article

Array regrouping and structure splitting using whole-program reference affinity

Authors:

Maksim Orlovich,

Chen DingAuthors Info & Claims

ACM SIGPLAN Notices, Volume 39, Issue 6

Pages 255 - 266

https://doi.org/10.1145/996893.996872

Published: 09 June 2004 Publication History

Abstract

While the memory of most machines is organized as a hierarchy, program data are laid out in a uniform address space. This paper defines a model of reference affinity, which measures how close a group of data are accessed together in a reference trace. It proves that the model gives a hierarchical partition of program data. At the top is the set of all data with the weakest affinity. At the bottom is each data element with the strongest affinity. Based on the theoretical model, the paper presents k-distance analysis, a practical test for the hierarchical affinity of source-level data. When used for array regrouping and structure splitting, k-distance analysis consistently outperforms data organizations given by the programmer, compiler analysis, frequency profiling, statistical clustering, and all other methods we have tried.

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Index Terms

Array regrouping and structure splitting using whole-program reference affinity
1. Software and its engineering
  1. Software notations and tools
    1. Compilers

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Information

Published In

cover image ACM SIGPLAN Notices

ACM SIGPLAN Notices Volume 39, Issue 6

PLDI '04

May 2004

299 pages

ISSN:0362-1340

EISSN:1558-1160

DOI:10.1145/996893

Issue’s Table of Contents

PLDI '04: Proceedings of the ACM SIGPLAN 2004 conference on Programming language design and implementation
June 2004
310 pages
ISBN:1581138075
DOI:10.1145/996841
General Chair:
William Pugh
University of Maryland, College Park
,
Program Chair:
Craig Chambers
University of Washington

Copyright © 2004 ACM.

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Association for Computing Machinery

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Published: 09 June 2004

Published in SIGPLAN Volume 39, Issue 6

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https://dl.acm.org/doi/10.1145/3710848.3710856
Hu QDing YLiu CLi KLi KZomaya A(2024)CBANA: A Lightweight, Efficient, and Flexible Cache Behavior Analysis FrameworkIEEE Transactions on Computers10.1109/TC.2024.341674773:9(2262-2274)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1109/TC.2024.3416747
Zhai JJin YChen WZheng WZhai JJin YChen WZheng W(2023)Performance Prediction for Scalability AnalysisPerformance Analysis of Parallel Applications for HPC10.1007/978-981-99-4366-1_6(129-161)Online publication date: 19-Jun-2023
https://doi.org/10.1007/978-981-99-4366-1_6
Rahman MArefin MRahman SAhmed AIslam TDhar PKwon O(2022)A Comprehensive Survey on Affinity Analysis, Bibliomining, and Technology Mining: Past, Present, and Future ResearchApplied Sciences10.3390/app1210522712:10(5227)Online publication date: 21-May-2022
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