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Cache-Sensitive Memory Layout for Dynamic Binary Trees

机译:动态二叉树的缓存敏感型内存布局

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We use cache-sensitive memory layouts to improve search performance in ordinary binary search trees, without increasing the time complexity of insertion or deletion. Our approach does not require changes to the structure of the nodes or the rebalancing strategy of the tree. Cache-sensitivity is maintained with a memory-layout invariant that keeps a given number of neighboring nodes in the tree stored in the same cache block. We show how to preserve it using worst-case constant-time operations executed when the tree changes. In our extensive experiments, the invariant consistently improved the search performance of large AVL and red-black trees by 26-32%, on synthetic data as well as realistic search tree operations extracted from a database benchmark. We also compare binary search trees with several cache-sensitive B-trees, and non-dynamic approaches for laying out tree nodes in a multi-level memory hierarchy.
机译:我们使用对缓存敏感的内存布局来提高普通二进制搜索树中的搜索性能,而不会增加插入或删除的时间复杂度。我们的方法不需要更改节点的结构或树的重新平衡策略。高速缓存敏感度通过内存布局不变性来维护,该不变式将给定数量的相邻节点保留在存储在同一高速缓存块中的树中。我们展示了如何使用在树更改时执行的最坏情况的恒定时间操作来保存它。在我们广泛的实验中,对于合成数据以及从数据库基准中提取的实际搜索树操作,不变量始终将大型AVL和红黑树的搜索性能提高了26-32%。我们还将二进制搜索树与几个对缓存敏感的B树进行比较,并使用非动态方法在多级内存层次结构中布置树节点。

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