The Impact of Thermal Enhance Layers on the Relaxation Effect in Analog RRAM
Yue Xi, Jianshi Tang, Bin Gao, Feng Xu, Xinyi Li, Yuyao Lu, He Qian, Huaqiang Wu
Abstract
Computing-in-memory (CIM) with analog resistive random access memory (RRAM) has recently shown great potential in building energy-efficient hardware for artificial intelligence (AI). However, the relaxation effect of analog RRAM featuring post-programming conductance drift has become a key performance-limiting factor. In this work, a comprehensive study of the relaxation effect is presented from the analysis of its causes to the strategy for device optimization as well as the impact on CIM applications. An application-oriented quantitative indicator (relative deviation [RD]) is proposed to fairly evaluate the relaxation effect of different devices. In particular, the influence of oxygen content in different thermal enhanced layers (TELs) on the relaxation and maximum conductance value <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${G}_{max}$ </tex-math></inline-formula> of analog RRAM is studied. A theory of ternary oxide TEL is proposed to mitigate relaxation while maintaining low <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${G}_{max}$ </tex-math></inline-formula> , which is experimentally validated by TaTiO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>x</i></sub> as TEL. Furthermore, neural network simulation is carried out to analyze the requirement for RRAM relaxation for CIM applications. This work provides a useful strategy for device optimization to suppress the relaxation effect by engineering the TEL.