Sparse Eigensolvers for Java (SEJ) builds on top of MTJ to provide eigenvalue and eigenvector solvers for sparse matrices.

Status

SEJ is currently in ALPHA and the API is subject to change: we hope to create a common API for a large variety of solvers, making it as easy as possible for clients to change the solver backend.

The following sparse solvers have been implemented:

• LOBPCG

and the following are planned shortly:

• ARPACK
• Block Davidson

Installation

SEJ is a Java library, not a standalone application. Add the SEJ (and MTJ) jars to your build path. If you are getting java.lang.NoClassDefFoundError exceptions, you probably forgot to do this step.

When the API becomes stable, SEJ will be distributed via Maven.

Documentation

Clients are advised to link their IDEs to the source code of this project in order to see the Javadocs and to study the test cases for example use cases.

The LobpcgJavaExamples page shows some use case examples.

References

1. The Symmetric Eigenvalue Problem, Beresford N. Parlett, Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA, 1998. Corrected reprint of the 1980 original.
2. Toward The Optimal Preconditioned Eigensolver: Locally Optimal Block Preconditioned Conjugate Gradient Method, A. V. Knyazev, SIAM Journal on Scientic Computing 23 (2001), no. 2, pp. 517-541.
3. Block Locally Optimal Preconditioned Eigenvalue Xolvers (BLOPEX) in hypre and PETSc, A. V. Knyazev, I. Lashuk, M. E. Argentati, and E. Ovchinnikov, SIAM Journal on Scientific Computing (SISC), Vol. 29 (2007), No. 5, pp. 2224-2239.
4. A Comparison of Eigensolvers for Large-scale 3D Modal Analysis Using AMG-Preconditioned Iterative Methods, (with Peter Arbenz, Ulrich Hetmaniuk, Ray Tuminaro), International Journal for Numerical Methods in Engineering, Volume 64, pp. 204-236, 2005.
5. A Survey of Software for Sparse Eigenvalue Problems, V. Hernández, J. E. Román, A. Thomás and V. Vidal, SLEPc Technical Report STR-6, June 2007.