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Scaling exact multi-objective combinatorial optimization by parallelization

  • Jianmei Guo*
  • , Edward Zulkoski
  • , Rafael Olaechea
  • , Derek Rayside
  • , Krzysztof Czarnecki
  • , Sven Apel
  • , Joanne M. Atlee
  • *此作品的通讯作者
  • University of Waterloo
  • University of Passau

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Multi-Objective Combinatorial Optimization (MOCO) is fundamental to the development and optimization of software systems. We propose five novel parallel algorithms for solving MOCO problems exactly and efficiently. Our algorithms rely on off-the-shelf solvers to search for exact Pareto-optimal solutions, and they parallelize the search via collaborative communication, divide-and-conquer, or both. We demonstrate the feasibility and performance of our algorithms by experiments on three case studies of software-system designs. A key finding is that one algorithm, which we call FS-GIA, achieves substantial (even super-linear) speedups that scale well up to 64 cores. Furthermore, we analyze the performance bottlenecks and opportunities of our parallel algorithms, which facilitates further research on exact, parallel MOCO.

源语言英语
主期刊名ASE 2014 - Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering
出版商Association for Computing Machinery, Inc
409-420
页数12
ISBN(电子版)9781450330138
DOI
出版状态已出版 - 2014
已对外发布
活动29th ACM/IEEE International Conference on Automated Software Engineering, ASE 2014 - Vasteras, 瑞典
期限: 15 9月 201419 9月 2014

出版系列

姓名ASE 2014 - Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering

会议

会议29th ACM/IEEE International Conference on Automated Software Engineering, ASE 2014
国家/地区瑞典
Vasteras
时期15/09/1419/09/14

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