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Peacock Hashing: Deterministic and Updatable Hashing for High Performance Networking

机译:孔雀散列:高性能网络的确定性和可更新的散列

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Hash tables are extensively used in networking to implement data-structures that associate a set of keys to a set of values, as they provide O(1), query, insert and delete operations. However, at moderate or high loads collisions are quite frequent which not only increases the access time, but also induces non-determinism in the performance. Due to this non-determinism, the performance of these hash tables degrades sharply in the multi-threaded network processor based environments, where a collection of threads perform the hashing operations in a loosely synchronized manner. In such systems, it is critical to keep the hash operations more deterministic. A recent series of papers have been proposed, which employs a compact on-chip memory to enable deterministic and fast hash queries. While effective, these schemes require substantial on-chip memory, roughly 10-bits for every entry in the hash table. This limits their general usability; specifically in the network processor context, where on-chip resources are scarce. In this paper, we propose a novel hash table construction called Peacock hash, which reduces the on-chip memory by more than 10-folds while keeping a high degree of determinism in performance. This significantly reduced on-chip memory not only makes Peacock hashing much more appealing for the general use but also makes it an attractive choice for the implementation of a hash hardware accelerator on a network processor.
机译:哈希表的联网实现,因为它们提供O(1),查询,插入和删除操作中,一组键的一组值相关联的数据结构广泛使用。然而,在中等或高负荷碰撞是相当频繁,不仅增加了访问时间,而且还会导致性能不确定性。由于这个不确定的,这些哈希表劣化急剧在多线程网络处理器基于环境中,线程的集合中的一个松散同步方式执行散列操作的性能。在这种系统中,关键是要保持散列操作更具有确定性。最近的一系列论文已经提出,它采用紧凑的片上存储器,使确定的和快速的哈希查询。尽管有效,但这些方案需要大量的片上存储器,大致10位为在哈希表中的每个条目。这限制了他们的通用性;特别是在网络处理器上下文,其中片上资源稀少。在本文中,我们提出了称为孔雀散列的新的哈希表结构,它由多于10倍降低的片上存储器,同时保持性能的高度决定的。这显著降低片上存储器不仅使孔雀哈希更吸引人的一般用途,但也使它成为一个散列硬件加速器对网络处理器的执行一个有吸引力的选择。

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