GENERATION OF DISCRETE RANDOM VARIABLES ON VECTOR COMPUTERS FOR MONTE CARLO SIMULATIONS

作     者：RIYANARTO SARNO VIRENDRA C. BHAVSAR ESAM M.A. HUSSEIN 

作者机构：Faculty of Computer Science Canada Department of Mechanical Engineering University of New Brunswick Fredericton N.B. Canada E3B 5A3 Canada 

出 版 物：《International Journal of High Speed Computing》 

年 卷 期：1990年第2卷第4期

页      面：335-350页

主　　题：Discrete random variables importance sampling Monte Carlo simulation parallel processing supercomputing vector processing 

摘      要：The paper reviews existing methods for generating discrete random variables and their suitability for vector processing. A new method for generating discrete random variables for use in vectorized Monte Carlo simulations is presented. The method uses the concept of importance sampling and generates random variables by employing uniform distribution to speed up the computation. The sampled random variables are subsequently adjusted so that unbiased estimates are obtained. The method preserves both the mean and variance of the original distribution. It is demonstrated that the method requires simpler coding and shorter execution time for both scalar and vector processing, when compared with other existing methods. The vectorization speedup of the method is demonstrated on an IBM 3090–180 machine with a vector facility.