A Brain-Inspired VLSI Architecture for Nano Devices and Circuits

What kind of system is most suited to implementation in nanoelectronics? A human-like intelligent system is proposed as one of the most promising candidates. In order to achieve human-like recognition performance, various types of sensing devices are required to gather information from environment, a large capacity of memories for learning from experience, and huge computational powers for recognition and understanding. Multifunctional device integration would certainly provide a platform for such system implementation. However, regarding the computational powers, enhancing the integration density alone will not be a solution, because the computational principle in the brain is not yet known. A brain-inspired VLSI architecture based on the associative principle is presented in this paper, in which the non-linear I-V characteristics of nano functional devices are directly utilized as the very bases of computation. The mind processing algorithms are tolerable to elemental-device level variability, thus being most suited to building systems in nanoelectronics.