Presenter

Dr. Catherine Graves is a research scientist at Hewlett Packard Labs developing next generation analog and neuromorphic computational accelerators utilizing memristor devices. Such specialized hardware accelerators can help meet the challenge of limited energy efficiency in existing general-purpose digital approaches and the tremendous recent increase of data centric computations. Dr. Graves’s work focuses on measuring and developing models of static and dynamical conduction behaviors in metal oxide memristor devices and implementing these devices in prototype systems for different computing applications. In particular, Dr. Graves is interested in how nanoscale analog and dynamical electronic devices such as the memristor can accelerate core bottleneck computations, such as a recent project to accelerate matrix multiplication with a dot product engine. This dot product engine (DPE) utilizes multilevel analog memristor devices to natively perform vector-matrix multiplications within a device crossbar array through Ohm’s law and Kirchoff’s law. This hardware approach to matrix multiplication has the potential to accelerate a core computation of wide-ranging applications from artificial neural networks to signal processing.

Dr. Graves received her Ph.D. in Applied Physics from Stanford University studying ultrafast magnetization reversal in ferrimagnetic materials for future computer memory applications while a NSF Graduate Research Fellow. Her work utilized time-resolved x-ray diffraction techniques at SLAC National Acceleratory Laboratory to observe nanoscale magnetization reversal at speeds faster than a picosecond and contributed to the development of key experimental techniques for the x-ray free electron laser (LCLS) at SLAC.