Experiences with different parallel programming paradigms for Monte Carlo particle transport leads to a portable toolkit for parallel Monte Carlo.

摘要

Monte Carlo particle transport is easy to implement on massively parallel computers relative to other methods of transport simulation. This paper describes experiences of implementing a realistic demonstration Monte Carlo code on a variety of parallel architectures. Our ''pool of tasks'' technique, which allows reproducibility from run to run regardless of the number of processors, is discussed. We present detailed timing studies of simulations performed on the 128 processor BBN-ACI TC2000 and preliminary timing results for the 32 processor Kendall Square Research KSR-1. Given sufficient workload to distribute across many computational nodes, the BBN achieves nearly linear speedup for a large number of nodes. The KSR, with which we have had less experience, performs poorly with more than ten processors. A simple model incorporating known causes of overhead accurately predicts observed behavior. A general-purpose communication and control package to facilitate the implementation of existing Monte Carlo packages is described together with timings on the BBN. This package adds insignificantly to the computational costs of parallel simulations.