A model-driven approach for predicting and analysing the execution efficiency of multi-core processing

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dc.contributor.authorHasan, Khondker
dc.date.accessioned2020-06-11T18:28:48Z
dc.date.available2020-06-11T18:28:48Z
dc.date.issued2017-03
dc.description.abstractTechniques for predicting the efficiency of multi-core processing associated with a set of tasks with varied CPU and main memory requirements are introduced. Prediction of CPU and memory availability is important in the context of making process assignment, load balancing, and scheduling decisions in distributed systems. Given a set of tasks each with varied CPU and main memory requirements, and a multi-core system (which generally has fewer cores than the number of tasks), we provide upper- and lower-bound models (formulas) for the efficiency with which the tasks are executed. In addition, a model for average CPU availability is introduced from the empirical study for applications that require a single predicted value instead of bounds. To facilitate scientific and controlled empirical evaluation, real-world benchmark programs with dynamic behaviour (CPU and memory requirements change in a short interval of time) are employed on UNIX systems that are parameterised by their CPU usage factor and memory requirement.en_US
dc.identifier.citationKhondker S. Hasan, John K. Antonio, Sridhar Radhakrishnan, "A model-driven approach for predicting and analysing the execution efficiency of multi-core processing”, International Journal of Computational Science and Engineering (IJCSE), INDERSCIENCE Publishers, Vol: 14, No 2, Page 105 – 125, Olney, Bucks, UK, March 2017.en_US
dc.identifier.urihttps://hdl.handle.net/10657.1/2366
dc.language.isoen_USen_US
dc.publisherInternational Journal of Computational Science and Engineeringen_US
dc.subjectcomposite prediction model; CPU availability; concurrent threads; memory model; modelling; multi-core processing; performance evaluation; execution efficiency; process assignment; load balancing; scheduling; distributed systems; CPU usage; memory requirement.en_US
dc.titleA model-driven approach for predicting and analysing the execution efficiency of multi-core processingen_US
dc.typeArticleen_US

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