首页> 外文期刊>Circuits and systems >Data Intelligent Low Power High Performance TCAM for IP-Address Lookup Table
【24h】

Data Intelligent Low Power High Performance TCAM for IP-Address Lookup Table

机译:用于IP地址查找表的数据智能低功耗高性能TCAM

获取原文
获取原文并翻译 | 示例
           

摘要

This paper represents current research in low-power Very Large Scale Integration (VLSI) domain. Nowadays low power has become more sought research topic in electronic industry. Power dissipation is the most important area while designing the VLSI chip. Today almost all of the high speed switching devices include the Ternary Content Addressable Memory (TCAM) as one of the most important features. When a device consumes less power that becomes reliable and it would work with more efficiency. Complementary Metal Oxide Semiconductor (CMOS) technology is best known for low power consumption devices. This paper aims at designing a router application device which consumes less power and works more efficiently. Various strategies, methodologies and power management techniques for low power circuits and systems are discussed in this research. From this research the challenges could be developed that might be met while designing low power high performance circuit. This work aims at developing Data Aware AND-type match line architecture for TCAM. A TCAM macro of 256 × 128 was designed using Cadence Advanced Development Environment (ADE) with 90 nm technology file from Taiwan Semiconductor Manufacturing Company (TSMC). The result shows that the proposed Data Aware architecture provides around 35% speed and 45% power improvement over existing architecture.
机译:本文介绍了低功耗超大规模集成(VLSI)领域的最新研究。如今,低功耗已成为电子行业中越来越受追捧的研究话题。在设计VLSI芯片时,功耗是最重要的领域。今天,几乎所有的高速交换设备都包括三重内容可寻址存储器(TCAM),这是最重要的功能之一。当设备消耗较少的功率时,它将变得可靠,并且可以提高效率。互补金属氧化物半导体(CMOS)技术以低功耗设备而闻名。本文旨在设计一种功耗更低,工作效率更高的路由器应用设备。本研究讨论了低功耗电路和系统的各种策略,方法和电源管理技术。通过这项研究,可以开发出在设计低功耗高性能电路时可能遇到的挑战。这项工作旨在为TCAM开发数据感知AND型匹配线体系结构。使用台湾半导体制造公司(TSMC)的具有90 nm技术文件的Cadence高级开发环境(ADE)设计了256×128的TCAM宏。结果表明,与现有架构相比,提出的数据感知架构可提供约35%的速度和45%的功耗提升。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号