no code implementations • 17 Aug 2021 • Weier Wan, Rajkumar Kubendran, Clemens Schaefer, S. Burc Eryilmaz, Wenqiang Zhang, Dabin Wu, Stephen Deiss, Priyanka Raina, He Qian, Bin Gao, Siddharth Joshi, Huaqiang Wu, H. -S. Philip Wong, Gert Cauwenberghs
Realizing today's cloud-level artificial intelligence functionalities directly on devices distributed at the edge of the internet calls for edge hardware capable of processing multiple modalities of sensory data (e. g. video, audio) at unprecedented energy-efficiency.
no code implementations • 27 Sep 2016 • S. Burc Eryilmaz, Emre Neftci, Siddharth Joshi, Sang-Bum Kim, Matthew BrightSky, Hsiang-Lan Lung, Chung Lam, Gert Cauwenberghs, H. -S. Philip Wong
Current large scale implementations of deep learning and data mining require thousands of processors, massive amounts of off-chip memory, and consume gigajoules of energy.
no code implementations • 29 May 2014 • S. Burc Eryilmaz, Duygu Kuzum, Rakesh G. D. Jeyasingh, Sang-Bum Kim, Matthew BrightSky, Chung Lam, H. -S. Philip Wong
We demonstrate, in hardware, that 2-D crossbar arrays of phase change synaptic devices can achieve associative learning and perform pattern recognition.