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Locality-aware Buffer Management: Algorithms Design and Systems Implementation for Data Intensive Applications (A Brief Progress Report)

机译:局部性缓冲区管理:用于数据密集型应用程序的算法设计和系统实现(简要进度报告)

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The speed gap between data processing in CPU and data accessing in disks has reached to an intolerable level, and only become worse as time goes by. This bottleneck has seriously hindered the development of large scale computing systems for data-intensive applications that demand fast accesses to a huge amount of data. Viable and cost-effective solutions to address this problem are to build large memory buffers to cache data for reuse by taking advantage of low price and large capacity of DRAM memory, and to prefetch data for predicted future use by taking advantage of high and idle bandwidths of networks. We are working on four different research projects on locality-aware buffer management for data intensive applications. This report briefly presents the background, motivation, and working progress of our work funded by the NSF NGS program.
机译:CPU中的数据处理与磁盘中的数据访问之间的速度差距已经达到了无法忍受的程度,并且随着时间的流逝而变得越来越严重。这个瓶颈严重阻碍了需要快速访问大量数据的数据密集型应用程序的大规模计算系统的开发。解决此问题的可行且具有成本效益的解决方案是建立大型内存缓冲区,以利用低廉的价格和大容量的DRAM内存来缓存数据以供重用,并通过获取高带宽和空闲带宽来预取数据以供将来预期使用网络。我们正在针对数据密集型应用程序进行有关位置感知缓冲区管理的四个不同的研究项目。本报告简要介绍了由NSF NGS计划资助的工作的背景,动机和工作进展。

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