In-memory computing based on multi-level RRAMs has shown great potential in neural network computations. In-situ training is becoming increasingly attractive, but requires accurate on-chip RRAM cell write. In this paper, we demonstrate a fully on-chip write and verify circuit and a novel methodology to improve the endurance of RRAM. Simulations show up to 120 × programming speed improvement, achieving 86% reduction of conductance standard deviation and 50 × longer device lifetime.
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Zhang et al. (2024) studied this question.
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