Processing High-Volume Stream Queries on a Supercomputer

E. Zeitler, T. Risch
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引用次数: 17

Abstract

Scientific instruments, such as radio telescopes, colliders, sensor networks, and simulators generate very high volumes of data streams that scientists analyze to detect and understand physical phenomena. The high data volume and the need for advanced computations on the streams require substantial hardware resources and scalable stream processing. We address these challenges by developing data stream management technology to support high-volume stream queries utilizing massively parallel computer hardware. We have developed a data stream management system prototype for state-of-the-art parallel hardware. The performance evaluation uses real measurement data from LOFAR, a radio telescope antenna array being developed in the Netherlands.
在超级计算机上处理大容量流查询
科学仪器,如射电望远镜、对撞机、传感器网络和模拟器,会产生大量的数据流,科学家们通过分析这些数据流来探测和理解物理现象。高数据量和对流的高级计算需求需要大量的硬件资源和可扩展的流处理。我们通过开发数据流管理技术来解决这些挑战,以支持利用大规模并行计算机硬件的大容量流查询。我们已经为最先进的并行硬件开发了一个数据流管理系统原型。性能评估使用来自LOFAR的真实测量数据,LOFAR是荷兰正在开发的射电望远镜天线阵列。
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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