In general, our research is focused on the development of novel ways to perform computation. Our research is highly interdisciplinary in nature, spanning across material science, physics, electrical engineering and computer science, and involves both theoretical and experimental work. This includes development of functional materials and investigating physical principles to implement novel electronic devices, exploration of novel high performance circuit architectures for general purpose and application specific tasks, and development of relevant algorithms and software tools. Our current research focus is on resistive switching ("memristive") effect in metal oxide thin-film devices and its applications in computing, specifically in the context of CMOL circuits.
Selected Recent Papers
NEW! 3D logic-in-memory computing - a pathway towards solving Feynman grand challenge:
NEW! The most accurate demo and models for spike-time-dependent plasticity of memristors:
Experimental demonstration of Hopfield neural network with memristors:
- X. Guo, F. Merrikh Bayat, L. Gao, B. D. Hoskins, F. Alibart, B. Linares-Barranco, L. Theogarajan, C. Teuscher, and D.B. Strukov, "Modeling and experimental demonstration of a Hopfield network analog-to-digital converter with hybrid CMOS/memristor circuits", Frontiers in Neuroscience 9, art. 488, Dec. 2015.
Experimental demonstration of pattern classifier with crossbar-integrated memristors:
Proposal for novel computing approach based on propagation delay of signals in electrical circuits:
- ace Logic: A hardware Acceleration for Dynamic Programming Algorithms", presented at ISCA, Twin Cities, MN, 2014
Our lab is equipped with various electrical characterization tools including cryogenic probe station, Agilent B1500 parameter analyzers, and Agilent 81180A arbitrary waveform generator. The fabrication facilities (cleanroom with state-of-the-art e-beam, photo and nanoimprinting lithographies, various deposition tools etc.) and material characterization tools (XPS, SIMS, SEM, TEM, AFM) are provided by UCSB nanofabrication center and Materials department. The experimental and theoretical work is aided with COMSOL, Matlab, Labview, Cadence software and NVidea Tesla S1070 computer.
Our research is funded by grants from NSF, AFOSR, DARPA, ARO, NIST, DENSO Corporation, and gifts from Hewlett Packard Laboratories and Hellman Family Foundation.
Last updated on March 24th, 2016