扑克:基于排列的SIMD执行密集树搜索的路径编码

Feng Zhang, Jingling Xue
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引用次数: 1

摘要

我们提出了POKER,一种基于排列的向量化方法,用于向量化B+树上的多个查询。我们的关键见解是结合矢量负载和基于路径编码的排列,以减轻内存延迟,同时将查询所需的键比较数量保持在最低限度。作为c++模板库实现,POKER代表了一种通用的解决方案,用于在配备SIMD单元的多核处理器上对索引树的查询进行向量化。对于一组使用24种配置评估的五个代表性基准测试,在支持256位AVX2的Intel Broadwell处理器上,POKER在单线程情况下的平均性能比最先进的基准测试高出2.11倍,在8线程情况下的平均性能高出2.28倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Poker: permutation-based SIMD execution of intensive tree search by path encoding
We propose POKER, a permutation-based vectorization approach for vectorizing multiple queries over B+-trees. Our key insight is to combine vector loads and path-encoding-based permutations to alleviate memory latency while keeping the number of key comparisons needed for a query to a minimum. Implemented as a C++ template library, POKER represents a general-purpose solution for vectorizing the queries over indexing trees on multi-core processors equipped with SIMD units. For a set of five representative benchmarks evaluated with 24 configurations each, POKER outperforms the state-of-the-art by 2.11x with one single thread and 2.28x with eight threads on an Intel Broadwell processor that supports 256-bit AVX2, on average.
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