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An Ultra-Area-Efficient 1024-Point In-Memory FFT Processor

Sensors Lab, Advanced Membranes & Porous Materials Center (AMPMC), Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
Center for Embedded and Cyber-physical Systems, University of California, Irvine, CA 92697, USA
Authors to whom correspondence should be addressed.
Micromachines 2019, 10(8), 509;
Received: 30 June 2019 / Revised: 19 July 2019 / Accepted: 30 July 2019 / Published: 31 July 2019
Current 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 mm2 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. View Full-Text
Keywords: Fast Fourier Transform; in-memory computing; associative processor; non-von neumann architecture Fast Fourier Transform; in-memory computing; associative processor; non-von neumann architecture
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MDPI and ACS Style

Yantir, H.E.; Guo, W.; Eltawil, A.M.; Kurdahi, F.J.; Salama, K.N. An Ultra-Area-Efficient 1024-Point In-Memory FFT Processor. Micromachines 2019, 10, 509.

AMA Style

Yantir HE, Guo W, Eltawil AM, Kurdahi FJ, Salama KN. An Ultra-Area-Efficient 1024-Point In-Memory FFT Processor. Micromachines. 2019; 10(8):509.

Chicago/Turabian Style

Yantir, Hasan E., Wenzhe Guo, Ahmed M. Eltawil, Fadi J. Kurdahi, and Khaled N. Salama 2019. "An Ultra-Area-Efficient 1024-Point In-Memory FFT Processor" Micromachines 10, no. 8: 509.

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