Omnisc'IO: a grammar-based approach to spatial and temporal I/O patterns prediction - Dorier, Matthieu; Ibrahim, Shadi; Antoniu, Gabriel; Ross, Rob (Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, 2014)
The increasing gap between the computation performance of post-petascale machines and the performance of their I/O subsystem has motivated many I/O optimizations including prefetching, caching, and scheduling techniques. In order to further improve these techniques, modeling and predicting spatial and temporal I/O patterns of HPC applications as they run has became crucial. In this paper we present Omnisc'IO, an approach that builds a grammar-based model of the I/O behavior of HPC applications and uses it to predict when future I/O operations will occur, and where and how much data will be accessed. Omnisc'IO is transparently integrated into the POSIX and MPI I/O stacks and does not require any modification in applications or higher-level I/O libraries. It works without any prior knowledge of the application and converges to accurate predictions within a couple of iterations only. Its implementation is efficient in both computation time and memory footprint.