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Nature communications, 2022-09, Vol.13 (1), p.5762-8, Article 5762
2022
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Autor(en) / Beteiligte
Titel
Probabilistic computing using Cu0.1Te0.9/HfO2/Pt diffusive memristors
Ist Teil von
  • Nature communications, 2022-09, Vol.13 (1), p.5762-8, Article 5762
Ort / Verlag
London: Nature Publishing Group UK
Erscheinungsjahr
2022
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • A computing scheme that can solve complex tasks is necessary as the big data field proliferates. Probabilistic computing (p-computing) paves the way to efficiently handle problems based on stochastic units called probabilistic bits (p-bits). This study proposes p-computing based on the threshold switching (TS) behavior of a Cu 0.1 Te 0.9 /HfO 2 /Pt (CTHP) diffusive memristor. The theoretical background of the p-computing resembling the Hopfield network structure is introduced to explain the p-computing system. P-bits are realized by the stochastic TS behavior of CTHP diffusive memristors, and they are connected to form the p-computing network. The memristor-based p-bit is likely to be ‘0’ and ‘1’, of which probability is controlled by an input voltage. The memristor-based p-computing enables all 16 Boolean logic operations in both forward and inverted operations, showing the possibility of expanding its uses for complex operations, such as full adder and factorization. Designing a computing scheme to solve complex tasks as the big data field proliferates remains a challenge. Here, the authors present a probabilistic bit generation hardware built using the random nature of Cu x Te 1− x /HfO 2 /Pt memristors capable of performing logic gates with invertible mode, showing the expandability to complex logic circuits.
Sprache
Englisch
Identifikatoren
ISSN: 2041-1723
eISSN: 2041-1723
DOI: 10.1038/s41467-022-33455-x
Titel-ID: cdi_doaj_primary_oai_doaj_org_article_950d36ecf3184345965e48b0a0c49bdd

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