In this theme, the team will design, simulate, and benchmark PSL Cores consisting of high kBT p-transistor weights and low kBT p-transistor probabilistic input/output units. Additionally, the maximum and optimal PSL Core sizes for implementing interconnected networks of PSL Cores to realize Deep Belief Networks of hierarchically organized RBMs for deep learning applications will be researched. P-transistor models will be used for the initial designs and we will develop a self-contained SPICE model with predictive transistor models (e.g. 10nm or 7nm) incorporating necessary LLG equations for processional motion of a time-varying magnetization vector.
Current2 Research Tasks2 Universities5 Students2 Faculty Researchers6 Liaison Personnel
This Year26 Research Publications
Last Year2 Task Starts20 Research Publications
Since Inception2 Research Tasks3 Universities6 Students3 Faculty Researchers6 Liaison Personnel46 Research Publications