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dc.creatorKappagantula, Vijay Rama Pramod
dc.date.accessioned2012-06-07T23:20:36Z
dc.date.available2012-06-07T23:20:36Z
dc.date.created2003
dc.date.issued2003
dc.identifier.urihttps://hdl.handle.net/1969.1/ETD-TAMU-2003-THESIS-K37
dc.descriptionDue to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to digital@library.tamu.edu, referencing the URI of the item.en
dc.descriptionIncludes bibliographical references (leaves 34-37).en
dc.descriptionIssued also on microfiche from Lange Micrographics.en
dc.description.abstractExisting approaches in hardware-software partitioning do not consider the maximum available system power while making the partitioning decision. Such a decision is sensitive to design efficiency when the target system is reconfigurable and supports multiple applications. Since partitioning and scheduling are interdependent, neglecting the available system power could result in an infeasible schedule. In this thesis, we present a power-aware partitioning technique for embedded systems that could support a set of applications. The applications specified at a task level of granularity are partitioned and scheduled such that timing and maximum available system power constraints are satisfied with minimum hardware logic.en
dc.format.mediumelectronicen
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherTexas A&M University
dc.rightsThis thesis was part of a retrospective digitization project authorized by the Texas A&M University Libraries in 2008. Copyright remains vested with the author(s). It is the user's responsibility to secure permission from the copyright holder(s) for re-use of the work beyond the provision of Fair Use.en
dc.subjectcomputer engineering.en
dc.subjectMajor computer engineering.en
dc.titleA power aware partitioning framework for hardware-software codesignen
dc.typeThesisen
thesis.degree.disciplinecomputer engineeringen
thesis.degree.nameM.S.en
thesis.degree.levelMastersen
dc.type.genrethesisen
dc.type.materialtexten
dc.format.digitalOriginreformatted digitalen


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