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- W4285194960 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." @default.
- W4285194960 created "2022-07-14" @default.
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- W4285194960 date "2022-08-01" @default.
- W4285194960 modified "2023-10-15" @default.
- W4285194960 title "The Impact of Thermal Enhance Layers on the Relaxation Effect in Analog RRAM" @default.
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- W4285194960 doi "https://doi.org/10.1109/ted.2022.3183958" @default.
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