Design of Efficient AI Accelerator Building Blocks in Quantum-Dot Cellular Automata (QCA)-Reference-Cited by-同舟云学术

Design of Efficient AI Accelerator Building Blocks in Quantum-Dot Cellular Automata (QCA)

Published:2022-09 Issue:3 Volume:12 Page:703-712
ISSN:2156-3357
Container-title:IEEE Journal on Emerging and Selected Topics in Circuits and Systems
language:
Short-container-title:IEEE J. Emerg. Sel. Topics Circuits Syst.

Author:

Mamdouh Ahmed¹^ORCID,Mjema Mbonea¹,Yemiscioglu Gurtac²^ORCID,Kondo Satoshi³^ORCID,Muhtaroglu Ali²^ORCID

Affiliation:

1. Department of Electrical and Electronics Engineering, Northern Cyprus Campus, Middle East Technical University, Kalkanlı, Güzelyurt, Turkey

2. Department of Electrical and Electronics Engineering and the Center for Sustainability, Northern Cyprus Campus, Middle East Technical University, Kalkanlı, Güzelyurt, Turkey

3. Mathematics Research and Teaching Group, Middle East Technical University, Northern Cyprus Campus, Kalkanlı, Güzelyurt, Turkey

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/5503868/9915329/09868024.pdf?arnumber=9868024

Reference48 articles.

1. QCADesigner: A Rapid Design and Simulation Tool for Quantum-Dot Cellular Automata

2. A QCA Implementation of a Configurable Logic Block for an FPGA

3. Analysis and modeling of sequential circuits in QCA nano computing: RAM and SISO register study

4. An Ultra-Low Cost Multilayer RAM in Quantum-Dot Cellular Automata

5. On the use of approximate adders in carry-save multiplier-accumulators

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