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A parallel distributed data CPHF algorithm for analytic Hessians
Author(s) -
Alexeev Yuri,
Schmidt Michael W.,
Windus Theresa L.,
Gordon Mark S.
Publication year - 2007
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.20633
Subject(s) - hessian matrix , scalability , distributed memory , computer science , code (set theory) , parallel computing , scheme (mathematics) , algorithm , mathematics , shared memory , mathematical analysis , set (abstract data type) , database , programming language
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. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2007