Kelefouras, V and Djemame, K orcid.org/0000-0001-5811-5263 (2018) A methodology for efficient code optimizations and memory management. In: CF '18 Proceedings of the 15th ACM International Conference on Computing Frontiers. ACM International Conference on Computing Frontiers 2018, 08-10 May 2018, Ischia, Italy. ACM , pp. 105-112. ISBN 978-1-4503-5761-6
Abstract
The key to optimizing software is the correct choice, order as well parameters of optimizations-transformations, which has remained an open problem in compilation research for decades for various reasons. First, most of the compilation subproblems-transformations are interdependent and thus addressing them separately is not effective. Second, it is very hard to couple the transformation parameters to the processor architecture (e.g., cache size and associativity) and algorithm characteristics (e.g. data reuse); therefore compiler designers and researchers either do not take them into account at all or do it partly. Third, the search space (all different transformation parameters) is very large and thus searching is impractical.
In this paper, the above problems are addressed for data dominant affine loop kernels, delivering significant contributions. A novel methodology is presented that takes as input the underlying architecture details and algorithm characteristics and outputs the near-optimum parameters of six code optimizations in terms of either L1,L2,DDR accesses, execution time or energy consumption. The proposed methodology has been evaluated to both embedded and general purpose processors and for 6 well known algorithms, achieving high speedup as well energy consumption gain values over gcc compiler, hand written optimized code and Polly.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2018, ACM. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in 'CF '18 Proceedings of the 15th ACM International Conference on Computing Frontiers', https://doi.org/10.1145/3203217.3203274 |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number EU - European Union 687584 |
Depositing User: | Symplectic Publications |
Date Deposited: | 11 May 2018 12:53 |
Last Modified: | 09 Aug 2018 21:32 |
Published Version: | http://computingfrontiers.org/2018/ |
Status: | Published |
Publisher: | ACM |
Identification Number: | 10.1145/3203217.3203274 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:130673 |