Characterization of Cloud-Based Applications for Different Memory Resource Sharing Scenarios

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dc.contributor.advisorDuan, Lide
dc.contributor.authorBernal Montana, Ana Maria
dc.contributor.committeeMemberJohn, Eugene
dc.contributor.committeeMemberLee, Wonjun
dc.date.accessioned2024-02-09T19:29:30Z
dc.date.available2024-02-09T19:29:30Z
dc.date.issued2017
dc.descriptionThis item is available only to currently enrolled UTSA students, faculty or staff. To download, navigate to Log In in the top right-hand corner of this screen, then select Log in with my UTSA ID.
dc.description.abstractA typical Cloud-Based application is scale-out, latency sensitive, and usually involves processing of enormous amounts of data. Web Searches, Streaming services, online transactions, etc., run on massive Warehouse-Scale Computers that are powered by processors designed to run traditional scale-up personal computer applications. Since Architectural decisions for the processors that run the Internet today were made with a desktop computer in mind, memory resources are often overprovisioned and underutilized. In this work, five different Cloud-Based applications from the CloudSuite benchmark suite are characterized according to their interaction with memory resources and their level of data sharing. Threads of each workload are distributed among nodes to study how different scenarios of Last Level Cache and Memory Controller Channel sharing can affect performance. Furthermore, the impact of co-running applications is also taken into consideration, and a scheduling algorithm intended to run on top of the Operating System scheduler is proposed.
dc.description.departmentElectrical and Computer Engineering
dc.format.extent56 pages
dc.format.mimetypeapplication/pdf
dc.identifier.isbn9781369776119
dc.identifier.urihttps://hdl.handle.net/20.500.12588/2965
dc.languageen
dc.subjectCloud Benchmarks
dc.subjectComputer Architecture
dc.subjectComputer Engineering
dc.subjectMemory Resources
dc.subjectServer Processors
dc.subject.classificationComputer engineering
dc.subject.classificationElectrical engineering
dc.subject.classificationEngineering
dc.titleCharacterization of Cloud-Based Applications for Different Memory Resource Sharing Scenarios
dc.typeThesis
dc.type.dcmiText
dcterms.accessRightspq_closed
thesis.degree.departmentElectrical and Computer Engineering
thesis.degree.grantorUniversity of Texas at San Antonio
thesis.degree.levelMasters
thesis.degree.nameMaster of Science

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