A hierarchic sparse matrix data structure for large-scale Hartree-Fock/Kohn-Sham calculations
2007 (English)In: Journal of Computational Chemistry, ISSN 0192-8651, E-ISSN 1096-987X, Vol. 28, no 16, 2531-2537 p.Article in journal (Refereed) Published
A hierarchic sparse matrix data structure for Hartree-Fock/Kohn-Sham calculations is presented. The data structure makes the implementation of matrix manipulations needed for large systems faster, easier, and more maintainable without loss of performance. Algorithms for symmetric matrix square and inverse Cholesky decomposition within the hierarchic framework are also described. The presented data structure is general; in addition to its use in HartreeFock/Kohn-Sham calculations, it may also be used in other research areas where matrices with similar properties are encountered. The applicability of the data structure to ab initio calculations is shown with help of benchmarks on water droplets and graphene nanoribbons.
Place, publisher, year, edition, pages
2007. Vol. 28, no 16, 2531-2537 p.
sparse matrix, C plus plus templates, Hartree-Fock, Density Functional Theory, inverse Cholesky decomposition, symmetric matrix square, electronic-structure calculations, approximate inverse preconditioners, conjugate-gradient method, consistent-field theory, density-matrix, diagonalization, search, purification, atoms
IdentifiersURN: urn:nbn:se:kth:diva-16288DOI: 10.1002/jcc.20691ISI: 000250972500003ScopusID: 2-s2.0-35948953260OAI: oai:DiVA.org:kth-16288DiVA: diva2:334330
QC 201008172010-08-052010-08-052011-08-30Bibliographically approved