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An analytic model for predicting the performance of distributed applications on multicore clusters

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dc.contributor.author Khanyile, NP
dc.contributor.author Tapamo, J-R
dc.contributor.author Dube, E
dc.date.accessioned 2012-09-17T09:53:41Z
dc.date.available 2012-09-17T09:53:41Z
dc.date.issued 2012-08
dc.identifier.citation Khanyile, NP, Tapamo, J-R and Dube, E. 2012. An analytic model for predicting the performance of distributed applications on multicore clusters. IAENG International Journal of Computer Science, vol. 39(3), pp 312-320 en_US
dc.identifier.issn 1819-656X
dc.identifier.uri http://www.iaeng.org/IJCS/issues_v39/issue_3/IJCS_39_3_11.pdf
dc.identifier.uri http://hdl.handle.net/10204/6099
dc.description IAENG International Journal of Computer Science, vol. 39(3), pp 312-320 en_US
dc.description.abstract Computationally demanding applications can benefit from distributed processing. Distributed processing offers immerse computational power from collections of autonomous systems which can provide up to thousands of processing cores. Over the years, a considerable amount of research has been put towards developing performance prediction models for distributed applications. Amdahl's law states that the speedup of any parallel program has an upper bound which is determined by the amount of time spent on the sequential fraction of the program, no matter how small and regardless of the number of processing nodes used. This paper discusses some of the short comings of this law in the current age. We propose a theoretical model for predicting the behavior of a distributed algorithm given the network restrictions of the cluster used. The paper focuses on the impact of latency and bandwidth which affect the cost of interprocessor communication and the number of processing nodes used to predict the performance. The model shows good accuracy in comparison to Amdahl's law. en_US
dc.language.iso en en_US
dc.publisher International Association of Engineers (IAENG) en_US
dc.relation.ispartofseries Workflow;9545
dc.subject Multicore clusters en_US
dc.subject Amdahl's law en_US
dc.subject Algorithms en_US
dc.subject Propagation delay en_US
dc.subject Bandwith en_US
dc.subject Latency en_US
dc.subject Distributed programming en_US
dc.title An analytic model for predicting the performance of distributed applications on multicore clusters en_US
dc.type Article en_US
dc.identifier.apacitation Khanyile, N., Tapamo, J., & Dube, E. (2012). An analytic model for predicting the performance of distributed applications on multicore clusters. http://hdl.handle.net/10204/6099 en_ZA
dc.identifier.chicagocitation Khanyile, NP, J-R Tapamo, and E Dube "An analytic model for predicting the performance of distributed applications on multicore clusters." (2012) http://hdl.handle.net/10204/6099 en_ZA
dc.identifier.vancouvercitation Khanyile N, Tapamo J, Dube E. An analytic model for predicting the performance of distributed applications on multicore clusters. 2012; http://hdl.handle.net/10204/6099. en_ZA
dc.identifier.ris TY - Article AU - Khanyile, NP AU - Tapamo, J-R AU - Dube, E AB - Computationally demanding applications can benefit from distributed processing. Distributed processing offers immerse computational power from collections of autonomous systems which can provide up to thousands of processing cores. Over the years, a considerable amount of research has been put towards developing performance prediction models for distributed applications. Amdahl's law states that the speedup of any parallel program has an upper bound which is determined by the amount of time spent on the sequential fraction of the program, no matter how small and regardless of the number of processing nodes used. This paper discusses some of the short comings of this law in the current age. We propose a theoretical model for predicting the behavior of a distributed algorithm given the network restrictions of the cluster used. The paper focuses on the impact of latency and bandwidth which affect the cost of interprocessor communication and the number of processing nodes used to predict the performance. The model shows good accuracy in comparison to Amdahl's law. DA - 2012-08 DB - ResearchSpace DP - CSIR KW - Multicore clusters KW - Amdahl's law KW - Algorithms KW - Propagation delay KW - Bandwith KW - Latency KW - Distributed programming LK - https://researchspace.csir.co.za PY - 2012 SM - 1819-656X T1 - An analytic model for predicting the performance of distributed applications on multicore clusters TI - An analytic model for predicting the performance of distributed applications on multicore clusters UR - http://hdl.handle.net/10204/6099 ER - en_ZA


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