publication . Article . Preprint . 2020

In-memory hyperdimensional computing

Geethan Karunaratne; Manuel Le Gallo; Giovanni Cherubini; Luca Benini; Abbas Rahimi; Abu Sebastian;
Open Access
  • Published: 01 Jun 2020 Journal: Nature Electronics, volume 3, pages 327-337 (eissn: 2520-1131, Copyright policy)
  • Publisher: Springer Science and Business Media LLC
  • Country: Switzerland
Hyperdimensional computing is an emerging computational framework that takes inspiration from attributes of neuronal circuits including hyperdimensionality, fully distributed holographic representation and (pseudo)randomness. When employed for machine learning tasks, such as learning and classification, the framework involves manipulation and comparison of large patterns within memory. A key attribute of hyperdimensional computing is its robustness to the imperfections associated with the computational substrates on which it is implemented. It is therefore particularly amenable to emerging non-von Neumann approaches such as in-memory computing, where the physica...
Persistent Identifiers
free text keywords: Electrical and Electronic Engineering, Instrumentation, Electronic, Optical and Magnetic Materials, Computer Science - Emerging Technologies, Computer Science - Artificial Intelligence, Physics - Applied Physics, Electronic circuit, Machine learning, computer.software_genre, computer, Robustness (computer science), Computation, CMOS, Computer science, Artificial intelligence, business.industry, business, Crossbar switch, Gesture recognition, Hyperdimensional computing, Randomness
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Funded by
Computation-in-memory architecture based on resistive devices
  • Funder: European Commission (EC)
  • Project Code: 780215
  • Funding stream: H2020 | RIA
PROJECTED MEMRISTOR: A nanoscale device for cognitive computing
  • Funder: European Commission (EC)
  • Project Code: 682675
  • Funding stream: H2020 | ERC | ERC-COG
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