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dc.contributor.authorYantir, Hasan Erdem
dc.contributor.authorGuo, Wenzhe
dc.contributor.authorEltawil, Ahmed M
dc.contributor.authorKurdahi, Fadi J
dc.contributor.authorSalama, Khaled N.
dc.date.accessioned2019-08-08T12:59:00Z
dc.date.available2019-08-08T12:59:00Z
dc.date.issued2019-08-03
dc.identifier.citationYantır, H. E., Guo, W., Eltawil, A. M., Kurdahi, F. J., & Salama, K. N. (2019). An Ultra-Area-Efficient 1024-Point In-Memory FFT Processor. Micromachines, 10(8), 509. doi:10.3390/mi10080509
dc.identifier.doi10.3390/mi10080509
dc.identifier.urihttp://hdl.handle.net/10754/656441
dc.description.abstractCurrent computation architectures rely on more processor-centric design principles. On the other hand, the inevitable increase in the amount of data that applications need forces researchers to design novel processor architectures that are more data-centric. By following this principle, this study proposes an area-efficient Fast Fourier Transform (FFT) processor through in-memory computing. The proposed architecture occupies the smallest footprint of around 0.1 mm 2 inside its class together with acceptable power efficiency. According to the results, the processor exhibits the highest area efficiency ( FFT / s / area ) among the existing FFT processors in the current literature.
dc.publisherMDPI AG
dc.relation.urlhttps://www.mdpi.com/2072-666X/10/8/509
dc.rightsby the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
dc.rights.urihttp://creativecommons.org/licenses/by/4.0
dc.subjectfast Fourier transform
dc.subjectin-memory computing
dc.subjectassociative processor
dc.subjectnon-von neumann architecture
dc.titleAn Ultra-Area-Efficient 1024-Point In-Memory FFT Processor.
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.identifier.journalMicromachines
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionCenter for Embedded and Cyber-physical Systems, University of California, Irvine, CA 92697, USA.
kaust.personYantir, Hasan Erdem
kaust.personGuo, Wenzhe
kaust.personSalama, Khaled N.
refterms.dateFOA2019-08-08T13:00:46Z


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by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).