Article
A Parallel Distributed Data CPHF Algorithm for Analytic Hessians
Journal of Computational Chemistry
Document Type
Article
Disciplines
Publication Version
Published Version
Publication Date
7-1-2007
DOI
10.1002/jcc.20633
Abstract
One of the most commonly used means to characterize potential energy surfaces of reactions and chemical systems is the Hessian calculation, whose analytic evaluation is computationally and memory demanding. A new scalable distributed data analytic Hessian algorithm is presented. Features of the distributed data parallel coupled perturbed Hartree-Fock (CPHF) are (a) columns of density-like and Fock-like matrices are distributed among processors, (b) an efficient static load balancing scheme achieves good work load distribution among the processors, (c) network communication time is minimized, and (d) numerous performance improvements in analytic Hessian steps are made. As a result, the new code has good performance which is demonstrated on large biological systems.
Rights
Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.
Language
en
File Format
application/pdf
Citation Information
Yuri Alexeev, Michael Schmidt, Theresa Lynn Windus and Mark S. Gordon. "A Parallel Distributed Data CPHF Algorithm for Analytic Hessians" Journal of Computational Chemistry Vol. 28 Iss. 10 (2007) p. 1685 - 1694 Available at: http://works.bepress.com/theresa-windus/7/
This article is from Journal of Computational Chemistry 28 (2007): 1685, doi:10.1002/jcc.20633.