positions. This enables computation of bonded 2{, 3{, and 4{body forces within the molecular topology to be partitioned among processors straightforwardly. A drawback to such methods is that the inter{processor communication scales as N , the number of atoms, independent of P , the number of processors. Thus, their parallel ee-ciency falls oo rapidly when large numbers of processors are used. In this article a new parallel method for simulating macromolecular or small{molecule systems is presented, called force{decomposition. Its memory and communication costs scale as N= p P , allowing larger problems to be run faster on greater numbers of processors. Like replicated{data techniques, and in contrast to spatial{decomposition approaches , the new method can be simply load{balanced and performs well even for irregular simulation geometries. The implementation of the algorithm in a prototypical macromolecular simulation code ParBond is also discussed. On a 1024{processor Intel Paragon, ParBond runs a standard benchmark simulation of solvated myoglobin with a parallel eeciency of 61% and at 40 times the speed of a vectorized version of CHARMM running on a single Cray Y{MP processor.

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