Block partitioning of sparse rectangular matrices

Andrei Dumitraşc; Philippe Leleux; Ulrich Rüde

doi:10.1002/pamm.201900287

ScienceGate Book Chapters

JOURNAL ARTICLE

Block partitioning of sparse rectangular matrices

Andrei Dumitraşc Philippe Leleux Ulrich Rüde

Year: 2019 Journal: PAMM Vol: 19 (1) Publisher: Wiley

DOI: 10.1002/pamm.201900287

Get Full-Text PDF Get Analytical Report

Abstract

Abstract We present a means of reordering large, sparse rectangular matrices such that their nonzeros are closer to the diagonal. This enables a block‐partitioning which is useful in parallel contexts. We use the Reverse Cuthill‐McKee (RCM) algorithm on the adjacency matrix of the associated bipartite graph. The resulting, reordered matrix has a block bidiagonal structure.

Keywords:

Adjacency matrix Bipartite graph Block (permutation group theory) Diagonal Sparse matrix Block matrix Adjacency list Matrix (chemical analysis) Combinatorics Graph Mathematics Computer science Algorithm Geometry Eigenvalues and eigenvectors Materials science Physics

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.18

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Matrix Theory and Algorithms

Physical Sciences → Computer Science → Computational Theory and Mathematics

VLSI and FPGA Design Techniques

Physical Sciences → Engineering → Electrical and Electronic Engineering

Interconnection Networks and Systems

Physical Sciences → Computer Science → Computer Networks and Communications

Block partitioning of sparse rectangular matrices

Abstract

Metrics

Topics

Related Documents

Partitioning sparse rectangular matrices for parallel processing

Permuting Sparse Rectangular Matrices into Block-Diagonal Form

Partitioning Rectangular and Structurally Unsymmetric Sparse Matrices for Parallel Processing

Partitioning sparse rectangular matrices for parallel computations of Ax and A T v

Inverting sparse matrices by tree partitioning