Pseudorandom number generator for massively parallel molecular-dynamics simulations

Brad Lee Holian, Ora E. Percus, Tony T. Warnock, and Paula A. Whitlock
Phys. Rev. E 50, 1607 – Published 1 August 1994
PDFExport Citation

Abstract

A class of uniform pseudorandom number generators is proposed for modeling and simulations on massively parallel computers. The algorithm is simple, nonrecursive, and is easily transported to serial or vector computers. We have tested the procedure for uniformity, independence, and correlations by several methods. Related, less complex sequences passed some of these tests well enough; however, inadequacies were revealed by tests for correlations and in an interesting application, namely, annealing from an initial lattice that is mechanically unstable. In the latter case, initial velocities chosen by a random number generator that is not sufficiently random lead quickly to unphysical regularity in grain structure. The new class of generators passes this dynamical diagnostic for unwanted correlations.

  • Received 22 November 1993

DOI:https://doi.org/10.1103/PhysRevE.50.1607

©1994 American Physical Society

Authors & Affiliations

Brad Lee Holian

  • Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545

Ora E. Percus

  • Courant Institute of Mathematical Science, New York University, 251 Mercer Street, New York, New York 10012

Tony T. Warnock

  • Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545

Paula A. Whitlock

  • Computer and Information Sciences Department, Brooklyn College, 2900 Bedford Avenue, Brooklyn, New York 11210

References (Subscription Required)

Click to Expand
Issue

Vol. 50, Iss. 2 — August 1994

Reuse & Permissions
Access Options
Author publication services for translation and copyediting assistance advertisement

Authorization Required


×
×

Images

×

Sign up to receive regular email alerts from Physical Review E

Log In

Cancel
×

Search


Article Lookup

Paste a citation or DOI

Enter a citation
×