Vector Symbolic Architectures as a Computing Framework for Emerging Hardware

This article reviews recent progress in the development of the computing framework Vector Symbolic Architectures (also known as Hyperdimensional Computing). This framework is well suited for implementation in stochastic, emerging hardware and it naturally expresses the types of cognitive operations...

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Veröffentlicht in:Proceedings of the IEEE. Institute of Electrical and Electronics Engineers. - 1998. - 110(2022), 10 vom: 11. Okt., Seite 1538-1571
1. Verfasser: Kleyko, Denis (VerfasserIn)
Weitere Verfasser: Davies, Mike, Frady, E Paxon, Kanerva, Pentti, Kent, Spencer J, Olshausen, Bruno A, Osipov, Evgeny, Rabaey, Jan M, Rachkovskij, Dmitri A, Rahimi, Abbas, Sommer, Friedrich T
Format: Aufsatz
Sprache:English
Veröffentlicht: 2022
Zugriff auf das übergeordnete Werk:Proceedings of the IEEE. Institute of Electrical and Electronics Engineers
Schlagworte:Journal Article Turing completeness computing framework computing in superposition data structures distributed representations emerging hardware hyperdimensional computing vector symbolic architectures
Beschreibung
Zusammenfassung:This article reviews recent progress in the development of the computing framework Vector Symbolic Architectures (also known as Hyperdimensional Computing). This framework is well suited for implementation in stochastic, emerging hardware and it naturally expresses the types of cognitive operations required for Artificial Intelligence (AI). We demonstrate in this article that the field-like algebraic structure of Vector Symbolic Architectures offers simple but powerful operations on high-dimensional vectors that can support all data structures and manipulations relevant to modern computing. In addition, we illustrate the distinguishing feature of Vector Symbolic Architectures, "computing in superposition," which sets it apart from conventional computing. It also opens the door to efficient solutions to the difficult combinatorial search problems inherent in AI applications. We sketch ways of demonstrating that Vector Symbolic Architectures are computationally universal. We see them acting as a framework for computing with distributed representations that can play a role of an abstraction layer for emerging computing hardware. This article serves as a reference for computer architects by illustrating the philosophy behind Vector Symbolic Architectures, techniques of distributed computing with them, and their relevance to emerging computing hardware, such as neuromorphic computing
Beschreibung:Date Revised 27.09.2024
published: Print-Electronic
Citation Status PubMed-not-MEDLINE
ISSN:0018-9219