Data Sieving and Collective I/O in ROMIO

The I/O access patterns of parallel programs often consist of accesses to a large number of small, noncontiguous pieces of data. If an application's I/O needs are met by making many small, distinct I/O requests, however, the I/O performance degrades drastically. To avoid this problem, MPI-IO allows users to access a noncontiguous data set with a single I/O function call. This feature provides MPI-IO implementations an opportunity to optimize data access. We describe how our MPI-IO implementation, ROMIO, delivers high performance in the presence of noncontiguous requests. We explain in detail the two key optimiza-tions ROMIO performs: data sieving for noncontiguous requests from one process and collective I/O for noncontiguous requests from multiple processes. We describe how one can implement these optimizations portably on multiple machines and le systems, con-trol their memory requirements, and also achieve high performance. We demonstrate the performance and portability with performance results for three applications|an astrophysics-application template (DIST3D), the NAS BTIO benchmark, and an un