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A scalable method for run-time loop parallelization

Authors:

Lawrence Rauchwerger,

Nancy M. Amato,

David A. PaduaAuthors Info & Claims

International Journal of Parallel Programming, Volume 23, Issue 6

Pages 537 - 576

https://doi.org/10.1007/BF02577866

Published: 01 December 1995 Publication History

Abstract

No abstract available.

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Pawlak WHlava MMetaksov MOancea CLow TGibbons J(2021)Acceleration of lattice models for pricing portfolios of fixed-income derivativesProceedings of the 7th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming10.1145/3460944.3464309(27-38)Online publication date: 17-Jun-2021
https://dl.acm.org/doi/10.1145/3460944.3464309
Wang QZheng LZhao JLiao XJin HXue J(2020)A Conflict-free Scheduler for High-performance Graph Processing on Multi-pipeline FPGAsACM Transactions on Architecture and Code Optimization10.1145/339052317:2(1-26)Online publication date: 29-May-2020
https://dl.acm.org/doi/10.1145/3390523
Mohammadi MYuki TCheshmi KDavis EHall MDehnavi MNandy POlschanowsky CVenkat AStrout MMcKinley KFisher K(2019)Sparse computation data dependence simplification for efficient compiler-generated inspectorsProceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation10.1145/3314221.3314646(594-609)Online publication date: 8-Jun-2019
https://dl.acm.org/doi/10.1145/3314221.3314646
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Advanced loop parallelization theory and techniques
Run-time data-flow analysis
Abstract
Parallelizing compilers have made great progress in recent years. However, there still remains a gap between the current ability of parallelizing compilers and their final goals. In order to achieve the maximum parallelism, run-time techniques ...
The LRPD Test: Speculative Run-Time Parallelization of Loops with Privatization and Reduction Parallelization

Current parallelizing compilers cannot identify a significant fraction of parallelizable loops because they have complex or statically insufficiently defined access patterns. As parallelizable loops arise frequently in practice, we advocate a novel ...

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Published In

cover image International Journal of Parallel Programming

International Journal of Parallel Programming Volume 23, Issue 6

Dec. 1995

76 pages

ISSN:0885-7458

Editors:
Utpal Banerjee
Intel Corp., Santa Clara, CA
,
David Gelernter
Yale Univ., New Haven, CT
,
Alex Nicolau
Univ. of California-Irvine, Irvine
,
David Padua
Univ. of Illinois at Urbana-Champaign, Urbana

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Kluwer Academic Publishers

United States

Publication History

Published: 01 December 1995

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Pawlak WHlava MMetaksov MOancea CLow TGibbons J(2021)Acceleration of lattice models for pricing portfolios of fixed-income derivativesProceedings of the 7th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming10.1145/3460944.3464309(27-38)Online publication date: 17-Jun-2021
https://dl.acm.org/doi/10.1145/3460944.3464309
Wang QZheng LZhao JLiao XJin HXue J(2020)A Conflict-free Scheduler for High-performance Graph Processing on Multi-pipeline FPGAsACM Transactions on Architecture and Code Optimization10.1145/339052317:2(1-26)Online publication date: 29-May-2020
https://dl.acm.org/doi/10.1145/3390523
Mohammadi MYuki TCheshmi KDavis EHall MDehnavi MNandy POlschanowsky CVenkat AStrout MMcKinley KFisher K(2019)Sparse computation data dependence simplification for efficient compiler-generated inspectorsProceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation10.1145/3314221.3314646(594-609)Online publication date: 8-Jun-2019
https://dl.acm.org/doi/10.1145/3314221.3314646
Xu YLee IAgrawal K(2018)Efficient parallel determinacy race detection for two-dimensional dagsACM SIGPLAN Notices10.1145/3200691.317851553:1(368-380)Online publication date: 10-Feb-2018
https://dl.acm.org/doi/10.1145/3200691.3178515
Xu YLee IAgrawal KKrall AGross T(2018)Efficient parallel determinacy race detection for two-dimensional dagsProceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming10.1145/3178487.3178515(368-380)Online publication date: 10-Feb-2018
https://dl.acm.org/doi/10.1145/3178487.3178515
Khatami ZTroska LKaiser HRamanujam JSerio A(2017)HPX Smart ExecutorsProceedings of the Third International Workshop on Extreme Scale Programming Models and Middleware10.1145/3152041.3152084(1-8)Online publication date: 12-Nov-2017
https://dl.acm.org/doi/10.1145/3152041.3152084
Venkat AMohammadi MPark JRong HBarik RStrout MHall MWest J(2016)Automating wavefront parallelization for sparse matrix computationsProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.5555/3014904.3014959(1-12)Online publication date: 13-Nov-2016
https://dl.acm.org/doi/10.5555/3014904.3014959
Huang JPrabhu PJablin TGhosh SApostolakis SLee JAugust DZaks AMendelson BRauchwerger LHwu W(2016)Speculatively Exploiting Cross-Invocation ParallelismProceedings of the 2016 International Conference on Parallel Architectures and Compilation10.1145/2967938.2967959(207-221)Online publication date: 11-Sep-2016
https://dl.acm.org/doi/10.1145/2967938.2967959
Ravishankar MDathathri RElango VPouchet LRamanujam JRountev ASadayappan P(2015)Distributed memory code generation for mixed Irregular/Regular computationsACM SIGPLAN Notices10.1145/2858788.268851550:8(65-75)Online publication date: 24-Jan-2015
https://dl.acm.org/doi/10.1145/2858788.2688515
Ravishankar MDathathri RElango VPouchet LRamanujam JRountev ASadayappan PCohen AGrove D(2015)Distributed memory code generation for mixed Irregular/Regular computationsProceedings of the 20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming10.1145/2688500.2688515(65-75)Online publication date: 24-Jan-2015
https://dl.acm.org/doi/10.1145/2688500.2688515
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Cited By

Index Terms

Recommendations

Advanced loop parallelization theory and techniques

Run-time data-flow analysis

The LRPD Test: Speculative Run-Time Parallelization of Loops with Privatization and Reduction Parallelization

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