低功耗CMOS自控预充免费内容可寻址存储器与最小面积的图像处理设备

S. Arulpriya, P. Kumar
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引用次数: 0

摘要

图像处理设备在医疗、安全、生物识别等领域发挥着至关重要的作用。这些设备的范围从便携式大小到更大的机器,有或没有人机接口的可能性。由于图像处理和人机界面系统应用对存储器的要求较高,因此功耗和面积都要小。在图像分类中,数据搜索是重中之重。通过硬件执行高速搜索使用内容可寻址内存。但该电路存在较高的功耗、预充电问题和较低的性能。对于较长的单词长度,需要消除预充电。因此,自控预充式凸轮(SCPF-CAM)适用于高速应用。本文提出了一种采用CMOS 32nm技术的4T混合自控预充电可寻址存储器。实验结果表明,该电路工作速度快,搜索时间短,运算性能好。与传统的SCPF-CAM相比,8T CAM减少了晶体管的数量。面积减少约20%,可用于低功耗和低能耗应用。在概述中,HSPICE预测技术模型用于在32nm CMOS技术上实现。这项工作将在未来扩展使用FinFET技术,泄漏电流可以最小化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Low power CMOS based Self Controlled Precharge Free Content Addressable Memory with Minimum area for Image Processing Devices
Image processing devices plays a vital role in several applications like medical, security, biometric etc. The devices ranges from portable size to larger machines with and without Human Computer Interface possibilities. As the image processing and human computer interface system application requires higher memory requirements, the power and area should be small. Searching of data is a high priority work in image classification. To perform high speed search through hardware Content Addressable Memory is used. But the circuit suffers from higher power consumption, precharging issues and low performance. For longer word length the elimination of precharge is needed. So for high speed applications self-controlled precharge-free CAM (SCPF-CAM) is suitable. A 4T hybrid self controlled pre charge free Content Addressable Memory is proposed in this paper using CMOS 32nm technology. The observation shows that the circuit works at high speed, minimizes the search time and has high performance operation. When compared to the conventional SCPF-CAM, 8T CAM the proposed design reduces the number of transistors. The reduction in area is about approximately 20% and can be used in low power and low energy applications. In Synopsis HSPICE Predictive technology models were used for the implementation in 32nm CMOS technology. The work will be extended in future using FinFET technology where the leakage current can be minimized.
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