Esposito, Darjn (2017) VLSI Circuits for Approximate Computing. [Tesi di dottorato]
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| Tipologia del documento: | Tesi di dottorato |
|---|---|
| Lingua: | English |
| Titolo: | VLSI Circuits for Approximate Computing |
| Autori: | Autore Email Esposito, Darjn darjesp@gmail.com |
| Data: | 8 Aprile 2017 |
| Numero di pagine: | 164 |
| Istituzione: | Università degli Studi di Napoli Federico II |
| Dipartimento: | Ingegneria Elettrica e delle Tecnologie dell'Informazione |
| Dottorato: | Information technology and electrical engineering |
| Ciclo di dottorato: | 29 |
| Coordinatore del Corso di dottorato: | nome email Riccio, Daniele daniele.riccio@unina.it |
| Tutor: | nome email Strollo, Antonio Giuseppe Maria [non definito] |
| Data: | 8 Aprile 2017 |
| Numero di pagine: | 164 |
| Parole chiave: | 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 |
| Depositato il: | 09 Mag 2017 14:48 |
| Ultima modifica: | 08 Mar 2018 13:28 |
| URI: | http://www.fedoa.unina.it/id/eprint/11627 |
| DOI: | 10.6093/UNINA/FEDOA/11627 |
Abstract
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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