Omnisc'IO: A Grammar-Based Approach to Spatial and Temporal I/O Patterns Prediction - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2014

Omnisc'IO: A Grammar-Based Approach to Spatial and Temporal I/O Patterns Prediction

Shadi Ibrahim
Gabriel Antoniu
Robert Ross
MCS

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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Dates and versions

hal-01025670 , version 1 (24-07-2014)

Identifiers

  • HAL Id : hal-01025670 , version 1

Cite

Matthieu Dorier, Shadi Ibrahim, Gabriel Antoniu, Robert Ross. Omnisc'IO: A Grammar-Based Approach to Spatial and Temporal I/O Patterns Prediction. SC14 - International Conference for High Performance Computing, Networking, Storage and Analysis, IEEE, ACM, Nov 2014, New Orleans, United States. ⟨hal-01025670⟩
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