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GAIA: a general application instruction set and architecture explorer

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dc.contributor Graduate Program in Computer Engineering.
dc.contributor.advisor Yurdakul, Arda.
dc.contributor.author Soykök, Ayşe Gaye.
dc.date.accessioned 2023-03-16T09:59:46Z
dc.date.available 2023-03-16T09:59:46Z
dc.date.issued 2008.
dc.identifier.other CMPE 2008 S68
dc.identifier.uri http://digitalarchive.boun.edu.tr/handle/123456789/12110
dc.description.abstract Embedded Systems are dedicated to a task for their life time with no or slight modi cations. These systems are necessary in a wide range of industrial areas from entertainment industry to cryptography and from house appliances to army equipment. The emerging of processors with customizable instruction sets and customizable architectures has enabled the embedded processors to be tailored for the application they are dedicated to. Tailoring stands for improving incompetent parts of an application by modifying the processor. Development of design automation tools have been a new research era for embedded processors. They enable customization either by partial automation which requires human assistance at varying levels or by full automation. In this thesis, an automation tool GAIA that selects custom instructions (CI) and Single Instruction Multiple Data (SIMD) style processing elements (PEs) has been developed. The system achieves customization by examining the intermediate representation (IR) of an application. It is a fuzzy expert system that acts as a voting mechanism evaluating the attributes of the application components. The work of this thesis contributes to the stage between the front-end and back-end compilation, with the aim of assisting back-end compilation at customization process.
dc.format.extent 30cm.
dc.publisher Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2008.
dc.subject.lcsh Embedded computer systems.
dc.subject.lcsh Computer architecture.
dc.title GAIA: a general application instruction set and architecture explorer
dc.format.pages xii, 68 leaves;


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