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SCAF: a speculation-aware collaborative dependence analysis framework

Authors:

Sotiris Apostolakis,

Simone Campanoni,

David I. AugustAuthors Info & Claims

PLDI 2020: Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation

Pages 638 - 654

https://doi.org/10.1145/3385412.3386028

Published: 11 June 2020 Publication History

Abstract

Program analysis determines the potential dataflow and control flow relationships among instructions so that compiler optimizations can respect these relationships to transform code correctly. Since many of these relationships rarely or never occur, speculative optimizations assert they do not exist while optimizing the code. To preserve correctness, speculative optimizations add validation checks to activate recovery code when these assertions prove untrue. This approach results in many missed opportunities because program analysis and thus other optimizations remain unaware of the full impact of these dynamically-enforced speculative assertions. To address this problem, this paper presents SCAF, a Speculation-aware Collaborative dependence Analysis Framework. SCAF learns of available speculative assertions via profiling, computes their full impact on memory dependence analysis, and makes this resulting information available for all code optimizations. SCAF is modular (adding new analysis modules is easy) and collaborative (modules cooperate to produce a result more precise than the confluence of all individual results). Relative to the best prior speculation-aware dependence analysis technique, by computing the full impact of speculation on memory dependence analysis, SCAF dramatically reduces the need for expensive-to-validate memory speculation in the hot loops of all 16 evaluated C/C++ SPEC benchmarks.

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Xu ZChon YSu YTan ZApostolakis SCampanoni SAugust D(2024)PROMPT: A Fast and Extensible Memory Profiling FrameworkProceedings of the ACM on Programming Languages10.1145/36498278:OOPSLA1(449-473)Online publication date: 29-Apr-2024
https://dl.acm.org/doi/10.1145/3649827
McMichen TGreiner NZhong PSossai FPatel ACampanoni SGrosser TDubach CSteuwer MXue JOttoni GQuintão Pereira F(2024)Representing Data Collections in an SSA FormProceedings of the 2024 IEEE/ACM International Symposium on Code Generation and Optimization10.1109/CGO57630.2024.10444817(308-321)Online publication date: 2-Mar-2024
https://dl.acm.org/doi/10.1109/CGO57630.2024.10444817
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
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Index Terms

SCAF: a speculation-aware collaborative dependence analysis framework
1. Software and its engineering
  1. Software notations and tools
    1. Compilers
  2. Software organization and properties
    1. Software functional properties
      1. Formal methods
        Automated static analysis
        Dynamic analysis

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cover image ACM Conferences

PLDI 2020: Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation

June 2020

1174 pages

ISBN:9781450376136

DOI:10.1145/3385412

General Chair:
Alastair F. Donaldson
Imperial College London, UK
,
Program Chair:
Emina Torlak
University of Washington, USA

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https://dl.acm.org/doi/10.1145/3649827
McMichen TGreiner NZhong PSossai FPatel ACampanoni SGrosser TDubach CSteuwer MXue JOttoni GQuintão Pereira F(2024)Representing Data Collections in an SSA FormProceedings of the 2024 IEEE/ACM International Symposium on Code Generation and Optimization10.1109/CGO57630.2024.10444817(308-321)Online publication date: 2-Mar-2024
https://dl.acm.org/doi/10.1109/CGO57630.2024.10444817
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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