Energy-Efficient Near-Sensor Event Detector based on Multilevel Ga2O3 RRAM

被引：0

作者：

Morsali, Mehrdad ^{[1
]}

Tabrizchi, Sepehr ^{[2
]}

Velpula, Ravi Teja ^{[3
]}

Muthu, Mano Bala Sankar ^{[3
]}

Hieu Pham Trung Nguyen ^{[3
]}

Imani, Mohsen ^{[4
]}

Roohi, Arman ^{[2
]}

Angizi, Shaahin ^{[1
]}

机构：

[1] New Jersey Inst Technol, Dept Elect & Comp Engn, Newark, NJ 07102 USA

[2] Univ Nebraska, Sch Comp, Lincoln, NE USA

[3] Texas Tech Univ, Dept Elect & Comp Engn, Lubbock, TX 79409 USA

[4] Univ Calif Irvine, Dept Comp Sci, Irvine, CA USA

来源：

2024 IEEE COMPUTER SOCIETY ANNUAL SYMPOSIUM ON VLSI, ISVLSI | 2024年

基金：

美国国家科学基金会;

关键词：

D O I：

10.1109/ISVLSI61997.2024.00067

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a cost-effective Near-Sensor Processing (NSP) platform is developed based on an experimentally-measured Ti/TiN/Ga2O3/Ti/Pt Resistive Random Access Memory (RRAM) device that facilitates event detection for edge vision sensors without the requirement for power-intensive Analog-to-Digital Converters (ADCs). The platform is supported with a hardware-friendly background comparison technique providing adjustable precision that allows for a dynamic balance between accuracy and efficiency at runtime. Our device-to-architecture simulation results demonstrate that the proposed platform achieves on average 66% and 63% energy saving over STT-MRAM and SOT-MRAM counterparts due to utilizing the ADC-less method.

引用

页码：331 / 336

页数：6

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