Quasi-Newton parallel geometry optimization methods

The Journal of Chemical Physics
Steven K Burger, Paul W Ayers

Abstract

Algorithms for parallel unconstrained minimization of molecular systems are examined. The overall framework of minimization is the same except for the choice of directions for updating the quasi-Newton Hessian. Ideally these directions are chosen so the updated Hessian gives steps that are same as using the Newton method. Three approaches to determine the directions for updating are presented: the straightforward approach of simply cycling through the Cartesian unit vectors (finite difference), a concurrent set of minimizations, and the Lanczos method. We show the importance of using preconditioning and a multiple secant update in these approaches. For the Lanczos algorithm, an initial set of directions is required to start the method, and a number of possibilities are explored. To test the methods we used the standard 50-dimensional analytic Rosenbrock function. Results are also reported for the histidine dipeptide, the isoleucine tripeptide, and cyclic adenosine monophosphate. All of these systems show a significant speed-up with the number of processors up to about eight processors.

References

Jul 13, 2002·Journal of Computational Chemistry·Jon Baker, Peter Pulay
Oct 12, 2004·The Journal of Chemical Physics·Chee Kwan GanMatt Challacombe
Feb 14, 2006·The Journal of Chemical Physics·Steven K Burger, Weitao Yang
Jun 22, 2007·The Journal of Chemical Physics·A GhyselsM Waroquier
Dec 25, 2007·The Journal of Chemical Physics·Elena F Koslover, David J Wales
Jul 31, 2009·The Journal of Physical Chemistry. a·Johannes KästnerPaul Sherwood
Oct 14, 2008·Journal of Chemical Theory and Computation·Philip BrownFrederick R Manby

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Software Mentioned

MINRES
GAUSSIAN03
Lanzcos

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