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.

With the rapid development of supercomputers, the scale and complexity are ever increasing, and the reliability and resilience are faced with larger challenges. There are many important technologies in fault tolerance, such as proactive failure avoidance technologies based on fault prediction, reactive fault tolerance based on checkpoint, and scheduling technologies to improve reliability. Both qualitative and quantitative descriptions on characteristics of system faults are very critical for these technologies. This study analyzes the source of failures on two typical petascale supercomputers called Sunway BlueLight (based on multi-core CPUs) and Sunway TaihuLight (based on heterogeneous manycore CPUs). It uncovers some interesting fault characteristics and finds unknown correlation relationship among main components’ faults. Finally the paper analyzes the failure time of the two supercomputers in various grains of resource and different time spans, and builds a uniform multi-dimensional failure time model for petascale supercomputers.