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ADVANCED HASHING SCHEMES FOR PACKETFORWARDING USING SET ASSOCIATIVEMEMORY ARCHITECTURES

机译:使用集合关联记忆体架构进行分组转发的高级哈希方案

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摘要

Building a high performance IP packet forwarding (PF) engine remains a challenge due to increasingly stringent throughput requirements and the growing sizes of IP forwarding tables.The router has to match the incoming packet's IP address against the forwarding table.The matching process has to be done in wire speed which is why scalability and low power consumption are features that PF engines must maintain.It is common for PF engines to use hash tables; however, the classic hashing downsides have to be dealt with (e.g., collisions, worst case memory access time, ... etc.).While open addressing hash tables, in general, provide good average case search performance, their memory utilization and worst case performance can degrade quickly due to collisions that leads to bucket overflows.Set associative memory can be used for hardware implementations of hash tables with the property that each bucket of a hash table can be searched in one memory cycle.Hence, PF engine architectures based on associative memory will outperform those based on the conventional Ternary Content Addressable Memory (TCAM) in terms of power and scalability.The two standard solutions to the overflow problem are either to use some sort of predefined probing (e.g., linear or quadratic) or to use multiple hash functions.This work presents two new hash schemes that extend both aforementioned solutions to tackle the overflow problem efficiently.The first scheme is a hash probing scheme that is called Content-based HAsh Probing, or CHAP.CHAP is a probing scheme that is based on the content of the hash table to avoid the classical side effects of predefined hash probing methods (i.e., primary and secondary clustering phenomena) and at the same time reduces the overflow.The second scheme, called Progressive Hashing, or PH, is a general multiple hash scheme that reduces the overflow as well.PH splits the prefixes into groups where each group is assigned one hash function, then reuse some hash functions in a progressive fashion to reduce the overflow.We show by experimenting with real IP lookup tables that both schemes outperform other hashing schemes.
机译:由于吞吐量要求日益严格以及IP转发表的规模不断扩大,构建高性能IP数据包转发(PF)引擎仍然是一个挑战。路由器必须将传入数据包的IP地址与转发表进行匹配。线速完成,这就是为什么PF引擎必须维护可伸缩性和低功耗的原因。PF引擎通常使用哈希表;但是,必须解决经典的散列缺点(例如,冲突,最坏情况下的内存访问时间等)。虽然开放式寻址哈希表通常提供良好的平均大小写搜索性能,其内存利用率以及最差的结果冲突会导致存储桶溢出,因此案例性能可能会迅速下降。集关联内存可用于哈希表的硬件实现,其属性是可以在一个内存周期内搜索哈希表的每个存储桶。因此,基于PF引擎的架构关联存储器的性能和可扩展性将优于基于传统三进制内容可寻址存储器(TCAM)的存储器。溢出问题的两种标准解决方案是使用某种预定义的探测(例如,线性或二次)或使用多个哈希函数。这项工作提出了两个新的哈希方案,这些方案扩展了上述两个解决方案以有效解决溢出问题。第一个方案是哈希p抢夺方案称为基于内容的哈希探测或CHAP。CHAP是一种基于哈希表内容的探测方案,可避免预定义哈希探测方法的经典副作用(即,主要和次要群集现象),以及第二种方案称为渐进式哈希(PH),它也是一种通用的多重哈希方案,它也可以减少溢出。PH将前缀分成几组,每组分配一个哈希函数,然后重用一些哈希函数以渐进方式减少溢出。我们通过试验真实的IP查找表来证明,这两种方案都优于其他哈希方案。

著录项

  • 作者

    Hanna Michel Nabil;

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  • 年度 2010
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  • 原文格式 PDF
  • 正文语种 en
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