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Smart Material Implication Using Spin-Transfer Torque Magnetic Tunnel Junctions for Logic-in-Memory Computing

  • Published:2022-08 Issue: Volume:194 Page:108390
  • ISSN:0038-1101
  • Container-title:Solid-State Electronics
  • language:en
  • Short-container-title:Solid-State Electronics

Author:

De Rose Raffaele,Zanotti Tommaso,Puglisi Francesco Maria,Crupi Felice,Pavan Paolo,Lanuzza Marco

Funder

Ministero dell’Istruzione, dell’Università e della Ricerca

Publisher

Elsevier BV

Subject

Materials Chemistry,Electrical and Electronic Engineering,Condensed Matter Physics,Electronic, Optical and Magnetic Materials

Reference28 articles.

1. IRDS-IEEE. International Roadmap for Devices and Systems 2020. Available: https://irds.ieee.org/.

2. Cost-effective low-power processor-in-memory-based reconfigurable datapath for multimedia applications;Lanuzza,2005

3. ‘Memristive’ switches enable ‘stateful’ logic operations via material implication;Borghetti;Nature,2010

4. Kvatinsky S, Satat G, Wald N, Friedman E G, Kolodny A, Weiser U C. Memristor-Based Material Implication (IMPLY) Logic: Design Principles and Methodologies. IEEE Transactions on Very Large Scale Integration (VLSI) Systems 2014; 22(10):2054–2066. DOI: 10.1109/TVLSI.2013.2282132.

5. A Logic Circuit Design for Perfecting Memristor-Based Material Implication;Chen;IEEE Trans Comput Aided Des Integr Circuits Syst,2017

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