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INTEGRATED INPUT MODELING AND MEMORY MANAGEMENT FOR IMAGE PROCESSING APPLICATIONS

dc.contributor.advisorBhattacharyya, Shuvra Sen_US
dc.contributor.authorHaim, Fiorellaen_US
dc.date.accessioned2006-02-04T07:48:37Z
dc.date.available2006-02-04T07:48:37Z
dc.date.issued2005-12-07en_US
dc.identifier.urihttp://hdl.handle.net/1903/3235
dc.description.abstractImage processing applications often demand powerful calculations and real-time performance with low power and energy consumption. Programmable hardware provides inherent parallelism and flexibility making it a good implementation choice for this application domain. In this work we introduce a new modeling technique combining Cyclo-Static Dataflow (CSDF) base model semantics and Homogeneous Parameterized Dataflow (HPDF) meta-modeling framework, which exposes more levels of parallelism than previous models and can be used to reduce buffer sizes. We model two different applications and show how we can achieve efficient scheduling and memory organization, which is crucial for this application domain, since large amounts of data are processed, and storing intermediate results usually requires the use of off-chip resources, causing slower data access and higher power consumption. We also designed a reusable wishbone compliant memory controller module that can be used to access the Xilinx Multimedia Board's memory chips using single accesses or burst mode.en_US
dc.format.extent1268863 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.titleINTEGRATED INPUT MODELING AND MEMORY MANAGEMENT FOR IMAGE PROCESSING APPLICATIONSen_US
dc.typeThesisen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentElectrical Engineeringen_US
dc.subject.pqcontrolledEngineering, Electronics and Electricalen_US
dc.subject.pquncontrolleddataflowen_US
dc.subject.pquncontrolledimage processingen_US
dc.subject.pquncontrolledFPGAen_US
dc.subject.pquncontrolledmodelingen_US


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