Disk I/O on high-end computing machines continues to be a significant performance bottleneck. Parallel file systems have been developed to improve parallel I/O performance. However, most of these methods are application dependent and their performance varies largely from application to application. The performance of parallel I/O can be improved with better understanding of I/O access characteristics at both client and file-server side. There is a great need for research into next-generation intelligent and application-specific I/O architectures to meet the demand of highend computing. We propose a dynamic application-specific I/O architecture that tailors various parallel I/O optimizations based on I/O characteristics of applications. This architecture is dynamic in the sense that its underlying optimization strategies are able to adapt to the variations in different applications for best performance. The proposed research is twofold: 1) understanding I/O behavior, 2) developing application-specific optimizations for data layout, prefetching, and caching to form an integrated application-specific I/O architecture. Several technical hurdles have been identified, which include I/O access signature, compiler analysis, global-aware coordinated caching, collective prefetching, data layout optimization and distribution strategies. Solutions are proposed and detailed plans are provided to test these newly proposed solutions and techniques under the PVFS2 parallel file system.
