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Effect of conductance linearity and multi-level cell characteristics of TaO_x-based synapse device on pattern

Changhyuck Sung¹, Seokjae Lim¹, Hyungjun Kim²

¹Department of Material Science and Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 790-784, Republic of Korea.

|January 13, 2018

Abstract:

To improve the classification accuracy of an image data set (CIFAR-10) by using analog input voltage, synapse devices with excellent conductance linearity (CL) and multi-level cell (MLC) characteristics are required. We analyze the CL and MLC characteristics of TaO_x-based filamentary resistive random access memory (RRAM) to implement the synapse device in neural network hardware. Our findings show that the number of oxygen vacancies in the filament constriction region of the RRAM directly controls the CL and MLC characteristics. By adopting a Ta electrode (instead of Ti) and the hot-forming step, we could form a dense conductive filament. As a result, a wide range of conductance levels with CL is achieved and significantly improved image classification accuracy is confirmed.

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