Limitations of Intra-operator Parallelism Using Heterogeneous Computing Resources
Limitations of Intra-operator Parallelism Using Heterogeneous Computing Resources
复制标题
使用异构计算资源的算子内并行性的局限性
DOI：
10.1007/978-3-319-44039-2_20
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Wolfgang Lehner
中科院分区：
文献类型：
--
作者：
Tomas Karnagel;Dirk Habich;Wolfgang Lehner
硬件环境正在从同构多核系统向结合不同计算单元（如CPU和GPU）的异构系统转变。为了利用这些异构环境，数据库查询执行必须科普不同的体系结构和计算行为。在本文中，我们探讨了一个简单的想法，分区运营商的输入数据和并行处理所有的数据分区，每个计算单元一个分区。对于异构系统，数据必须根据计算单元的性能进行分区。我们定义了一种方法来计算分区大小，分析并行执行两个数据库操作员的例子，并提出限制，可能会阻碍显着的性能改进。本文的研究结果可以帮助系统开发人员评估异构环境中操作员内部并行的可能性和局限性，如果这种方法对给定的工作负载和硬件环境有利，则可以做出更明智的决策。
The hardware landscape is changing from homogeneous multi-core systems towards wildly heterogeneous systems combining different computing units, like CPUs and GPUs. To utilize these heterogeneous environments, database query execution has to adapt to cope with different architectures and computing behaviors. In this paper, we investigate the simple idea of partitioning an operator’s input data and processing all data partitions in parallel, one partition per computing unit. For heterogeneous systems, data has to be partitioned according to the performance of the computing units. We define a way to calculate the partition sizes, analyze the parallel execution exemplarily for two database operators, and present limitations that could hinder significant performance improvements. The findings in this paper can help system developers to assess the possibilities and limitations of intra-operator parallelism in heterogeneous environments, leading to more informed decisions if this approach is beneficial for a given workload and hardware environment.
影响因子：
2.5
作者：
Albutiu, Martina-Cezara;Kemper, Alfons;Neumann, Thomas
通讯作者：
Neumann, Thomas