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Simplifying reductions

Published: 11 January 2006 Publication History

Abstract

We present optimization techniques for high level equational programs that are generalizations of affine control loops (ACLs). Significant parts of the SpecFP and PerfectClub benchmarks are ACLs. They often contain reductions: associative and commutative operators applied to a collection of values. They also often exhibit reuse: intermediate values computed or used at different index points being identical. We develop various techniques to automatically exploit reuse to simplify the computational complexity of evaluating reductions. Finally, we present an algorithm for the optimal application of such simplifications resulting in an equivalent specification with minimum complexity.

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cover image ACM Conferences
POPL '06: Conference record of the 33rd ACM SIGPLAN-SIGACT symposium on Principles of programming languages
January 2006
432 pages
ISBN:1595930272
DOI:10.1145/1111037
  • cover image ACM SIGPLAN Notices
    ACM SIGPLAN Notices  Volume 41, Issue 1
    Proceedings of the 2006 POPL Conference
    January 2006
    421 pages
    ISSN:0362-1340
    EISSN:1558-1160
    DOI:10.1145/1111320
    Issue’s Table of Contents
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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Publication History

Published: 11 January 2006

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Author Tags

  1. equational programming
  2. incremental computation
  3. loop optimization
  4. polyhedral model
  5. program transformation

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Overall Acceptance Rate 824 of 4,130 submissions, 20%

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  • (2022)Parallelizing Neural Network Models Effectively on GPU by Implementing Reductions AtomicallyProceedings of the International Conference on Parallel Architectures and Compilation Techniques10.1145/3559009.3569656(451-466)Online publication date: 8-Oct-2022
  • (2019)Aggregation of Votes with Multiple Positions on Each IssueACM Transactions on Economics and Computation10.1145/32966757:1(1-25)Online publication date: 25-Jan-2019
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