Achieving Green AI with Energy-Efficient Deep Learning Using Neuromorphic Computing.

This article details a neuromorphic computing projects program in Singapore, a collaboration between the Agency for Science, Technology and Research, A*STAR, and the National University of Singapore (NUS). The ultimate goal of the program is attainment of energy-efficient deep learning practices. To...

Descripción completa

Detalles Bibliográficos
Publicado en:	Communications of the ACM Vol. 66; no. 7; pp. 52 - 58
Autores principales:	TAO LUO, WENG-FAI WONG, SIOW MONG GOH, RICK, ANH TUAN DO, ZHIXIAN CHEN, HAIZHOU LI, WENYU JIANG, WEIYUN YAU
Formato:	Artículo
Publicado:	Association for Computing Machinery Jul2023
Materias:	Neuromorphics Deep learning Middleware Computer software Computer input-output equipment Computers National University of Singapore Singapore. Agency for Science, Technology & Research
Acceso en línea:	Ver este registro en EBSCOhost

Descripción
Sumario:	This article details a neuromorphic computing projects program in Singapore, a collaboration between the Agency for Science, Technology and Research, A*STAR, and the National University of Singapore (NUS). The ultimate goal of the program is attainment of energy-efficient deep learning practices. Topics include a description of all areas of the neuromorphic computing program with a look at the hardware, middleware, software and system integration implementation.