Tutor: FIORINI CARLO ETTORE Major Research topic
:Simulation of memristive devices and circuits for logic and neuromorphic computing
Advisor: IELMINI DANIELEAbstract:
In last decade, CMOS scaling according to Moore’s law has started facing serious limitations due to excessive device area and off-state power consumption. In addition, the performance bottleneck of conventional processors based on Von Neumann architecture has encouraged many researchers to explore novel concepts and architectures mainly for very complex applications such as pattern classification and sensory processing. Neuromorphic brain inspired computing systems represent an interesting solution to overcome the limitations of conventional architectures by exploiting memristive devices such as phase change and resistive switching memories. The research aims at modelling and simulating spiking neural networks based on memristors as synapses to implement machine learning tasks such as pattern recognition and to solve difficult constraint satisfaction problems.