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Parallelizing Sequential Programs with Statistical Accuracy Tests

Authors:

Sasa Misailovic,

Martin RinardAuthors Info & Claims

ACM Transactions on Embedded Computing Systems (TECS), Volume 12, Issue 2s

Article No.: 88, Pages 1 - 26

https://doi.org/10.1145/2465787.2465790

Published: 01 May 2013 Publication History

Abstract

We present QuickStep, a novel system for parallelizing sequential programs. Unlike standard parallelizing compilers (which are designed to preserve the semantics of the original sequential computation), QuickStep is instead designed to generate (potentially nondeterministic) parallel programs that produce acceptably accurate results acceptably often. The freedom to generate parallel programs whose output may differ (within statistical accuracy bounds) from the output of the sequential program enables a dramatic simplification of the compiler, a dramatic increase in the range of applications that it can parallelize, and a significant expansion in the range of parallel programs that it can legally generate.

Results from our benchmark set of applications show that QuickStep can automatically generate acceptably accurate and efficient parallel programs---the automatically generated parallel versions of five of our six benchmark applications run between 5.0 and 7.8 times faster on eight cores than the original sequential versions. These applications and parallelizations contain features (such as the use of modern object-oriented programming constructs or desirable parallelizations with infrequent but acceptable data races) that place them inherently beyond the reach of standard approaches.

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Tan ZChon YKruse MDoerfert JXu ZHomerding BCampanoni SAugust DAamodt TJerger NSwift M(2023)SPLENDID: Supporting Parallel LLVM-IR Enhanced Natural Decompilation for Interactive DevelopmentProceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 310.1145/3582016.3582058(679-693)Online publication date: 25-Mar-2023
https://dl.acm.org/doi/10.1145/3582016.3582058
Deiana ESuchy BWilkins MHomerding BMcMichen TDunajewski KDinda PHardavellas NCampanoni SDubach CBruening DHardekopf B(2023)Program State Element CharacterizationProceedings of the 21st ACM/IEEE International Symposium on Code Generation and Optimization10.1145/3579990.3580011(199-211)Online publication date: 17-Feb-2023
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Rodrigues GKastensmidt FBosio ARodrigues GKastensmidt FBosio A(2022)An Introduction to the Approximate Computing ParadigmApproximate Computing and its Impact on Accuracy, Reliability and Fault-Tolerance10.1007/978-3-031-15717-2_2(11-22)Online publication date: 17-Nov-2022
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Index Terms

Parallelizing Sequential Programs with Statistical Accuracy Tests
1. Computing methodologies
  1. Parallel computing methodologies
    1. Parallel programming languages
2. Software and its engineering
  1. Software notations and tools
    1. Compilers
    2. General programming languages
      1. Language types
        Parallel programming languages

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Published In

cover image ACM Transactions on Embedded Computing Systems

ACM Transactions on Embedded Computing Systems Volume 12, Issue 2s

Special Section on Probabilistic Embedded Computing

May 2013

269 pages

ISSN:1539-9087

EISSN:1558-3465

DOI:10.1145/2465787

Issue’s Table of Contents

Copyright © 2013 ACM.

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 01 May 2013

Accepted: 01 November 2011

Revised: 01 September 2011

Received: 01 July 2011

Published in TECS Volume 12, Issue 2s

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Cited By

Tan ZChon YKruse MDoerfert JXu ZHomerding BCampanoni SAugust DAamodt TJerger NSwift M(2023)SPLENDID: Supporting Parallel LLVM-IR Enhanced Natural Decompilation for Interactive DevelopmentProceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 310.1145/3582016.3582058(679-693)Online publication date: 25-Mar-2023
https://dl.acm.org/doi/10.1145/3582016.3582058
Deiana ESuchy BWilkins MHomerding BMcMichen TDunajewski KDinda PHardavellas NCampanoni SDubach CBruening DHardekopf B(2023)Program State Element CharacterizationProceedings of the 21st ACM/IEEE International Symposium on Code Generation and Optimization10.1145/3579990.3580011(199-211)Online publication date: 17-Feb-2023
https://dl.acm.org/doi/10.1145/3579990.3580011
Rodrigues GKastensmidt FBosio ARodrigues GKastensmidt FBosio A(2022)An Introduction to the Approximate Computing ParadigmApproximate Computing and its Impact on Accuracy, Reliability and Fault-Tolerance10.1007/978-3-031-15717-2_2(11-22)Online publication date: 17-Nov-2022
https://doi.org/10.1007/978-3-031-15717-2_2
Misailovic S(2022)Accuracy-Aware CompilersApproximate Computing Techniques10.1007/978-3-030-94705-7_7(177-214)Online publication date: 3-Jan-2022
https://doi.org/10.1007/978-3-030-94705-7_7
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Stanley-Marbell PAlaghi ACarbin MDarulova EDolecek LGerstlauer AGillani GJevdjic DMoreau TCacciotti MDaglis AJerger NFalsafi BMisailovic SSampson AZufferey D(2020)Exploiting Errors for EfficiencyACM Computing Surveys10.1145/339489853:3(1-39)Online publication date: 12-Jun-2020
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