Chalcogenide phase-change devices for neuromorphic photonic computing
The integration of artificial intelligence systems into daily applications like speech recognition and autonomous driving rapidly increases the amount of data generated and processed. However, satisfying the hardware requirements with the conventional von Neumann architecture remains challenging due...
Auteurs principaux: | Brueckerhoff-Plueckelmann, F, Feldmann, J, Wright, CD, Bhaskaran, H, Pernice, WHP |
---|---|
Format: | Journal article |
Langue: | English |
Publié: |
American Institute of Physics
2021
|
Documents similaires
-
Photonics for artificial intelligence and neuromorphic computing
par: Shastri, BJ, et autres
Publié: (2021) -
Chalcogenide optomemristors for multi-factor neuromorphic computation
par: Sarwat, SG, et autres
Publié: (2022) -
A large scale photonic matrix processor enabled by charge accumulation
par: Brueckerhoff-Plueckelmann, F, et autres
Publié: (2022) -
Behavioral modeling of integrated phase-change photonic devices for neuromorphic computing applications
par: Carrillo, S, et autres
Publié: (2019) -
Integrated 256 cell photonic phase-change memory with 512-bit capacity
par: Feldmann, J, et autres
Publié: (2019)