A New Multi-core CPU Resource Availability Prediction Model for Concurrent Processes

dc.contributor.authorHasan, Khondker S.
dc.contributor.authorAntonio, John K.
dc.contributor.authorRadhakrishnan, Sridhar
dc.date.accessioned2021-04-19T19:26:43Z
dc.date.available2021-04-19T19:26:43Z
dc.date.issued2017-03
dc.description.abstractThe efficiency of a multi-core architecture is directly related to the mechanisms that map the threads (processes in execution) to the cores. Determining the CPU resource availability of a multi-core architecture based on the characteristics of the threads that are in execution is the art of system performance prediction. Prediction of CPU resource availability is important in the context of making process assignment, load balancing, and scheduling decisions. In distributed infrastructure, CPU resources are allocated on demand for a chosen set of compute nodes. In this paper, a prediction model is derived for multi-core architectures and empirical evaluations are performed with real-world benchmark programs in a heterogeneous environment to demonstrate the accuracy of the proposed model. This model can be utilized in various time-sensitive applications like resource allocation in a cloud environment, task distribution (determining the order for faster processing time) in distributed systems, and others.en_US
dc.description.peerreviewYesen_US
dc.identifier.citationKhondker S. Hasan, John K. Antonio, Sridhar Radhakrishnan, "A New Multi-core CPU Resource Availability Prediction Model for Concurrent Processes”, The 2017 IAENG International Conference on Computer Science (ICCS-17), Organized under: International MultiConference of Engineers and Computer Scientists (IMECS-17), Hong Kong, 15-17 March 2017.en_US
dc.identifier.urihttps://hdl.handle.net/11244/329209
dc.languageen_USen_US
dc.subjectCPU Availabilityen_US
dc.subjectExecution Efficiencyen_US
dc.subjectHyper-threadingen_US
dc.subjectMulti-core Prediction Modelen_US
dc.subjectPrediction Algorithmen_US
dc.titleA New Multi-core CPU Resource Availability Prediction Model for Concurrent Processesen_US
dc.typeArticleen_US
ou.groupGallogly College of Engineering::School of Computer Scienceen_US

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