exploiting global input/output access pattern classification
Parallel input/output systems attempt to alleviate the performance bottleneck that affects many input/output intensive applications. In such systems, an understanding of the application access pattern, especially how requests from multiple processors for different file regions are logically related, is important for optimizing file system performance. We propose a method for automatically classifying these global access patterns and using these global classifications to select and tune file system policies to improve input/output performance. We demonstrate this approach on benchmarks and scientific applications using global classification to automatically select appropriate underlying Intel PFS input/output modes and server buffering strategies.
global input access pattern classification parallel systems performance affect applications understandability processor region optimality file systems method classifiation select policy demonstrate benchmark server buffers strategies