Enrique Saez
Los Alamos National Labs
enriquem at lanl.gov

Sublattice parallel replica dynamics

Exascale computing presents a challenge for the scientific community as new algorithms must be developed to take full advantage of the new computing paradigm. Atomistic simulation methods that offer full fidelity to the underlying potential, i.e., molecular dynamics (MD) and parallel replica dynamics, fail to use the whole machine speedup, leaving a region in time and sample size space that is unattainable with current algorithms. We present an extension of the parallel replica dynamics algorithm A. F. Voter, Phys. Rev. B 57, R13985 (1998) by combining it with the synchronous sublattice approach of Shim and Amar Y. Shim and J. G. Amar, Phys. Rev. B 71, 125432 (2005), thereby exploiting event locality to improve the algorithm scalability. This algorithm is based on a domain decomposition in which events happen independently in different regions in the sample. We develop an analytical expression for the speedup given by this sublattice parallel replica dynamics algorithm and compare it with parallel MD and traditional parallel replica dynamics. We demonstrate how this algorithm, which introduces a slight additional approximation of event locality, enables the study of physical systems unreachable with traditional methodologies and promises to better utilize the resources of current high performance and future exascale computers.