A COMPARISON BETWEEN 2 MASSIVELY-PARALLEL ALGORITHMS FOR MONTE-CARLO COMPUTER-SIMULATION - AN INVESTIGATION IN THE GRAND-CANONICAL ENSEMBLE

We present a comparison between two different approaches to paralleliz ing the grand canonical Monte Carlo simulation technique (GCMC) for cl assical fluids: a spatial decomposition and a time decomposition. The spatial decomposition relies on the fact that for short-ranged fluids, such as the cut and shifted Lennard-Jones potential used in this work , atoms separated by a greater distance than the reach of the potentia l act independently, and thus different processors can work concurrent ly in regions of the same system which are sufficiently far apart. The time decomposition is an exactly parallel approach which employs simu ltaneous (GCMC) simulations, one per processor, identical in every res pect except the initial random number seed, with the thermodynamic out put variables averaged across all processors. While scaling characteri stics for the spatial decomposition are presented for 8-1024 processor systems, the comparison between the two decompositions is limited to the 8-128 processor range due to the warm-up time and memory imitation s of the time decomposition. Using a combination of speed and statisti cal efficiency, the two algorithms are compared at two different state points. While the time decomposition reaches a given value of standar d error in the system's potential energy more quickly than the spatial decomposition for both densities, the warm-up time demands of the tim e decomposition quickly become insurmountable as the system size incre ases. (C) 1996 by John Wiley & Sons, Inc.