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

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 I/O pattern. This paper summarizes these studies and presents the lessons learned from the process.

Publication
Journal of Computer Science and Technology 2020, Vol. 35, Issue 1, pp. 47-60.