Dynamic Analyses of Result Quality in Energy-Aware Approximate Programs

dc.contributor.advisorGrossman, Daniel Jen_US
dc.contributor.authorRIngenburg, Michaelen_US
dc.date.accessioned2014-04-30T16:18:47Z
dc.date.available2014-04-30T16:18:47Z
dc.date.issued2014-04-30
dc.date.submitted2014en_US
dc.descriptionThesis (Ph.D.)--University of Washington, 2014en_US
dc.description.abstractEnergy efficiency is a key concern in the design of modern computer systems. One promising approach to energy-efficient computation, <italic>approximate computing</italic>, trades off output precision for energy efficiency. However, this tradeoff can have unexpected effects on computation quality. This thesis presents dynamic analysis tools to study, debug, and monitor the quality and energy efficiency of approximate computations. We propose three styles of tools: prototyping tools that allow developers to experiment with approximation in their applications, offline tools that instrument code to determine the key sources of error, and online tools that monitor the quality of deployed applications in real time. Our prototyping tool is based on an extension to the functional language OCaml. We add approximation constructs to the language, an approximation simulator to the runtime, and profiling and auto-tuning tools for studying and experimenting with energy-quality tradeoffs. We also present two offline debugging tools and three online monitoring tools. The first offline tool identifies correlations between output quality and the total number of executions of, and errors in, individual approximate operations. The second tracks the number of approximate operations that flow into a particular value. Our online tools comprise three low-cost approaches to dynamic quality monitoring. They are designed to monitor quality in deployed applications without spending more energy than is saved by approximation. Online monitors can be used to perform real time adjustments to energy usage in order to meet specific quality goals. We present prototype implementations of all of these tools and describe their usage with several applications. Our prototyping, profiling, and autotuning tools allow us to experiment with approximation strategies and identify new strategies, our offline tools succeed in providing new insights into the effects of approximation on output quality, and our monitors succeed in controlling output quality while still maintaining significant energy efficiency gains.en_US
dc.embargo.termsNo embargoen_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.otherRIngenburg_washington_0250E_12771.pdfen_US
dc.identifier.urihttp://hdl.handle.net/1773/25356
dc.language.isoen_USen_US
dc.rightsCopyright is held by the individual authors.en_US
dc.subjectApproximate Computing; Energy efficiency; Quality of Resulten_US
dc.subject.otherComputer scienceen_US
dc.subject.othercomputer science and engineeringen_US
dc.titleDynamic Analyses of Result Quality in Energy-Aware Approximate Programsen_US
dc.typeThesisen_US

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