期刊
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE
卷 37, 期 4, 页码 -出版社
ASSOC COMPUTING MACHINERY
DOI: 10.1145/1916461.1916464
关键词
Design; Performance; Electronic structure calculation; elimination tree; selected inversion; sparse LDLT factorization; supernodes
资金
- NSF [DMS-0708026, DMS-0914336]
- Doe [DE-FG02-03ER25587]
- ONR [N00014-01-1-0674]
- University of Texas at Austin
- Director, Office of Science, Division of Mathematical, Information, and Computational Sciences of the U.S. Department of Energy [DE-AC02-05CH11231]
- Director, Office of Advanced Scientific Computing Research of the U.S. Department of Energy [DE-AC02-05CH11232]
- Direct For Mathematical & Physical Scien
- Division Of Mathematical Sciences [0914336] Funding Source: National Science Foundation
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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