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SelInv---An Algorithm for Selected Inversion of a Sparse Symmetric Matrix

Published: 01 February 2011 Publication History

Abstract

We describe an efficient implementation of an algorithm for computing selected elements of a general sparse symmetric matrix A that can be decomposed as A = LDLT, where L is lower triangular and D is diagonal. Our implementation, which is called SelInv, is built on top of an efficient supernodal left-looking LDLT factorization of A. We discuss how computational efficiency can be gained by making use of a relative index array to handle indirect addressing. We report the performance of SelInv on a collection of sparse matrices of various sizes and nonzero structures. We also demonstrate how SelInv can be used in electronic structure calculations.

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cover image ACM Transactions on Mathematical Software
ACM Transactions on Mathematical Software  Volume 37, Issue 4
February 2011
212 pages
ISSN:0098-3500
EISSN:1557-7295
DOI:10.1145/1916461
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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Publication History

Published: 01 February 2011
Accepted: 01 August 2010
Revised: 01 March 2010
Received: 01 October 2009
Published in TOMS Volume 37, Issue 4

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Author Tags

  1. Electronic structure calculation
  2. elimination tree
  3. selected inversion
  4. sparse LDLT factorization
  5. supernodes

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