ECE Seminar - Material-to-system co-optimization for computation-in-memory architecture
Conventional von Neumann based computing architecture is facing great challenges due to the memory-wall bottleneck. The computation-in-memory (CIM) technology based on emerging memristor device can reduce data moving, and thus significantly improve the computing density and energy efficiency. In this talk, I will first introduce the principles of CIM technology. Then I will talk about the recent progress of CIM development from material level to device level, circuit level, system level, and software level, as well as some cross-layer co-design methodology. I will also show our hardware demonstrations on CIM chips and systems for the AI acceleration.
Bin Gao is currently an Associate Professor with the School of Integrated Circuits, Tsinghua University, Beijing, China. He received the B.S. degree in 2008 and Ph.D. degree in 2013, both from Peking University, Beijing, China. His current research interests include fabrication, characterization, and modeling of emerging semiconductor devices, and design of computation-in-memory chips. He has published more than 100 technical papers on Nature, Nature Electronics, Proceedings of the IEEE, EDL, TED, JSSC, IEDM, ISSCC, VLSI, etc. His total citation is over 13000. He was a recipient of the IEEE EDS Ph.D. Student Fellowship in 2012. He served as Sub-committee Chair of IEDM, IRPS, EDTM, and ICTA, and TPC member of DAC, IPFA, etc.