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Parallel pseudospectral electronic structure: I. Hartree–Fock calculations
Author(s) -
Chasman David,
Beachy Michael D.,
Wang Limin,
Friesner Richard A.
Publication year - 1998
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/(sici)1096-987x(19980715)19:9<1017::aid-jcc3>3.0.co;2-t
Subject(s) - eigenvalues and eigenvectors , partition (number theory) , parallel computing , basis (linear algebra) , fock matrix , computer science , lanczos resampling , computational science , scalability , basis set , code (set theory) , hartree–fock method , mathematics , algorithm , set (abstract data type) , computational chemistry , physics , chemistry , quantum mechanics , geometry , density functional theory , combinatorics , database , programming language
We present an outline of the parallel implementation of our pseudospectral electronic structure program, Jaguar, including the algorithm and timings for the Hartree–Fock and analytic gradient portions of the program. We also present the parallel algorithm and timings for our Lanczos eigenvector refinement code and demonstrate that its performance is superior to the ScaLAPACK diagonalization routines. The overall efficiency of our code increases as the size of the calculation is increased, demonstrating actual as well as theoretical scalability. For our largest test system, alanine pentapeptide [818 basis functions in the cc‐pVTZ(‐f) basis set], our Fock matrix assembly procedure has an efficiency of nearly 90% on a 16‐processor SP2 partition. The SCF portion for this case (including eigenvector refinement) has an overall efficiency of 87% on a partition of 8 processors and 74% on a partition of 16 processors. Finally, our parallel gradient calculations have a parallel efficiency of 84% on 8 processors for porphine (430 basis functions). © 1998 John Wiley & Sons, Inc. J Comput Chem 19: 1017–1029, 1998