Date and Time:
Location: Seminar room OMZ (U013, INF 350, floor -1)
Title: Reconfigurable and Programmable Physical Computing
Abstract: Digital computation is enabled by a framework developed over the last 80 years. Having an analog framework enables wider capability while giving the designer tools to make reasonable choices. In the past, discussions on the capability of analog or physical computing were only of theoretical interest. Analog computation becomes relevant with the advent of large-scale Field Programmable Analog Arrays (FPAA) devices, particularly the SoC FPAA devices and resulting design tools. We will discuss FPAAs developed at GT as well as well as recent advances approaches are fueled by recent advances in programmable and configurable large-scale analog circuits and systems enabling a typical factor of 1000 improvement in computational power (Energy) efficiency over their digital counterparts. Analog and digital systems have tools to model resolution and computational noise and computation energy; analog and digital approaches have their own optimal computing regions. We will overview a few examples in this area as helps the resulting roadmap discussion, including speech, vision, and sensor interfaces.
CV: Jennifer Hasler received her B.S.E. and M.S. degrees in electrical engineering from Arizona State University in August 1991. She received her Ph.D. in computation and neural systems from California Institute of Technology in February 1997. Hasler is a professor at the Georgia Institute of Technology in the School of Electrical and Computer Engineering; Atlanta is the coldest climate in which Hasler has lived. Hasler founded the Integrated Computational Electronics (ICE) laboratory at Georgia Tech, a laboratory affiliated with the Laboratories for Neural Engineering. Hasler is a member of Tau Beta P, Eta Kappa Nu, and the IEEE.