Parallelization strategies for Monte Carlo simulations of thin film deposition Original Research Article

Atomistic simulations of thin film deposition, based on the lattice Monte Carlo method, provide insights into the microstructure evolution at the atomic level. However, large-scale atomistic simulation is limited on a single computer—due to memory and speed constraints. Parallel computation, although promising in memory and speed, has not been widely applied in these simulations because of the intimidating overhead. The key issue in achieving optimal performance is, therefore, to reduce communication overhead among processors. In this paper, we propose a new parallel algorithm for the simulation of large-scale thin film deposition incorporating two optimization strategies: (1) domain decomposition with sub-domain overlapping and (2) asynchronous communication. This algorithm was implemented both on message-passing-processor systems (MPP) and on cluster computers. We found that both architectures are suitable for parallel Monte Carlo simulation of thin film deposition in either a distributed memory mode or a shared memory mode with message-passing libraries.