SPRNG

Abstract

Computational stochastic approaches (Monte Carlo methods) based on the random sampling are becoming extremely important research tools not only in their "traditional" fields such as physics, chemistry or applied mathematics but also in social sciences and, recently, in various branches of industry. An indication of importance is, for example, the fact that Monte Carlo calculations consume about one half of the supercomputer cycles. One of the indispensable and important ingredients for reliable and statistically sound calculations is the source of pseudo random number generators. The goal of our project is to develop, implement and test a scalable package for parallel pseudo random number generation which will be easy to use on a variety of architectures, especially in large scale Monte-Carlo applications

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