k-ary search on modern processors

B. Schlegel, Rainer Gemulla, Wolfgang Lehner
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引用次数: 66

Abstract

This paper presents novel tree-based search algorithms that exploit the SIMD instructions found in virtually all modern processors. The algorithms are a natural extension of binary search: While binary search performs one comparison at each iteration, thereby cutting the search space in two halves, our algorithms perform k comparisons at a time and thus cut the search space into k pieces. On traditional processors, this so-called k-ary search procedure is not beneficial because the cost increase per iteration offsets the cost reduction due to the reduced number of iterations. On modern processors, however, multiple scalar operations can be executed simultaneously, which makes k-ary search attractive. In this paper, we provide two different search algorithms that differ in terms of efficiency and memory access patterns. Both algorithms are first described in a platform independent way and then evaluated on various state-of-the-art processors. Our experiments suggest that k-ary search provides significant performance improvements (factor two and more) on most platforms.
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在现代处理器上的K-ary搜索
本文提出了一种新的基于树的搜索算法,该算法利用了几乎所有现代处理器中发现的SIMD指令。这些算法是二分搜索的自然扩展:二分搜索在每次迭代中执行一次比较,从而将搜索空间分成两部分,而我们的算法一次执行k次比较,从而将搜索空间分成k个部分。在传统处理器上,这种所谓的k-ary搜索过程是无益的,因为每次迭代的成本增加抵消了由于迭代次数减少而导致的成本降低。然而,在现代处理器上,可以同时执行多个标量操作,这使得k-ary搜索很有吸引力。在本文中,我们提供了两种不同的搜索算法,它们在效率和内存访问模式方面有所不同。这两种算法首先以平台独立的方式进行描述,然后在各种最先进的处理器上进行评估。我们的实验表明,k-ary搜索在大多数平台上提供了显著的性能改进(因子2或更多)。
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