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Network processor memory hierarchy designs for IP packet classification.

机译:用于IP数据包分类的网络处理器内存层次结构设计。

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摘要

The use of Application Specific Integrated Circuits (ASICs) for processing Internet Protocol (IP) packets is becoming infeasible due to increasing network wire transmission speeds, coupled with frequent improvements to existing algorithms. Development time and cost to fabricate a new generation of ASICs to implement newly developed algorithms is increasing. The age of programmable network processors (NPs) has arrived, since their flexibility allows reuse and thus amortizes their development cost over successive generations of network applications.; The flexibility of network processors comes at a price; there is a trade-off in performance compared to ASICs. One major factor is the performance of the memory subsystem. This dissertation discusses the design of memory hierarchies for network processors to achieve high performance in IP packet forwarding and classification. We demonstrate how caching can be used to improve the performance of a trie-based IP forwarding algorithm. We develop a new packet classification algorithm based on partitioning classification rules into separate categories. Packets are classified independently using each rule category and then results are combined. The advantage is two-fold: parallel computation and reduced memory requirements per rule category. The algorithm is thus well-suited for implementation on multiple NPs which have limited memory. We justify our approach through trace-driven simulation.
机译:由于增加的网络线路传输速度以及对现有算法的频繁改进,使用专用集成电路(ASIC)处理Internet协议(IP)数据包已变得不可行。制造新一代ASIC以实现新开发算法的开发时间和成本不断增加。可编程网络处理器(NP)的时代已经到来,因为它们的灵活性允许重用,并因此在连续几代的网络应用程序中摊销其开发成本。网络处理器的灵活性需要付出一定的代价。与ASIC相比,性能需要权衡。一个主要因素是内存子系统的性能。本文讨论了网络处理器的存储层次结构设计,以实现IP数据包转发和分类的高性能。我们演示了如何使用缓存来提高基于Trie的IP转发算法的性能。我们基于分类规则划分为单独的类别,开发了一种新的数据包分类算法。使用每个规则类别对数据包进行独立分类,然后组合结果。优点有两个:并行计算和每个规则类别减少的内存需求。因此,该算法非常适合在内存有限的多个NP上实施。我们通过跟踪驱动的仿真来证明我们的方法是正确的。

著录项

  • 作者

    Low, Douglas Wai Kok.;

  • 作者单位

    University of Washington.;

  • 授予单位 University of Washington.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2005
  • 页码 137 p.
  • 总页数 137
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

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