Neuromorphic Computing Special Session
NUO XU; Samsung (Session Organizer)
Philip H.-S. Wong, Stanford University
Shimeng Yu, Arizona State University
Giacomo Indiveri,ETH Zurich
John Arthur, IBM Research, Almaden
As Dennard scaling is almost approaching its limits, a new computing paradigm involving system, circuit and technology co-innovation is on demand. The “Brain-like” computation, a.k.a. the neuromorphic computing has been considered as the most promising candidate as a replacement or supplement to existing Van Neumann computers. Both emerging semiconductor devices and circuit/system designs have been studied extensively and many progress has been achieved in recent years.
This special session invites four leading researchers in this field yet with different paths to implement a “Silicon” neural network. Prof. Wong and Prof. Yu will introduce their work on emerging device-based spiking neural network, such as Resistive RAM (RRAM) and Phase Change Memory (PCM) based synapses. These are also promising for 3-D integration schemes. Prof. Indiveri, on the other hand, will talk about the analog/mixed-signal circuit designs to implement neurons for different computational models. Dr. Arthur will provide a review of the IBM’s TrueNorth development work to demonstrate the feasibility of neuromorphic computing at product level.