Open AccessAn out-of-core sparse symmetric-indefinite factorization method
Author(s) -
Omer Meshar,
Dror Irony,
Sivan Toledo
Publication year - 2006
Publication title -
acm transactions on mathematical software
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.767
H-Index - 87
eISSN - 1557-7295
pISSN - 0098-3500
DOI - 10.1145/1163641.1163645
Subject(s) - cholesky decomposition , computer science , factorization , parallel computing , core (optical fiber) , incomplete cholesky factorization , code (set theory) , sparse matrix , multi core processor , sparse approximation , algorithm , factor (programming language) , physics , telecommunications , eigenvalues and eigenvectors , set (abstract data type) , quantum mechanics , programming language , gaussian
We present a new out-of-core sparse symmetric-indefinite factorization algorithm. The most significant innovation of the new algorithm is a dynamic partitioning method for the sparse factor. This partitioning method results in very low I/O traffic and allows the algorithm to run at high computational rates, even though the factor is stored on a slow disk. Our implementation of the new code compares well with both high-performance in-core sparse symmetric-indefinite codes and a high-performance out-of-core sparse Cholesky code.
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