关系数据的高效协同处理

H. Pirk, S. Manegold, M. Kersten
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引用次数: 41

摘要

现代计算机系统中存储设备的多样性给数据管理系统带来了机遇和挑战。特别是图形处理单元(gpu)及其快速存储器的开发已经得到了相当深入的研究。然而,目前的方法将GPU视为独立的系统,无法提供有效的CPU/GPU合作的通用策略。我们为关系查询处理提出了这样一种策略:基于有损压缩的gpu驻留数据计算近似结果,并使用CPU上的残差(即丢失的数据)改进结果。我们开发了所需的算法,在现有的DBMS中实现了该策略,并发现即使对于大于可用GPU内存的数据集,性能也提高了8倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Waste not… Efficient co-processing of relational data
The variety of memory devices in modern computer systems holds opportunities as well as challenges for data management systems. In particular, the exploitation of Graphics Processing Units (GPUs) and their fast memory has been studied quite intensively. However, current approaches treat GPUs as systems in their own right and fail to provide a generic strategy for efficient CPU/GPU cooperation. We propose such a strategy for relational query processing: calculating an approximate result based on lossily compressed, GPU-resident data and refine the result using residuals, i.e., the lost data, on the CPU.We developed the required algorithms, implemented the strategy in an existing DBMS and found up to 8 times performance improvement, even for datasets larger than the available GPU memory.
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