Journal ArticleDOI
A note on sparse factorization in a paging environment
TLDR
It is shown experimentally that an equivalent reordering, if appropriately chosen, can reduce the CPU time and elapsed time for sparse factorization.Abstract:
The impact of reordering on the Cholesky factorization of a sparse matrix in a paging environment is examined. We show experimentally that an equivalent reordering, if appropriately chosen, can reduce the CPU time and elapsed time for sparse factorization.read more
Citations
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Book ChapterDOI
The Mosek Interior Point Optimizer for Linear Programming: An Implementation of the Homogeneous Algorithm
TL;DR: The MOSEK optimizer is based on the homogeneous interior-point algorithm which in contrast to the primal-dual algorithm detects a possible primal or dual infeasibility reliably reliably.
Journal ArticleDOI
A survey of direct methods for sparse linear systems
TL;DR: The goal of this survey article is to impart a working knowledge of the underlying theory and practice of sparse direct methods for solving linear systems and least-squares problems, and to provide an overview of the algorithms, data structures, and software available to solve these problems.
Journal ArticleDOI
Memory Management Issues in Sparse Multifrontal Methods On Multiprocessors
Patrick R. Amestoy,Lain S. Duff +1 more
TL;DR: A flexible memory man agement scheme which adapts well to a variation in the size of the working area and/or the number of pro cessors is designed, which is useful when designing an efficient memory management scheme for a wider range of parallel applications.
Journal ArticleDOI
Efficient sparse matrix factorization on high performance workstations—exploiting the memory hierarchy
Edward Rothberg,Anoop Gupta +1 more
TL;DR: This paper considers the problem of Cholesky factorization of a large sparse positive definite system of equations on a high-performance workstation and finds that the major factor limiting performance is the cost of moving data between memory and the processor.
Journal ArticleDOI
The multifrontal method and paging in sparse Cholesky factorization
TL;DR: It is shown that the multif prefrontal method can have significant advantage over the conventional sparse column-Cholesky scheme on a paged virtual memory system and over the multifrontal method in its adaptability to the amount of available working storage.
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