Reproducibility in Stochastic Simulation

Name:    Prof. Michael Mascagni                 
Address: Department of Computer Science and
         Department of Mathematics and
	 Department of Scientific Computing and
         Graduate Program in Molecular Biophysics	
         Florida State University
         Tallahassee, FL  32306-4530  USA
         AND
         Information Technology Laboratory
         Applied and Computational Mathematics Division
         100 Bureau Drive M/S 8910
         National Institute of Standards and Technology (NIST)
         Gaithersburg, MD  20899-8910  USA

Offices: 498 Dirac Science Library/207A Love Building (FSU) Building 225/Room B154 (NIST)
Phone:   +1.850.644.3290 (FSU) +1.301.975.2051 (NIST)
FAX:     +1.850.644.0058
e-mail:  mascagni@fsu.edu (FSU) mascagni@nist.gov (NIST)

Title: Reproducibility in Stochastic Simulation

In this talk we consider the issues of reproducibility for stochastic simulation. We define what stochastic computations are, and we first focus on random number generation as a key to controlling reproducibility. We look at different types of random numbers and how to make them reproducible. We then show how the Scalable Parallel Random Number Generators (SPRNG) library was designed partly to ensure absolute random number reproducibility. We then consider situations where even with SPRNG, reproducibility is problematic. We then introduce a much more modest level of reproducibility that we call "Forensic Reproducibility." We then consider another approach to reproducibility in stochastic simulations by noting that certain deterministic systems when computed in the presence of round-off error behave more like solutions to stochastic systems.