Analysis of electro-chemical RAM synaptic array for energy-efficient weight update

초록

While electro-chemical RAM (ECRAM)-based cross-point synaptic arrays are considered to be promising candidates for energy-efficient neural network computational hardware, array-level analyses to achieve energy-efficient update operations have not yet been performed. In this work, we fabricated CuOx/HfOx/WOx ECRAM arrays and demonstrated linear and symmetrical weight update capabilities in both fully parallel and sequential update operations. Based on the experimental measurements, we showed that the source-drain leakage current (I-SD) through the unselected ECRAM cells and resultant energy consumption-which had been neglected thus far-contributed a large portion to the total update energy. We showed that both device engineering to reduce I-SD and the selection of an update scheme-for example, column-by-column-that avoided I-SD intervention via unselected cells were key to enable energy-efficient neuromorphic computing.

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