Esposito, Darjn (2017) VLSI Circuits for Approximate Computing. [Tesi di dottorato]


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Item Type: Tesi di dottorato
Lingua: English
Title: VLSI Circuits for Approximate Computing
Date: 8 April 2017
Number of Pages: 164
Institution: Università degli Studi di Napoli Federico II
Department: Ingegneria Elettrica e delle Tecnologie dell'Informazione
Dottorato: Information technology and electrical engineering
Ciclo di dottorato: 29
Coordinatore del Corso di dottorato:
Strollo, Antonio Giuseppe MariaUNSPECIFIED
Date: 8 April 2017
Number of Pages: 164
Uncontrolled Keywords: Approximate computing; VLSI; digital circuits; arithmetic; precision-scalable units
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-INF/01 - Elettronica
Date Deposited: 09 May 2017 14:48
Last Modified: 08 Mar 2018 13:28
DOI: 10.6093/UNINA/FEDOA/11627


Approximate Computing has recently emerged as a promising solution to enhance circuits performance by relaxing the requisite on exact calculations. Multimedia and Machine Learning constitute a typical example of error resilient, albeit compute-intensive, applications. In this dissertation, the design and optimization of approximate fundamental VLSI digital blocks is investigated. In chapter one the theoretical motivations of Approximate Computing, from the VLSI perspective, are discussed. In chapter two my research activity about approximate adders is reported. In this chapter approximate adders for both traditional non-error tolerant applications and error resilient applications are discussed. In chapter three precision-scalable units are investigated. Real-time precision scalability allows adapting the precision level of the unit with the precision requirements of the applications. In this context my research activities regarding approximate Multiply-and-Accumulate and memory units are described. In chapter four a precision-scalable approximate convolver for computer vision applications is discussed. This is composed of both the approximate Multiply-and-Accumulate and memory units, presented in the chapter three.


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