Evaluation of efficient computational work division in parallel Monte Carlo grain growth algorithm

Evaluation of efficient computational work division in parallel Monte Carlo grain growth algorithm

Mateusz Sitko, Łukasz Madej

AGH University of Science and Technology, 30 Mickiewicza Av., Krakow, 30-059 Poland.




Implementation of parallel version of the Monte Carlo (MC) grain growth algorithm is the subject of the present paper. First, modifications of the classical MC grain growth algorithm required for the parallel execution are presented. Then, schemes for the MC space division between subsequent computational threads/nodes are discussed. Finally, implementation details of different parallelization approaches based on OpenMP and MPI are presented and compared. 

Cite as:

Sitko, M., Madej, Ł. (2016).  Evaluation of efficient computational work division in parallel Monte Carlo grain growth algorithm.. Computer Methods in Materials Science, 16(3), 113 – 120. https://doi.org/10.7494/cmms.2016.3.0579

Article (PDF):


Monte Carlo, OpenMP, MPI, Parallelization, Grain growth


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