在百亿亿级存储堆栈原型上的无抖动协同处理

John Bent, S. Faibish, J. Ahrens, G. Grider, J. Patchett, P. Tzelnic, J. Woodring
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引用次数: 52

摘要

在千兆级时代,超大规模高性能计算社区使用的存储堆栈在各个站点之间是相当一致的。在堆栈的计算边缘,文件系统客户端或IO转发服务通过互连网络将IO直接发送到相对较小的IO节点集。这些节点通过二级存储网络将请求转发到基于轴的并行文件系统。不幸的是,这种架构在百亿亿次时代将变得不可行。随着磁盘密度的增长继续超过其转速的增长,磁盘在容量方面的成本效益越来越高,但在带宽方面的成本效益却越来越低。幸运的是,固态设备等新的存储介质正在填补这一空白;尽管在容量方面不具有成本效益,但在性能方面却是如此。这表明exascale的存储堆栈将在计算节点和并行文件系统之间合并固态存储。有三个自然的位置可以放置这个新的存储层:计算节点、IO节点或并行文件系统。在本文中,我们认为IO节点是HPC工作负载的合适位置,并展示了我们相应地构建的原型系统的结果。通过运行计算模拟和可视化管道,我们发现我们的原型系统将总完成时间缩短了30%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Jitter-free co-processing on a prototype exascale storage stack
In the petascale era, the storage stack used by the extreme scale high performance computing community is fairly homogeneous across sites. On the compute edge of the stack, file system clients or IO forwarding services direct IO over an interconnect network to a relatively small set of IO nodes. These nodes forward the requests over a secondary storage network to a spindle-based parallel file system. Unfortunately, this architecture will become unviable in the exascale era. As the density growth of disks continues to outpace increases in their rotational speeds, disks are becoming increasingly cost-effective for capacity but decreasingly so for bandwidth. Fortunately, new storage media such as solid state devices are filling this gap; although not cost-effective for capacity, they are so for performance. This suggests that the storage stack at exascale will incorporate solid state storage between the compute nodes and the parallel file systems. There are three natural places into which to position this new storage layer: within the compute nodes, the IO nodes, or the parallel file system. In this paper, we argue that the IO nodes are the appropriate location for HPC workloads and show results from a prototype system that we have built accordingly. Running a pipeline of computational simulation and visualization, we show that our prototype system reduces total time to completion by up to 30%.
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