Fault Diagnosis for Resistive Random-Access Memory and Monolithic Inter-tier Vias in Monolithic 3D Integration

Abstract

Resistive random-access memory (RRAM) constitutes a promising technology for next-generation memory architectures due to its simple structure, high on/off ratio, and processing-in-memory ability. Its compatibility with emerging monolithic 3D (M3D) integration enables extremely high density using monolithic inter-tier vias (MIVs). However, both RRAM and M3D are susceptible to high defect rates due to immature manufacturing processes and process variations. Fault diagnosis for M3D-integrated RRAM and MIVs is therefore necessary to facilitate yield learning. In this work, we present a detailed characterization of RRAM faulty behaviors in the presence of process variations and manufacturing defects. We develop a diagnosis procedure by identifying appropriate reference resistance based on RRAM characteristics to efficiently distinguish fault origins. Results show that the proposed solution is compatible with existing test algorithms to significantly improve diagnostic resolution without affecting fault coverage.