A New 1P1R Image Sensor with In-Memory Computing Properties Based on Silicon Nitride Devices

• Main Authors: Vasileiadis, Nikolaos, Ntinas, Vasileios, Fyrigos, Iosif-Angelos, Karamani, Rafailia-Eleni, Ioannou-Sougleridis, Vassilios, Normand, Pascal, Karafyllidis, Ioannis, Sirakoulis, Georgios Ch, Dimitrakis, Panagiotis
• Format: Conference Proceeding
• Language: English
• Subjects: BJT; Computational modeling; Computer architecture; crossbar; dot product engine; edge computing; image sensor; Image sensors; in-memory computing; Integrated circuit modeling; IoT; memristor; Memristors; phototransistor; resistance switching; resistive random access memory (RRAM); Silicon nitride; SPICE; Switching circuits
• ISSN: 2158-1525; 2158-1525
• DOI: 10.1109/ISCAS51556.2021.9401586

Research progress in edge computing hardware, capable of demanding in-the-field processing tasks with simultaneous memory and low power properties, is leading the way towards a revolution in IoT hardware technology. Resistive random access memories (RRAM) are promising candidates for replacing current non-volatile memories and realize storage class memories, but also due to their memristive nature they are the perfect candidates for in-memory computing architectures. In this context, a CMOS compatible silicon nitride (SiN) device with memristive properties is presented accompanied by a data-fitted model extracted through analysis of measured resistance switching dynamics. Additionally, a new phototransistor-based image sensor architecture with integrated SiN memristor (1P1R) was presented. The in-memory computing capabilities of the 1P1R device were evaluated through SPICE-level circuit simulation with the previous presented device model. Finally, the fabrication aspects of the sensor are discussed.