Affiliation:
1. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences Shenzhen 518055 China
2. University of Chinese Academy of Sciences Beijing 100049 China
3. University of Science and Technology of China Hefei 230026 China
4. Shenzhen Virtual Clusters Information Technology Co., Ltd Shenzhen 518057 China
Abstract
SummaryAs the capacity of Solid‐State Drives (SSDs) is constantly being optimised and boosted with gradually reduced cost, the SSD cluster is now widely deployed as part of the hybrid storage system in various scenarios such as cloud computing and big data processing. However, despite its rapid developments, the performance of the SSD cluster remains largely under‐investigated, leaving its sub‐optimal applications in reality. To address this issue, in this paper we conduct extensive empirical studies for a comprehensive understanding of the SSD cluster in diverse settings. To this end, we configure a real SSD cluster and gather the generated trace data based on some often‐used benchmarks, then adopt analytical methods to analyse the performance of the SSD cluster with different configurations. In particular, regression models are built to provide better performance predictability under broader configurations, and the correlations between influential factors and performance metrics with respect to different numbers of nodes are investigated, which reveal the high scalability of the SSD cluster. Additionally, the cluster's network bandwidth is inspected to explain the performance bottleneck. Finally, the knowledge gained is summarised to benefit the SSD cluster deployment in practice.
Subject
Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software
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