Node Selection Strategies for Bottom-Up Sparse Matrix Ordering

1998 ◽  
Vol 19 (3) ◽  
pp. 682-695 ◽  
Author(s):  
Edward Rothberg ◽  
Stanley C. Eisenstat
Keyword(s):  
Sparse Matrix ◽  
Node Selection ◽  
Bottom Up ◽  
Selection Strategies ◽  
Sparse Matrix Ordering ◽  
Matrix Ordering

PMORSy: parallel sparse matrix ordering software for fill-in minimization

2016 ◽  
Vol 32 (2) ◽  
pp. 274-289 ◽  
Author(s):  
Anna Pirova ◽  
Iosif Meyerov ◽  
Evgeniy Kozinov ◽  
Sergey Lebedev
Keyword(s):  
Sparse Matrix ◽  
Sparse Matrix Ordering ◽  
Matrix Ordering

Fast recommendation on bibliographic networks with sparse-matrix ordering and partitioning

2013 ◽  
Vol 3 (4) ◽  
pp. 1097-1111 ◽  
Author(s):  
Onur Küçüktunç ◽  
Kamer Kaya ◽  
Erik Saule ◽  
Ümit V. Çatalyürek
Keyword(s):  
Sparse Matrix ◽  
Sparse Matrix Ordering ◽  
Matrix Ordering

Implementing Sparse Matrix Ordering Using Hypergraph Partitioning

2013 ◽  
Vol 706-708 ◽  
pp. 1890-1893
Author(s):  
Lu Yao ◽  
Yi Yang ◽  
Zheng Hua Wang ◽  
Wei Cao
Keyword(s):  
Sparse Matrix ◽  
Factorization Method ◽  
Cholesky Factorization ◽  
The Novel ◽  
Nested Dissection ◽  
Vertex Separator ◽  
Hypergraph Partitioning ◽  
Ordering Algorithms ◽  
Sparse Matrix Ordering ◽  
Matrix Ordering

Matrix ordering is a key technique when applying Cholesky factorization method to solving sparse symmetric positive definite system Ax = b. Much effort has been devoted to the development of powerful heuristic ordering algorithms. This paper implements a sparse matrix ordering scheme based on hypergraph partitioning. The novel nested dissection ordering scheme achieve the vertex separator by hypergraph partitioning. Experimental results show that the novel scheme produces results that are substantially better than METIS.

Sign in / Sign up

Export Citation Format

Share Document