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ABSTRACT: This session will provide participants with an opportunity to acquaint themselves with the Scalable Parallel Random Number Generators Library (SPRNG) as it can be used to investigate computational stochastic (Monte Carlo) applications. One of the indispensable and important ingredients for reliable and statistically sound calculations is a good source of pseudorandom numbers. The goal of the SPRNG project is to develop, implement, and test a scalable package for parallel pseudorandom number generation that will be easy to use on a variety of architectures, especially in large-scale parallel Monte Carlo applications. There will be material that allows students to "play with" and visualize certain pseudorandom number generators, and there will also be some examples of simple Monte Carlo computations that use SPRNG. Random number generation is based on simple recurrences; however, if improperly handled, these simple recurrences can produce very nonrandom output that can harm Monte Carlo results.
Chair/Presenter Details:
Michael V. Mascagni (Chair) - Florida State University
