A Scalable Library For Pseudorandom Number Generation Therory And Practice
Description of the Seminar I
September 2, 1997
This seminar is given by Dr. Mascagni, Director of the Scientific Computing P.h.D. Program in School of Mathematical Sciences of University of Southern Mississippi.
The two of the main goals of the scalable library for pseudorandom number generation theory and practice is:
1. to use new results in pseudorandom number generation to create an easy and effective new tool.
2. to create a tool that facilitates experimental Monte Carlo computation on scalable patform.
A scalable pseudorandom number generation tool for Monte Carlo must allow the computational scientist to use their computational environment as a numerical laboratory for discovering and verifying new results. Several new mathematical and computer science results serve as the theoretical foundation for this topic's approach.
New mathematical results on parameterized pseudorandom number generators have provided three different mathematical methods that can be uniformly incorporated in the library. These are the: i) additive lagged-Fibonacci; ii) prime modulus linear congruential; and iii) maximal-period shift-register generators.
Given parameterized generators, one can map an enumeration of the generators onto a binary tree in a canonical way. The mapping to the binary tree then permits the assignment and dynamic allocation of pseudorandom number streams in a parallel environment without the need for interprocessor communication. Large-scale calculations will be used to demonstrate the usefulness of the package and power of Monte Carlo approach in general will be carried out.
