TRLan software package
[Documentation (PS)
(HTML)]
[Software (gzipped tar file), last updated on Oct 10, 2010]
[Software license]
 Motivation
 By some estimates, more than 90% of the eigenvalue problems solved
are real symmetric or complex Hermitian problems. For many of these
problems, the discrete form of the operators (a.k.a the matrices) are
simply too large to store in computer memory. Typically, a small
fraction of the total eigenvalues and eigenvectors are wanted, and the
wanted one are often the extreme eigenvalues. In these cases, it is
fairly difficult to work with the matrices directly. However, through
years of research, many fast schemes have been developed to multiply
these matrices on vectors. The software package we developed is mainly
targetted for this type of eigenvalue problems. By limiting the scope
of its functionalities, we are able to provide a small, efficient and
userfriendly software package.
 Overview of the software
 This software package implements the thickrestart Lanczos
method. It can be used on either a single address space machine or
a distributed parallel machine. The user can choose to implement or use
a matrixvector multiplication routine in any form convenient.
Most of the arithmetic computations in the software
are done through calls to BLAS and LAPACK.
The software is written in Fortran 90. Because Fortran 90 offers many
utility functions such functions such as dynamic memory management,
timing functions, random number generator and so on, the program is
easily portable to different machines without modifying the source
code. It can also be easily accessed from other language
such as C or C++. Since the software is highly modularized, it
relatively easy to adopt it for different type of situation. For
example if the eigenvalue problem may have some symmetry and only a
portion of the physical domain is discretized, then the dotproduct
routine needs to be modified. In this software, this modification is
limited to one subroutine.
It also can be instructed to write checkpoint files so that it can be
restarted is a later time.
 Selected publications

I. Yamazaki, Z. Bai, H. Simon, L.W. Wang, and K. Wu. Adaptive Projection
Subspace Dimension for the ThickRestart Lanczos
Method. Tech report LBNL1059E.
2008.ACM TOMS 37:3

K. Wu and H. Simon, Thickrestart Lanczos method for
large symmetric eigenvalue problems. SIAM Journal on Matrix Analysis and Applications
Vol. 22, No. 2, pp. 602616, 2001.
An early draft of this paper is
available as LBNL tech report 41412.

K. Wu and H. Simon,
TRLAN user guide,
Lawrence Berkeley National Laboratory tech report number LBNL42953.
[executive summary]
[PS document]
[HTML document]
[Software (gzipped tar file)]
 Application known to use TRLan
 Berkeley
Segmentation Engine
 Papers that cites TRLan
 Papers
that cite the TRLan
algorithm
 Papers
that cite TRLan
User Guide
Disclaimers
This page is maintained by John Wu
Last modified on $Date: 2005/04/04 16:09:57 $