Parallel relaxed and extrapolated algorithms for computing PageRank

被引：0
|
作者：
Josep Arnal
Héctor Migallón
Violeta Migallón
Juan A. Palomino
José Penadés
机构：
[1] Universidad de Alicante,Departamento de Ciencia de la Computación e Inteligencia Artificial
[2] Universidad Miguel Hernández,Departamento de Física y Arquitectura de Computadores
来源：
The Journal of Supercomputing | 2014年 / 70卷
关键词：
PageRank; Parallel algorithms; Power method; Relaxation and extrapolation;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, parallel Relaxed and Extrapolated algorithms based on the Power method for accelerating the PageRank computation are presented. Different parallel implementations of the Power method and the proposed variants are analyzed using different data distribution strategies. The reported experiments show the behavior and effectiveness of the designed algorithms for realistic test data using either OpenMP, MPI or an hybrid OpenMP/MPI approach to exploit the benefits of shared memory inside the nodes of current SMP supercomputers.
引用
收藏
页码：637 / 648
页数：11
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