Data partitioning on chip multiprocessors

J. Cieslewicz, K. A. Ross
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引用次数: 42

Abstract

Partitioning is a key database task. In this paper we explore partitioning performance on a chip multiprocessor (CMP) that provides a relatively high degree of on-chip thread-level parallelism. It is therefore important to implement the partitioning algorithm to take advantage of the CMP's parallel execution resources. We identify the coordination of writing partition output as the main challenge in a parallel partitioning implementation and evaluate four techniques for enabling parallel partitioning. We confirm previous work in single threaded partitioning that finds L2 cache misses and translation lookaside buffer misses to be important performance issues, but we now add the management of concurrent threads to this analysis.
芯片多处理器上的数据分区
分区是一项关键的数据库任务。在本文中,我们探讨了芯片多处理器(CMP)上的分区性能,它提供了相对较高的片上线程级并行性。因此,实现分区算法以利用CMP的并行执行资源是很重要的。我们将写入分区输出的协调确定为并行分区实现中的主要挑战,并评估了实现并行分区的四种技术。我们确认了之前在单线程分区中发现L2缓存缺失和转换暂置缓冲区缺失是重要的性能问题的工作,但是我们现在将并发线程的管理添加到这个分析中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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