Abstract
This work presents a parallel approach of the Kinetic Monte Carlo (KMC) algorithm using a distributed memory architecture. The resulting computer software was tested by conducting crystal growth simulations on barite (001) face. Execution times, simulated times and crystallization velocities are compared with a shared memory parallel KMC software (MMonCa). Finally, a ≈ 1 μm2 crystal growth simulation is performed and compared with atomic force microscopy crystal growth experiments. The capability of this approach is demonstrated: a) a significant reduction of parallel overhead is achieved when comparing to the shared memory parallel version of the software, b) a distributed memory approach achieves an increase in memory resources enough to perform simulations with lattice sizes about 1 μm2, allowing the study of larger structures than those in shared memory or sequential implementations, c) this approach should be used only with large scale simulations to take advantage of the distributed memory architecture, d) further improvements are needed for parallel KMC to be faster than serial KMC in small scale simulations, e) the KMC algorithm used is able to adequately simulate two‐dimensional nucleation on large areas of barite (001) faces.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
