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A practical approach to reconciling availability, performance, and capacity in provisioning extreme-scale storage systems

机译:调配极端规模存储系统时的可用性,性能和容量的实用方法

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The increasing data demands from high-performance computing applications significantly accelerate the capacity, capability and reliability requirements of storage systems. As systems scale, component failures and repair times increase, significantly impacting data availability. A wide array of decision points must be balanced in designing such systems. We propose a systematic approach that balances and optimizes both initial and continuous spare provisioning based on a detailed investigation of the anatomy and field failure data analysis of extreme-scale storage systems. We consider the component failure characteristics and its cost and impact at the system level simultaneously. We build a tool to evaluate different provisioning schemes, and the results demonstrate that our optimized provisioning can reduce the duration of data unavailability by as much as 52% under a fixed budget. We also observe that non-disk components have much higher failure rates than disks, and warrant careful considerations in the overall provisioning process.
机译:高性能计算应用程序对数据的不断增长的需求极大地加快了存储系统对容量,容量和可靠性的要求。随着系统的扩展,组件故障和维修时间会增加,从而极大地影响数据可用性。在设计此类系统时,必须平衡各种决策点。我们基于对超大规模存储系统的解剖结构和现场故障数据分析的详细调查,提出了一种平衡和优化初始和连续备用资源调配的系统方法。我们同时考虑组件故障特征及其成本和对系统的影响。我们构建了一种工具来评估不同的配置方案,结果表明,在固定预算下,我们优化的配置可以将数据不可用的持续时间减少多达52%。我们还观察到非磁盘组件的故障率比磁盘高得多,因此在整个预配过程中需要仔细考虑。

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