Room 236C WEB
Dr. Hai (Helen) Li/Associate Professor, University of Pittsburgh
As big data processing becomes pervasive and ubiquitous in our lives, the desire for embedded-everywhere and human-centric information systems calls for an “intelligent” computing paradigm that is capable of handling large volume of data through massively parallel operations under limited hardware and power resources. This demand, however, is unlikely to be satisfied through the traditional computer systems whose performance is greatly hindered by the increasing performance gap between CPU and memory as well as the fast-growing power consumption. Inspired by the working mechanism of human brains, a neuromorphic system naturally possesses a massively parallel architecture with closely coupled memory, offering a great opportunity to break the “memory wall” in von Neumann architecture. In this talk, I will give an overview of our research on emerging nonvolatile memory (eNVM) technologies that feature many attractive characteristics such as non-volatility, high cell density, nanosecond access time and low operation voltage. The talk starts with the expectations of modern computing systems on memory hierarchy, followed by two examples in eNVM design and applications in conventional and neuromorphic computing systems, respectively. Our prospects on the research of eNVM technologies will be also given at the end of this talk, offering the audiences an alternative thinking about the future evolution and revolution of modern computing systems.
Bio: Hai (Helen) Li received B.S and M.S. from Tsinghua University (both with early graduation) and Ph.D. from Purdue University. She currently is an Associate Professor in the Electrical and Computer Engineering Department at the University of Pittsburgh. Earlier in her career, she was with Qualcomm, Inc., Intel Corporation, Seagate Technology, and the Polytechnic Institute of New York University. Her research interests include memory design and architecture, brain-inspired computing and neuromorphic systems, and device/circuit/architecture co-optimization for low power and high performance. She has published 1 book, a few book chapters, and about 140 research papers in journals and refereed conference proceedings. Dr. Li is the associate editors of IEEE TVLSI, ACM TODAES, IEEE TMSCS, and served on the technical and organization committees of more than 20 conferences. She received five best paper awards from ISQED’08, ISLPED’10, GLSVLS’13, ISVLSI’14, ASPDAC’15 and several other nominations in ICCAD, DATE, etc. Dr. Li is recipient of the NSF CAREER award in 2012 and DARPA Young Faculty Award (YFA) in 2013.
Host: Dr. Hu