Always-On Sub-Microwatt Spiking Neural Network Based on Spike-Driven Clock- and Power-Gating for an Ultra-Low-Power Intelligent Device.

Chundi, Pavan Kumar; Wang, Dewei; Kim, Sung Justin; Yang, Minhao; Cerqueira, Joao Pedro; Kang, Joonsung; Jung, Seungchul; Kim, Sangjoon; Seok, Mingoo

Chundi, Pavan Kumar; Wang, Dewei; Kim, Sung Justin; Yang, Minhao; Cerqueira, Joao Pedro; Kang, Joonsung; Jung, Seungchul; Kim, Sangjoon; Seok, Mingoo.

Afiliação

Chundi PK; Department of Electrical Engineering, Columbia University, New York City, NY, United States.
Wang D; Department of Electrical Engineering, Columbia University, New York City, NY, United States.
Kim SJ; Department of Electrical Engineering, Columbia University, New York City, NY, United States.
Yang M; Department of Electrical Engineering, Columbia University, New York City, NY, United States.
Cerqueira JP; Department of Electrical Engineering, Columbia University, New York City, NY, United States.
Kang J; Samsung Electronics, Seoul, South Korea.
Jung S; Samsung Electronics, Seoul, South Korea.
Kim S; Samsung Electronics, Seoul, South Korea.
Seok M; Department of Electrical Engineering, Columbia University, New York City, NY, United States.

Front Neurosci ; 15: 684113, 2021.

Article em En | MEDLINE | ID: mdl-34354559

Palavras-chave

always-on device; clock and power gating; event-driven architecture; neuromorphic hardware; spiking neural network

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Neurosci Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

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