Abstract
We introduce P oker , a permutation-based 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, P oker 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, P oker 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. In addition, strip-mining queries will further improve P oker ’s performance by 1.21x (with one single thread) and 1.31x (with eight threads), on average.
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