选择多个订单统计与图形处理单元

Pub Date : 2016-08-08 DOI:10.1145/2948974
Jeffrey D. Blanchard, Erik Opavsky, Emircan Uysaler
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引用次数: 1

摘要

从一个庞大的数据集中提取一组多阶统计信息,可以提供关于整个数据集中值分布的重要信息。本文介绍了一种算法bucketMultiSelect,用于使用图形处理单元(GPU)同时选择多个顺序统计信息。通常,当需要大量顺序统计信息时,对向量进行排序。当不需要向量的排序版本时,bucketMultiSelect通过消除排序中涉及的大部分不必要的操作来显着减少计算时间。对于大的向量,bucketMultiSelect在比排序向量更短的时间内返回数千个顺序统计信息,同时通常使用更少的内存。对于包含228个double类型值的向量,bucketMultiSelect在不到95ms的时间内选择101个百分位数的顺序统计信息,并且比使用GPU优化的合并排序对向量进行排序快8倍以上。
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Selecting Multiple Order Statistics with a Graphics Processing Unit
Extracting a set of multiple order statistics from a huge data set provides important information about the distribution of the values in the full set of data. This article introduces an algorithm, bucketMultiSelect, for simultaneously selecting multiple order statistics with a graphics processing unit (GPU). Typically, when a large set of order statistics is desired, the vector is sorted. When the sorted version of the vector is not needed, bucketMultiSelect significantly reduces computation time by eliminating a large portion of the unnecessary operations involved in sorting. For large vectors, bucketMultiSelect returns thousands of order statistics in less time than sorting the vector while typically using less memory. For vectors containing 228 values of type double, bucketMultiSelect selects the 101 percentile order statistics in less than 95ms and is more than 8× faster than sorting the vector with a GPU optimized merge sort.
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