A parallel-processing computer program finds a few eigenvalues in a sparse Hermitian matrix that contains as many as 100 million diagonal elements. This program finds the eigenvalues faster, using less memory, than do other, comparable eigensolver programs. This program implements a Lanczos algorithm in the American National Standards Institute/ International Organization for Standardization (ANSI/ISO) C computing language, using the Message Passing Interface (MPI) standard to complement an eigensolver in PARPACK. [PARPACK (Parallel Arnoldi Package) is an extension, to parallel-processing computer architectures, of ARPACK (Arnoldi Package), which is a collection of Fortran 77 subroutines that solve large-scale eigenvalue problems.] The eigensolver runs on Beowulf clusters of computers at the Jet Propulsion Laboratory (JPL). The package is open-source software and is distributed under the terms of the GNU Lesser General Public License (LGPL) on the Internet through the Open Channel Foundation at http://www.openchannelsoftware.com/ .

This program was written by E. Robert Tisdale, Fabiano Oyafuso, Gerhard Klimeck, and R. Chris Brown of Caltech for NASA’s Jet Propulsion Laboratory.

This software is available for commercial licensing. Please contact Don Hart of the California Institute of Technology at (818) 393- 3425. Refer to NPO-30834.

This Brief includes a Technical Support Package (TSP).
Eigensolver for a Sparse, Large Hermitian Matrix

(reference NPO-30834) is currently available for download from the TSP library.

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