KernTune: self-tuning Linux kernel performance using support vector machines

dc.contributor.advisorConnan, James
dc.contributor.authorYi, Long
dc.contributor.otherDept. of Computer Science
dc.contributor.otherFaculty of Science
dc.date.accessioned2013-10-11T08:47:08Z
dc.date.accessioned2024-10-30T14:00:45Z
dc.date.available2009/08/03 08:21
dc.date.available2009/08/03
dc.date.available2013-10-11T08:47:08Z
dc.date.available2024-10-30T14:00:45Z
dc.date.issued2006
dc.descriptionMagister Scientiae - MScen_US
dc.description.abstractSelf-tuning has been an elusive goal for operating systems and is becoming a pressing issue for modern operating systems. Well-trained system administrators are able to tune an operating system to achieve better system performance for a specific system class. Unfortunately, the system class can change when the running applications change. The model for self-tuning operating system is based on a monitor-classify-adjust loop. The idea of this loop is to continuously monitor certain performance metrics, and whenever these change, the system determines the new system class and dynamically adjusts tuning parameters for this new class. This thesis described KernTune, a prototype tool that identifies the system class and improves system performance automatically. A key aspect of KernTune is the notion of Artificial Intelligence oriented performance tuning. Its uses a support vector machine to identify the system class, and tunes the operating system for that specific system class. This thesis presented design and implementation details for KernTune. It showed how KernTune identifies a system class and tunes the operating system for improved performance.en_US
dc.description.countrySouth Africa
dc.identifier.urihttps://hdl.handle.net/10566/16945
dc.language.isoenen_US
dc.publisherUniversity of the Western Capeen_US
dc.rights.holderUniversity of the Western Capeen_US
dc.subjectLinuxen_US
dc.subjectOperating systems (Computers)en_US
dc.subjectHigh performance computingen_US
dc.subjectSystem analysisen_US
dc.subjectData processingen_US
dc.titleKernTune: self-tuning Linux kernel performance using support vector machinesen_US
dc.typeThesisen_US

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