Computing-in-memory with thin-filmtransistors: challenges and opportunities. (1st June 2022)

• Record Type: Journal Article
• Authors: Tang, Wenjun; Liu, Jialong; Li, Hongtian; Chen, Deyun; Jiang, Chen; Li, Xueqing; Yang, Huazhong
• Is Part Of: Flexible and printed electronics. Volume 7:Number 2(2022)
• Publication Date: 2022-06-01
• Subjects: thin film transistor -- edge computing -- computing-in-memory; Flexible electronics -- Periodicals; Printed electronics -- Periodicals; Flexible electronics; Printed electronics; Electronic journals; Periodicals; 621.381
• DOI: 10.1088/2058-8585/ac541d
• Languages: English
• ISSNs: 2058-8585

Abstract

Abstract: Thin-film transistors (TFTs) have attracted significant interest recently fortheir great potential in a wide range of edge computing applications, due to their advantages such as large-area low-cost flexible fabrications, and well integration with sensors and displays. With the support of in situ processing of sensor data, TFT-based edge systems show their advantages in large-scale dense sensing with real-time energy-efficient processing and interaction, and more excitingly, they provide the opportunity to eliminate the massive data transfer to the cloud servers. However, the design of high-performance processing modules based on TFT is difficult, due to large device variation, poor stability, and low mobility. Computing-in-memory (CiM), which has been proposed recently as a high-efficiency high-parallelism computing approach, is expected to improve the capacity of TFT-based edge computing systems. In thispaper, various recent works on TFT-based CiM have been summarized, showing the superiority to conventional processing flow by efficient in-memory analog computation with mitigation of data transfer, and reduced analog-to-digital converter usage for sensor data. With both opportunities and challenges, the design space and trend of TFT-based CiM to be explored are then described. Finally, further development and co-optimization from device to system are discussed for the flourishing of the next-generation intelligent TFT-based edge system.