Jitter-free co-processing on a prototype exascale storage stack
Jitter-free co-processing on a prototype exascale storage stack
复制标题
原型亿亿级存储堆栈上的无抖动协同处理
DOI：
10.1109/msst.2012.6232382
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
J. Woodring
中科院分区：
文献类型：
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作者：
John Bent;Sorin Faibish;J. Ahrens;G. Grider;J. Patchett;P. Tzelnic;J. Woodring
在千万亿级时代，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相当同质。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 定向到相对较小的 IO 节点集。这些节点通过辅助存储网络将请求转发到基于主轴的并行文件系统。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旋转速度的增长，磁盘的容量成本效益越来越高，但带宽成本效益却越来越低。幸运的是，固态设备等新存储介质正在填补这一空白。尽管就容量而言不具有成本效益，但就性能而言却如此。这表明百亿亿级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。这个新存储层自然可以放置在三个位置：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 工作负载的适当位置，并展示了我们相应构建的原型系统的结果。运行计算模拟和可视化流程后，我们发现我们的原型系统将总完成时间缩短了 30%。
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%.