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 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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Feb 01, 2011
- Source ID
- 10.1145/1916461.1916464
Entities
People
- Chao Yang
- Jianfeng Lu
- Juan C. Meza
- Lexing Ying
- Lin Lin
- Weinan E
Organizations
- Courant Institute of Mathematical Sciences, NYU
- Lawrence Berkeley National Laboratory
- National Science Foundation Division of Mathematical Sciences
- Office of Advanced Scientific Computing Research
- Office of Naval Research
- Princeton University
- United States Department of Energy
- University of Texas at Austin