Article

Multi-slicing: a compiler-supported parallel approach to data dependence profiling

Authors:

Zhiyuan LiAuthors Info & Claims

ISSTA 2012: Proceedings of the 2012 International Symposium on Software Testing and Analysis

Pages 23 - 33

https://doi.org/10.1145/2338965.2336756

Published: 15 July 2012 Publication History

Abstract

Retrofitting existing software for the increasingly dominant multicore microprocessors has a strong appeal from the economic point of view. One of the key issues in such an effort is to fully understand the data dependences in the existing software. Unfortunately, current compilers have quite limited ability to analyze data dependences. Therefore, execution-driven data dependence profiling has gained significant interest because it can resolve memory access ambiguity exactly during program execution, which allows data dependences to be analyzed exactly. Although such dependence profiling is valid for specific inputs only, the insight it provides can be highly valuable to software engineers in their parallelization effort. On the other hand, dependence profiling itself can take tremendous memory and machine time. In this paper, we propose a novel dependence profiling method which, with the support of several new compiler and runtime techniques, partitions the profiling task into many independent slices, each requiring significantly less memory. Different slices can be profiled in parallel, producing subgraphs which are eventually combined automatically into the complete data dependence graph by the compiler. The slices can be extracted with different degrees of granularity. Experiments show that, for several well-known benchmark programs, our parallel scheme shortens the profiling time by a few orders of magnitude.

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Cited By

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
Abbas MSoliman MRabia SKimura KEl-Mahdy A(2022)Accelerating Data Dependence Profiling Through Abstract Interpretation of Loop InstructionsIEEE Access10.1109/ACCESS.2022.316072910(31626-31640)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3160729
Vasiladiotis CLozano RCole MFranke BLee J(2021)Loop parallelization using dynamic commutativity analysisProceedings of the 2021 IEEE/ACM International Symposium on Code Generation and Optimization10.1109/CGO51591.2021.9370319(150-161)Online publication date: 27-Feb-2021
https://dl.acm.org/doi/10.1109/CGO51591.2021.9370319
Show More Cited By

Index Terms

Multi-slicing: a compiler-supported parallel approach to data dependence profiling
1. Software and its engineering
  1. Software notations and tools
    1. Compilers
2. Theory of computation
  1. Semantics and reasoning
    1. Program semantics

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cover image ACM Conferences

ISSTA 2012: Proceedings of the 2012 International Symposium on Software Testing and Analysis

July 2012

341 pages

ISBN:9781450314541

DOI:10.1145/2338965

General Chair:
Mats Heimdahl,
Program Chair:
Zhendong Su

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 15 July 2012

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July 15 - 20, 2012

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Overall Acceptance Rate 58 of 213 submissions, 27%

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Cited By

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
Abbas MSoliman MRabia SKimura KEl-Mahdy A(2022)Accelerating Data Dependence Profiling Through Abstract Interpretation of Loop InstructionsIEEE Access10.1109/ACCESS.2022.316072910(31626-31640)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3160729
Vasiladiotis CLozano RCole MFranke BLee J(2021)Loop parallelization using dynamic commutativity analysisProceedings of the 2021 IEEE/ACM International Symposium on Code Generation and Optimization10.1109/CGO51591.2021.9370319(150-161)Online publication date: 27-Feb-2021
https://dl.acm.org/doi/10.1109/CGO51591.2021.9370319
Abbas MOmar REl-Mahdy ARohou E(2020)Approximate Data Dependence Profiling Based on Abstract Interval and Congruent DomainsArchitecture of Computing Systems – ARCS 202010.1007/978-3-030-52794-5_1(3-16)Online publication date: 9-Jul-2020
https://doi.org/10.1007/978-3-030-52794-5_1
Abbas MEl-Mahdy A(2016)Approximate Data Dependence Graph Generation Using Adaptive Sampling2016 45th International Conference on Parallel Processing Workshops (ICPPW)10.1109/ICPPW.2016.54(329-337)Online publication date: Aug-2016
https://doi.org/10.1109/ICPPW.2016.54
Li ZJannesari AWolf F(2015)An Efficient Data-Dependence Profiler for Sequential and Parallel ProgramsProceedings of the 2015 IEEE International Parallel and Distributed Processing Symposium10.1109/IPDPS.2015.41(484-493)Online publication date: 25-May-2015
https://dl.acm.org/doi/10.1109/IPDPS.2015.41
Li ZBeaumont MJannesari AWolf F(2015)Fast Data-Dependence Profiling by Skipping Repeatedly Executed Memory OperationsAlgorithms and Architectures for Parallel Processing10.1007/978-3-319-27140-8_40(583-596)Online publication date: 16-Dec-2015
https://doi.org/10.1007/978-3-319-27140-8_40
Edler von Koch TFranke B(2014)Variability of data dependences and control flow2014 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)10.1109/ISPASS.2014.6844482(180-189)Online publication date: Mar-2014
https://doi.org/10.1109/ISPASS.2014.6844482
Yu HKo HLi Z(2013)General data structure expansion for multi-threadingACM SIGPLAN Notices10.1145/2499370.246218248:6(243-252)Online publication date: 16-Jun-2013
https://dl.acm.org/doi/10.1145/2499370.2462182
Yu HKo HLi ZBoehm HFlanagan C(2013)General data structure expansion for multi-threadingProceedings of the 34th ACM SIGPLAN Conference on Programming Language Design and Implementation10.1145/2491956.2462182(243-252)Online publication date: 16-Jun-2013
https://dl.acm.org/doi/10.1145/2491956.2462182
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