TY - GEN
T1 - 1.1 Deep Learning Hardware
T2 - 2019 IEEE International Solid-State Circuits Conference, ISSCC 2019
AU - Lecun, Yann
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/3/6
Y1 - 2019/3/6
N2 - Historically, progress in neural networks and deep learning research has been greatly influenced by the available hardware and software tools. This paper identifies trends in deep learning research that will influence hardware architectures and software platforms of the future.
AB - Historically, progress in neural networks and deep learning research has been greatly influenced by the available hardware and software tools. This paper identifies trends in deep learning research that will influence hardware architectures and software platforms of the future.
UR - http://www.scopus.com/inward/record.url?scp=85063468498&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85063468498&partnerID=8YFLogxK
U2 - 10.1109/ISSCC.2019.8662396
DO - 10.1109/ISSCC.2019.8662396
M3 - Conference contribution
AN - SCOPUS:85063468498
T3 - Digest of Technical Papers - IEEE International Solid-State Circuits Conference
SP - 12
EP - 19
BT - 2019 IEEE International Solid-State Circuits Conference, ISSCC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 17 February 2019 through 21 February 2019
ER -