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Adaptive Projection Subspace Dimension for the Thick-Restart Lanczos Method

Published: 01 September 2010 Publication History

Abstract

The Thick-Restart Lanczos (TRLan) method is an effective method for solving large-scale Hermitian eigenvalue problems. The performance of the method strongly depends on the dimension of the projection subspace used at each restart. In this article, we propose an objective function to quantify the effectiveness of the selection of subspace dimension, and then introduce an adaptive scheme to dynamically select the dimension to optimize the performance. We have developed an open-source software package a--TRLan to include this adaptive scheme in the TRLan method. When applied to calculate the electronic structure of quantum dots, a--TRLan runs up to 2.3x faster than a state-of-the-art preconditioned conjugate gradient eigensolver.

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Published In

cover image ACM Transactions on Mathematical Software
ACM Transactions on Mathematical Software  Volume 37, Issue 3
September 2010
296 pages
ISSN:0098-3500
EISSN:1557-7295
DOI:10.1145/1824801
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 2010
Accepted: 01 February 2010
Revised: 01 October 2009
Received: 01 September 2008
Published in TOMS Volume 37, Issue 3

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Author Tags

  1. Adaptive subspace dimension
  2. Lanczos
  3. electronic structure calculation
  4. thick-restart

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