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Fast Computation of Database Operations Using Content-Addressable Memories

机译:使用内容可寻址内存快速计算数据库操作

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Research efforts on conventional CPU architectures over the past decade have focused primarily on performance enhancement. In contrast, the NPU (Network Processing Unit) architectures have evolved significantly in terms of functionality. The memory hierarchy of a typical network router features a Content-Addressable Memory (CAM) which provides very fast constant-time lookups over large amounts of data and facilitates a wide range of novel high-speed networking solutions such as Packet Classification, Intrusion Detection and Pattern Matching. While these networking applications span an entirely different domain than the database applications, they share a common operation of searching for a particular data entry among huge amounts of data. In this paper, we investigate how CAM-based technology can help in addressing the existing memory hierarchy bottlenecks in database operations. We present several high-speed CAM-based solutions for computationally intensive database operations. In particular, we discuss an efficient linear-time complexity CAM-based sorting algorithm and apply it to develop a fast solution for complex join operations widely used in database applications.
机译:在过去的十年中,对常规CPU体系结构的研究工作主要集中在性能增强上。相比之下,NPU(网络处理单元)体系结构在功能方面已经有了很大的发展。典型网络路由器的存储器层次结构具有内容可寻址存储器(CAM),它可对大量数据进行非常快速的恒定时间查找,并促进了各种新颖的高速联网解决方案,例如数据包分类,入侵检测和模式匹配。尽管这些联网应用程序跨越的领域与数据库应用程序完全不同,但是它们共享一种在海量数据中搜索特定数据条目的通用操作。在本文中,我们研究了基于CAM的技术如何帮助解决数据库操作中现有的内存层次结构瓶颈。我们为计算密集型数据库操作提供了几种基于CAM的高速解决方案。特别是,我们讨论了一种基于线性时间复杂度基于CAM的高效排序算法,并将其应用于针对数据库应用中广泛使用的复杂联接操作开发快速解决方案。

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