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A highly adaptive load balancing algorithm for parallel simulations usingparticle methods, such as molecular dynamics and smoothed particlehydrodynamics (SPH), is developed. Our algorithm is based on the dynamicspatial decomposition of simulated material samples between Voronoi subdomains,where each subdomain with all its particles is handled by a singlecomputational process which is typically run on a single CPU core of amultiprocessor computing cluster.  The algorithm displaces the positions of neighbor Voronoi subdomains inaccordance with the local load imbalance between the corresponding processes.It results in particle transfers from heavy-loaded processes to less-loadedones. Iteration of the algorithm puts into alignment the processor loads.Convergence to a well-balanced decomposition from imbalanced one is improved bythe usage of multi-body terms in the balancing displacements.  The high adaptability of the balancing algorithm to simulation conditions isillustrated by SPH modeling of the dynamic behavior of materials under extremeconditions, which are characterized by large pressure and velocity gradients,as a result of which the spatial distribution of particles varies greatly intime. The higher parallel efficiency of our algorithm in such conditions isdemonstrated by comparison with the corresponding static decomposition of thecomputational domain. Our algorithm shows almost perfect strong scalability intests using from tens to several thousand processes.

Parallel SPH modeling using dynamic domain decomposition and load balancing displacement of Voronoi subdomains