This is the old home page of the PARINT project in the Department of Computer Science at Western Michigan University and Washington State University. The PARINT Project was developed with support from the National Science Foundation under the award ACR-0000442.

We are working on a new web page and on a new release, ParInt2.0.
ParInt1.2 links are provided under Downloading below. The adaptive code works as expected, but the MC and QMC codes do not because their dependence on the random number generator needs modifications.

Announcements

Note: The versions under Software Downloading target 32-bit systems, and need fixes for dynamic linking on 64-bit systems. This will be addressed in ParInt 2.0.

PARINT1.2 - beta

The PARINT Version 1.2 beta includes significant improvements: the use of Quasi-Monte Carlo techniques over arbitrary hyperrectangular regions, parallel Monte Carlo and integration over simplex regions.
 

PARINT1.1 Release

Features of this release include additional integration rules and improved memory handling methods for reducing memory use when solving very large problems.
 

Project Overview

The goals of the PARINT project include: to investigate new techniques for computing multivariate integrals in parallel, as well as numerical methods and high precision computations; to study applications of the package, for example in high energy physics, Bayesian statistics and computational finance; and to develop a user-friendly software interface for the package. Research areas include load balancing, distributed data structures, parallel quasi-Monte Carlo techniques and extrapolation.

Downloading

PARINT1.1 incorporates a set of basic techniques for solving multivariate integration problems numerically. One of the basic algorithms is parallel global adaptive integration, with each process storing its own priority queue of subproblems, and incorporating a scheduler-based local load balancing technique. Features include: Users can download the parint1.2-beta release and the documentation.

You can view the website of our HPCS (High Performance Computational Science) Laboratory at http://www.cs.wmich.edu/~hpcs

People

Elise de Doncker and John Kapenga lead the project at Western Michigan University, Alan Genz at Washington State University. This project was funded in part by the National Science Foundation and Western Michigan University. If you are interested in contributing or have any questions, please contact one of the authors.
Click on icon to email us with questions or comments.