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On Resistive Memories: One Step Row Readout Technique and Sensing Circuitry

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arxiv 1903.01512 v1 pith:NRUXTG5O submitted 2019-03-04 cs.ET cs.AR

classification cs.ETcs.AR
keywords memoriesreadoutresistivecircuitrycrossbarproposedreadingtechnique
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Transistor-based memories are rapidly approaching their maximum density per unit area. Resistive crossbar arrays enable denser memory due to the small size of switching devices. However, due to the resistive nature of these memories, they suffer from current sneak paths complicating the readout procedure. In this paper, we propose a row readout technique with circuitry that can be used to read {selector-less} resistive crossbar based memories. High throughput reading and writing techniques are needed to overcome the memory-wall bottleneck problem and to enable near memory computing paradigm. The proposed technique can read the entire row of dense crossbar arrays in one cycle, unlike previously published techniques. The requirements for the readout circuitry are discussed and satisfied in the proposed circuit. Additionally, an approximated expression for the power consumed while reading the array is derived. A figure of merit is defined and used to compare the proposed approach with existing reading techniques. Finally, a quantitative analysis of the effect of biasing mismatch on the array size is discussed.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Spiking Neural Networks for Inference and Learning: A Memristor-based Design Perspective

    cs.ET 2019-09 unverdicted novelty 2.0 of 10

    A review of memristor-compatible learning for spiking neural networks, centered on device-aware three-factor plasticity rules with pulse-count updates derived from a fitted RRAM conductance model.

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