Omnisc'IO: A Grammar-Based Approach to Spatial and Temporal I/O Patterns Prediction
Abstract
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. 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 any HPC application, and uses it to predict when future I/O operations will occur, 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 towards accurate predictions within a couple of iterations only. Its implementation is very efficient both in computation time and memory footprint.
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