High performance threaded data streaming for large scale simulations

V. Bhat, S. Klasky, S. Atchley, Micah Beck, D. McCune, M. Parashar
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引用次数: 41

Abstract

We have developed a threaded parallel data streaming approach using logistical networking (LN) to transfer multiterabyte simulation data from computers at NERSC to our local analysis/visualization cluster, as the simulation executes, with negligible overhead. Data transfer experiments show that this concurrent data transfer approach is more favorable compared with writing to local disk and later transferring this data to be post-processed. Our algorithms are network aware, and can stream data at up to 97 Mbs on a 100 Mbs link from CA to NJ during a live simulation, using less than 5% CPU overhead at NERSC. This method is the first step in setting up a pipeline for simulation workflow and data management.
用于大规模模拟的高性能线程数据流
我们已经开发了一种线程并行数据流方法,使用逻辑网络(LN)将数tb的模拟数据从NERSC的计算机传输到我们的本地分析/可视化集群,在模拟执行时,开销可以忽略不计。数据传输实验表明,这种并行数据传输方式比将数据写入本地磁盘后再传输到后处理更有利。我们的算法具有网络感知能力,在实时模拟过程中,可以在从CA到NJ的100 mb链路上传输高达97 mb的数据,在NERSC使用不到5%的CPU开销。该方法是建立仿真工作流和数据管理管道的第一步。
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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