Parallel Optimization of Queries in XML Dataset Using GPU

X. Si, Airu Yin, Xiaocheng Huang, Xiaojie Yuan, X. Liu, G. Wang
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引用次数: 10

Abstract

As XML is playing a crucial role in web services, databases, and document processing, efficient processing of XML queries has become an important issue. On the other hand, due to the increasing number of users, high throughput of XML queries is also required to execute tens of thousands of queries in a short time. Given the great success of GPGPU (General-Purpose computations on the Graphics Processors), we propose a parallel XML query model based on GPU, which mainly consists of two efficient task distribution strategies, to improve the efficiency and throughput of XML queries. We have developed a parallel simplified XPath language using Compute Unified Device Architecture (CUDA) on GPU, and evaluate our model on a recent NVIDIA GPU in comparison with its counterpart on eight-core CPU. The experiment results show that our model achieves both higher throughput and efficiency than CPU-based XML query.
基于GPU的XML数据集查询并行优化
由于XML在web服务、数据库和文档处理中起着至关重要的作用,因此XML查询的有效处理已成为一个重要问题。另一方面,由于用户数量的增加,也需要高吞吐量的XML查询,以便在短时间内执行数万个查询。鉴于GPGPU (General-Purpose computing on the Graphics Processors)的巨大成功,我们提出了一种基于GPU的并行XML查询模型,该模型主要由两种高效的任务分配策略组成,以提高XML查询的效率和吞吐量。我们在GPU上使用计算统一设备架构(CUDA)开发了一种并行简化的XPath语言,并在最新的NVIDIA GPU上评估了我们的模型,并将其与8核CPU上的对应模型进行了比较。实验结果表明,该模型比基于cpu的XML查询具有更高的吞吐量和效率。
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