n-Cube model for cluster computing and its evaluation

Tian Song*, Dongsheng Wang, Meizhi Hu, Yibo Xue

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Cluster systems are widely used in modern high performance computing. With the rapidly increasing of parallel algorithms, it is an open problem to analyze and evaluate whether they take good advantage of the computing and network resources of clusters.[1-3] We present a novel mathematic model(n-Cube Model for Cluster Computing) that epitomizes the algorithms commonly used on clusters and evaluate this model using Stochastic Petri Nets (SPN). The state space of our model's SPN is also discussed formally. Finally, we take MM5(the FifthGeneration Model) as a case and the comparative performance analysis shows the immense vitality of the model.

Original languageEnglish
Title of host publicationAdvanced Parallel Processing Technologies - 7th International Symposium, APPT 2007
PublisherSpringer Verlag
Pages340-351
Number of pages12
ISBN (Print)9783540768364
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event7th International Symposium on Advanced Parallel Processing Technologies, APPT 2007 - Guangzhou, China
Duration: 22 Nov 200723 Nov 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4847 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Symposium on Advanced Parallel Processing Technologies, APPT 2007
Country/TerritoryChina
CityGuangzhou
Period22/11/0723/11/07

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