Parallel Programming of Resistive Cross-point Array for Synaptic Plasticity

This paper proposes a parallel programming scheme for the cross-point array with resistive random access memory (RRAM). Synaptic plasticity in unsupervised learning is realized by tuning the conductance of each RRAM cell. Inspired by the spike-timing-dependent-plasticity (STDP), the programming strength is encoded into the spike firing rate (i.e., pulse frequency) and the overlap time (i.e., duty cycle) of the pre-synaptic node and post-synaptic node, and simultaneously applied to all RRAM cells in the cross-point array. Such an approach achieves parallel programming of the entire RRAM array, only requiring local information from pre-synaptic and post-synaptic nodes to each RRAM cell. As demonstrated by digital peripheral circuits implemented in 65 nm CMOS, the programming time of a 40 kb RRAM array is 84 ns, indicating 900X speedup as compared to state-of-the-art software approach of sparse coding in image feature extraction.