Processing of Range Query Using SIMD and GPU

Processing of Range Query Using SIMD and GPU
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使用 SIMD 和 GPU 处理范围查询

DOI:
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发表时间:
2012
期刊:
ADBIS Workshops
影响因子:
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通讯作者:
P. Chovanec
P. Chovanec
中科院分区:
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文献类型:
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作者:
Pavel Bednár;P. Gajdoš;M. Krátký;P. Chovanec

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一维或多维范围查询是DBMS物理实现中最重要的查询之一。 (数据结构的)比较项的数量可能非常巨大,尤其是对于范围查询的选择性较低的情况。对于长度较长的更复杂的项目(或元组),比较操作的数量会增加,例如单词存储在 B 树中。由于范围查询处理期间可能会执行大量比较操作,因此我们可以考虑提供并行任务计算的硬件设备,例如 CPU 的 SIMD 或 GPU。在本文中,我们展示了范围查询算法的顺序、索引、CPU SIMD 和 GPU 变体的性能和可扩展性。这些结果使得未来将这些计算设备集成到 DBMS 内核中成为可能。
Onedimensional or multidimensional range query is one of the most important query of physical implementation of DBMS. The number of compared items (of a data structure) can be enormous especially for lower selectivity of the range query. The number of compare operations increases for more complex items (or tuples) with the longer length, e.g. words stored in a B-tree. Due to the possibly high number of compare operations executed during the range query processing, we can take into account hardware devices providing a parallel task computation like CPU’s SIMD or GPU. In this paper, we show the performance and scalability of sequential, index, CPU’s SIMD, and GPU variants of the range query algorithm. These results make possible a future integration of these computation devices into a DBMS kernel.