GfarmBB xe2x80x94 Gfarm File System for NodeLocal Burst Buffer Burst buffer has become a major component to meet the IO performance requirement of HPC bursty traffic. This paper proposes GfarmBB that is a file system for a burst buffer efficiently exploiting nodelocal storage systems. Although nodelocal storages improve storage performance, they are only available during the job allocation. GfarmBB should have better access and metadata performance while it should be constructed ondemand before the job execution. To improve the read and write performance, it exploits the file descriptor passing and remote direct memory access (RDMA). It improves the metadata performance by omitting the persistency and the redundancy since it is a temporal file system. Using RDMA, writes and reads bandwidth are improved by 1.7x and 2.2x compared with IP over InfiniBand (IPoIB), respectively. It achieves 14 700 operations per second in the directory creation performance, which is 13.4x faster than the fully persistent and redundant case. The construction of GfarmBB takes 0.31 seconds using 2 nodes. IOR benchmark and ARGOTIO application IO benchmark show the scalable performance improvement by exploiting the locality of nodelocal storages. Compared with BeeOND, GfarmBB shows 2.6x and 2.4x better performance in IOR write and read benchmarks, respectively, and it shows 2.5x better performance in ARGOTIO.

Lessons Learned from Optimizing the Sunway Storage System for Higher Application IO Performance It is hard for applications to make full utilization of the peak bandwidth of the storage system in highperformance computers because of IO interferences, storage resource misallocations and complex long IO 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 endtoend performance monitoring and diagnosis tool was developed to understand IO 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 IO forwarding layer and the parallel file system layer. An applicationaware IO forwarding allocation framework was used to address the IO interferences and resource misallocations at the IO forwarding layer. A performanceaware data placement mechanism was proposed to mitigate the impact of IO interferences and performance variations of storage devices in the PFS. Together, applications obtained much better IO performance. During the process, we also proposed a lightweight storage stack to shorten the IO path of applications with N IO pattern. This paper summarizes these studies and presents the lessons learned from the process.