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

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 supermodal 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.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 16, 2009
Accession Number
ADA522688

Entities

People

  • Chao Yang
  • Jianfeng Lu
  • Juan C. Meza
  • Lexing Ying
  • Lin Lin
  • Weinan E

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Addressing
  • Algebra
  • Algorithms
  • Computational Science
  • Computations
  • Crystal Structure
  • Density Functional Theory
  • Electron Density
  • Electrons
  • Floating Point Operations
  • Inversion
  • Linear Algebra
  • Mathematics
  • Solid State Physics
  • Sparse Matrix
  • Three Dimensional
  • Two Dimensional

Readers

  • Distributed Systems and Data Platform Development
  • Linear Algebra

Technology Areas

  • Microelectronics