## Abstract

Most common multicomputer networks, e.g. d-ary h-cubes, are graph topologies where an edge (channel) interconnects exactly two vertices (nodes). Hypergraphs are a generalisation of the graph model, where a channel interconnects an arbitrary number of nodes. Previous studies have used synthetic workloads (e.g. statistical distributions) to stress the superior performance characteristics of regular multi-dimensional hypergraphs, also known as hypermeshes, over d-ary h-cubes. There has been, however, hardly any study that has considered real-world parallel applications. This paper contributes towards filling this gap by providing a comparative study of the performance of one of the most common numerical problems, namely matrix factorisation, on the hypermesh, hypercube, and d-ary h-cube, To this end, the paper first introduces orthogonal networks as a unified model for describing both the graph and hypergraph topologies. It then develops a generalised parallel algorithm for matrix factorisation and evaluates its performance on the hypermesh, hypercube and d-ary h-cube. The results reveal that the hypermesh supports matrix computation more efficiently, and therefore provides more evidence of the hypermesh as a viable network for future large-scale multicomputers.

Original language | English |
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Pages (from-to) | 37-53 |

Number of pages | 17 |

Journal | Journal of Supercomputing |

Volume | 20 |

Issue number | 1 |

DOIs | |

Publication status | Published - Aug 2001 |

## Keywords

- Gaussian elimination
- Hypermeshes
- Interconnection networks
- Matrix factorization
- Multicomputers
- Orthogonal networks
- Performance analysis

## ASJC Scopus subject areas

- Software
- Theoretical Computer Science
- Information Systems
- Hardware and Architecture