I/O Optimizations Based on Workload Characteristics for Parallel File Systems

Abstract

Parallel file systems usually provide a unified storage solution, which fails to meet specific application needs. In this paper, we propose an extended file handle scheme to address this problem. It allows the file systems to specify optimizations for individual file or directory based on workload characteristics. One case study shows that our proposed approach improves the aggregate throughput of large files and small files by up to 5% and 30%, respectively. To further improve the access performance of small files in parallel file systems, we also propose a new metadata-based small file optimization method. The experimental results show that the aggregate throughput of small files can be effectively improved through our method.