research-article

Adaptive runtime selection of parallel schedules in the polytope model

Authors:

Benoît Pradelle,

Philippe Clauss,

Vincent LoechnerAuthors Info & Claims

HPC '11: Proceedings of the 19th High Performance Computing Symposia

Pages 81 - 88

Published: 03 April 2011 Publication History

Abstract

There is often no unique version of a program that provides the best performance in all circumstances. Compilers should rely on an adaptive runtime decision to choose which optimizing and parallelizing transformations will lead to the best performance in any execution context. We present a new adaptive framework solving two drawbacks of existing methods: it is effective since the very first execution, and it handles slight variations of input data shape and size.

In our proposal, different code versions of parallel loop nests are statically generated by the compiler. At install time, each version is profiled in different execution contexts. At runtime, the execution time of each code version is predicted using the profiling results, the current input data shape and the number of available processor cores. The predicted best version is then run.

Our framework handles several versions of possibly tiled parallel loops, using the polytope model for both the profiling and the dynamic selection phases. We show on several benchmark programs that our runtime system selects one of the most efficient version with a very low runtime overhead. This quick and efficient selection leads to speedups compared to the usage of a unique version in every execution context.

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Cited By

Doerfert JGrosser THack SReddi VSmith ATang L(2017)Optimistic loop optimizationProceedings of the 2017 International Symposium on Code Generation and Optimization10.5555/3049832.3049864(292-304)Online publication date: 4-Feb-2017
https://dl.acm.org/doi/10.5555/3049832.3049864
Moll SDoerfert JHack SZaks AHermenegildo M(2016)Input space splitting for OpenCLProceedings of the 25th International Conference on Compiler Construction10.1145/2892208.2892217(251-260)Online publication date: 17-Mar-2016
https://dl.acm.org/doi/10.1145/2892208.2892217
Jimborean AMastrangelo LLoechner VClauss P(2012)VMADProceedings of the 21st international conference on Compiler Construction10.1007/978-3-642-28652-0_12(220-239)Online publication date: 24-Mar-2012
https://dl.acm.org/doi/10.1007/978-3-642-28652-0_12

Index Terms

Adaptive runtime selection of parallel schedules in the polytope model
1. Applied computing
  1. Life and medical sciences
2. Computing methodologies
  1. Modeling and simulation
    1. Simulation support systems

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Information

Published In

cover image ACM Other conferences

HPC '11: Proceedings of the 19th High Performance Computing Symposia

April 2011

193 pages

General Chairs:
Layne T. Watson
Polytechnic Institute and State University
,
Gary Howell,
Program Chairs:
William I. Thacker,
Steven Seidel

Sponsors

SCS: Society for Modeling and Simulation International

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SIGSIM: ACM Special Interest Group on Simulation and Modeling

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Society for Computer Simulation International

San Diego, CA, United States

Publication History

Published: 03 April 2011

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SpringSim '11

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SCS

SpringSim '11: 2011 Spring Simulation Multi-conference

April 3 - 7, 2011

Massachusetts, Boston

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Cited By

Doerfert JGrosser THack SReddi VSmith ATang L(2017)Optimistic loop optimizationProceedings of the 2017 International Symposium on Code Generation and Optimization10.5555/3049832.3049864(292-304)Online publication date: 4-Feb-2017
https://dl.acm.org/doi/10.5555/3049832.3049864
Moll SDoerfert JHack SZaks AHermenegildo M(2016)Input space splitting for OpenCLProceedings of the 25th International Conference on Compiler Construction10.1145/2892208.2892217(251-260)Online publication date: 17-Mar-2016
https://dl.acm.org/doi/10.1145/2892208.2892217
Jimborean AMastrangelo LLoechner VClauss P(2012)VMADProceedings of the 21st international conference on Compiler Construction10.1007/978-3-642-28652-0_12(220-239)Online publication date: 24-Mar-2012
https://dl.acm.org/doi/10.1007/978-3-642-28652-0_12

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