山东大学学报 (工学版) ›› 2021, Vol. 51 ›› Issue (3): 7-14.doi: 10.6040/j.issn.1672-3961.0.2019.508
吴振鹏1,张健2,范星奇3,李翠平4
WU Zhenpeng1, ZHANG Jian2, FAN Xingqi3, LI Cuiping4
摘要: 针对联机分析处理(online analytical processing, OLAP)中的整体型聚集函数中位数,提出基于图形处理单元(graphics processing unit, GPU)的GPU-Median算法,通过对数据进行划分,分段排序,不断裁剪全局中位数之前的数据,对未裁剪的数据进行合并,得到最终的中位数,避免了全局的排序时间。提出GPU-Median+算法,对GPU-Median算法进行优化和扩展,使用CPU与GPU协同作业实现聚集操作,利用GPU处理每个队列的数据,CPU处理全局数据。试验和分析证明,相比CPU算法,GPU-Median+算法将中位数计算的时间复杂度从O(n2)降低到了O(n);相比GPU上的基数排序算法,GPU-Median+算法的计算时间减少了三分之一。该算法的应用使得GPU计算OLAP中的整体型聚集函数时,发挥出更加优良的并行计算能力,为提升OLAP的查询性能提供了新的思路。
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