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dc.contributor.authorGong, Yifu
dc.description.abstractStatic Random Access Memory (SRAM) is a critical component in mobile video processing systems. Because of the large video data size, the memory is frequently accessed, which dominates the power consumption and limits battery life. In energy-efficient SRAM design, a substantial amount of research is presented to discuss the mechanisms of approximate storage, but the content and environment adaptations were never a part of the consideration in memory design. This dissertation focuses on optimization methods for the SRAM system, specifically addressing three areas of Intelligent Energy-Efficient Storage system design. First, the SRAM stability is discussed. The relationships among supply voltage, SRAM transistor sizes, and SRAM failure rate are derived in this section. The result of this study is applied to all of the later work. Second, intelligent voltage scaling techniques are detailed. This method utilizes the conventional voltage scaling technique by integrating self-correction and sizing techniques. Third, intelligent bit-truncation techniques are developed. Viewing environment and video content characteristics are considered in the memory design. The performance of all designed SRAMs are compared to published literature and are proven to have improvement.en_US
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU policy 190.6.2en_US
dc.titleIntelligent Energy-Efficient Storage System for Big-Data Applicationsen_US
dc.typeDissertationen_US
dc.typeVideoen_US
dc.date.accessioned2021-02-04T21:40:51Z
dc.date.available2021-02-04T21:40:51Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/10365/31752
dc.subjectapproximate computingen_US
dc.subjectlow poweren_US
dc.subjectSRAMen_US
dc.subjectVLSIen_US
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdfen_US
ndsu.degreeDoctor of Philosophy (PhD)en_US
ndsu.collegeEngineeringen_US
ndsu.departmentElectrical and Computer Engineeringen_US
ndsu.programElectrical and Computer Engineeringen_US
ndsu.advisorBraaten, Benjamin


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