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Regular Paper

Lessons Learned from Optimizing the Sunway Storage System for Higher Application I/O Performance

Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
Chinese Academy of Engineering, Beijing 100088, China
National Supercomputing Center in Wuxi, Wuxi 214100, China
School of Software, Shandong University, Jinan 250101, China
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Abstract

It is hard for applications to make full utilization of the peak bandwidth of the storage system in highperformance computers because of I/O interferences, storage resource misallocations and complex long I/O paths. We performed several studies to bridge this gap in the Sunway storage system, which serves the supercomputer Sunway TaihuLight. To locate these issues and connections between them, an end-to-end performance monitoring and diagnosis tool was developed to understand I/O behaviors of applications and the system. With the help of the tool, we were about to find out the root causes of such performance barriers at the I/O forwarding layer and the parallel file system layer. An application-aware I/O forwarding allocation framework was used to address the I/O interferences and resource misallocations at the I/O forwarding layer. A performance-aware data placement mechanism was proposed to mitigate the impact of I/O interferences and performance variations of storage devices in the PFS. Together, applications obtained much better I/O performance. During the process, we also proposed a lightweight storage stack to shorten the I/O path of applications with N-N I/O pattern. This paper summarizes these studies and presents the lessons learned from the process.

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Journal of Computer Science and Technology
Pages 47-60

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Cite this article:
Chen Q, Chen K, Chen Z-N, et al. Lessons Learned from Optimizing the Sunway Storage System for Higher Application I/O Performance. Journal of Computer Science and Technology, 2020, 35(1): 47-60. https://doi.org/10.1007/s11390-020-9798-5

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Received: 30 July 2019
Revised: 28 November 2019
Published: 17 January 2020
©Institute of Computing Technology, Chinese Academy of Sciences 2020