1215
(Invited) Unconventional Computing with Memristors

Wednesday, 4 October 2017: 14:00
Camellia 4 (Gaylord National Resort and Convention Center)
D. Strukov (UC Santa Barbara)
By now, there have been many demonstrations of resistive switching (“memristive”) devices based on organic, chalcogenide, transition metal-oxide and silicon materials and involving different physical switching mechanisms, such as phase-change transitions and modulation of the ionic concentration profiles by electrical and/or thermal forces. The conductance of some properly engineered memristors can be continuously tuned with relatively large electrical bias, and retained, effectively indefinitely, when small stress is applied. Such analog nonvolatile memory functionality combined with potentially very high device density, achieved by lateral scaling and/or monolithical vertical integration, enable many new exciting applications of memristors in neuromorphic and other types of computing.

In my talk, I will review several such applications based on metal-oxide memristors which were a recent focus of my group. I will start with stateful material implication logic, which was originally suggested by HPL group. In our work, we showed that 3D version of this logic allows resolving Feynman grand challenge of implementing 8-bit adder in a volume smaller than 50-nm cube. I will then review our experimental work on memristor-based security primitives, in which we utilized device variations and their nonlinear I-Vs to demonstrate functionality and physical performance superior to those of conventional approaches. Finally, I will discuss Race Logic, a novel computing paradigm in which information is encoded in timing of the signals, so that a particular problem is mapped to a circuit with controllable memristor-based delay elements, and the solution is provided by measuring the time for the injected signals to propagate via circuit. Due to direct encoding of the computation to the underlying physics, Race Logic is extremely energy efficient for a variety of problems, such as bioinformatics and neurocomputing. I will conclude my talk with a summary on the device/material challenges, and potential future work, specific to the discussed applications.