Mixed-Signal Neuromorphic Computing Circuits Using Hybrid CMOS-RRAM Integration

摘要

Recent integration of Resistive Random Access Memory (RRAM) with standard CMOS has spurred exploration of high-density and low-power in-memory computing. RRAM arrays are being intensely investigated for analog-domain Vector Matrix Multiplication (VMM) and Neuromorphic Computing. However, to exploit the advantages of RRAM over other forms of nonvolatile memories, mixed-signal circuit designers need to accommodate their device nonidealities, and design circuits to translate high-level deep neural network algorithms to mixed-signal hardware. This brief reviews the field of neuromorphic computing using hybrid CMOS-RRAM circuits, associated circuit design challenges, and potential approaches for their mitigation, followed by benchmarking of recent demonstrations.