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 proc...Show MoreMetadata
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 3-D (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. Research efforts have been devoted to RRAM testing, while existing test solutions predominantly focus on fault detection. Fault diagnosis for M3D-integrated RRAM and MIVs remains unexplored. In this work, we propose a diagnosis procedure to identify the fault origin when a chip fails the manufacturing test. We present a detailed characterization of RRAM faulty behaviors in the presence of concurrent process variations and manufacturing defects. Based on RRAM characteristics, we develop a diagnosis sequence by identifying appropriate reference resistance and applied voltages to efficiently distinguish fault origins. Experimental results show that the proposed solution is compatible with existing test algorithms to significantly improve diagnostic resolution. By appending the proposed sequence to test algorithms, over 90% diagnostic resolution is achieved for every type of fault considered in an M3D-integrated RRAM.
Published in: IEEE Transactions on Very Large Scale Integration (VLSI) Systems ( Volume: 32, Issue: 7, July 2024)