Omnisc'IO a grammar-based approach to spatial and temporal I/O patterns prediction

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 a...

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Published in:Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis pp. 623 - 634
Main Authors: Dorier, Matthieu, Ibrahim, Shadi, Antoniu, Gabriel, Ross, Rob
Format: Conference Proceeding
Language:English
Published: Piscataway, NJ, USA IEEE Press 16.11.2014
IEEE
Series:ACM Conferences
Subjects:
Computer systems organization > Dependable and fault-tolerant systems and networks
Context
Exascale
General and reference > Cross-computing tools and techniques > Performance
Grammar
Hidden Markov models
HPC
I/O
Libraries
Networks > Network performance evaluation
Omnisc'IO
Prediction
Prediction algorithms
Predictive models
Prefetching
Software and its engineering > Software organization and properties > Contextual software domains > Operating systems > Communications management > Input > output
Storage
Theory of computation > Formal languages and automata theory > Formalisms > Rewrite systems
Theory of computation > Formal languages and automata theory > Grammars and context-free languages
grammar
exascale
I/O
prediction
HPC
storage
Omnisc'IO
ISBN:1479955000, 9781479955008
ISSN:2167-4329
Online Access:Get full text
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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. 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.
AbstractList 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.
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.
Author Ibrahim, Shadi
Dorier, Matthieu
Antoniu, Gabriel
Ross, Rob
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  email: rross@mcs.anl.gov
  organization: Argonne National Laboratory, Argonne, IL
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I/O
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HPC
storage
Omnisc'IO
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Snippet The increasing gap between the computation performance of post-petascale machines and the performance of their I/O subsystem has motivated many I/O...
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StartPage 623
SubjectTerms Computer systems organization -- Dependable and fault-tolerant systems and networks
Context
Exascale
General and reference -- Cross-computing tools and techniques -- Performance
Grammar
Hidden Markov models
HPC
I/O
Libraries
Networks -- Network performance evaluation
Omnisc'IO
Prediction
Prediction algorithms
Predictive models
Prefetching
Software and its engineering -- Software organization and properties -- Contextual software domains -- Operating systems -- Communications management -- Input -- output
Storage
Theory of computation -- Formal languages and automata theory -- Formalisms -- Rewrite systems
Theory of computation -- Formal languages and automata theory -- Grammars and context-free languages
Subtitle a grammar-based approach to spatial and temporal I/O patterns prediction
Title Omnisc'IO
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