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 numbers. The goal of this 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 parallel Monte Carlo applications.

WWW: http://www.sprng.org/