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An ILP-Based Approach to Locality Optimization

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Languages and Compilers for High Performance Computing (LCPC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3602))

Abstract

One of the most important factors that determine performance of data-intensive applications is data locality. A program with high data locality makes better use of fast, on-chip memories and can avoid large main memory latencies. Although previous compiler research investigated numerous techniques for enhancing locality, we lack of formal techniques, against which the existing heuristics can be compared. Motivated by this observation, this paper presents a fresh look at locality optimization based on integer linear programming (ILP). We formulate the conditions for data locality, and present a system of constraints whose solution gives optimal computation re-ordering and data-to-memory assignment under our objective function and cost model. Our experimental results using three data-intensive applications clearly indicate that the ILP-based approach generates very good results and outperforms a previously proposed heuristic solution to locality.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, 16802, USA

    Guilin Chen, Ozcan Ozturk & Mahmut Kandemir

Authors
  1. Guilin Chen
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  2. Ozcan Ozturk
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  3. Mahmut Kandemir
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Editor information

Editors and Affiliations

  1. School of ECE, Purdue University, 47907, West Lafayette, IN

    Rudolf Eigenmann

  2. Department of Computer Science, Purdue University, 47906, West Lafayette, IN, USA

    Zhiyuan Li

  3. School of Electrical and Computer Engineering, Purdue University, 47907, West Lafayette, IN, USA

    Samuel P. Midkiff

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© 2005 Springer-Verlag Berlin Heidelberg

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Chen, G., Ozturk, O., Kandemir, M. (2005). An ILP-Based Approach to Locality Optimization. In: Eigenmann, R., Li, Z., Midkiff, S.P. (eds) Languages and Compilers for High Performance Computing. LCPC 2004. Lecture Notes in Computer Science, vol 3602. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11532378_12

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  • DOI: https://doi.org/10.1007/11532378_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28009-5

  • Online ISBN: 978-3-540-31813-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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