论文标题
Yewpar中的平行流坊
Parallel Flowshop in YewPar
论文作者
论文摘要
并行性可能会减少为许多操作研究（OR）问题找到确切解决方案的时间，但是并行的组合搜索极具挑战性。 Yewpar是一个新的组合搜索框架，旨在允许域专家通过重复复杂的并行搜索模式从并行性中受益。本文表明（1）即使在可扩展的簇中，Yewpar中的典型或问题（Flowshop Scheduling FSP）的编码和并行处理也很少。 （2）Yewpar库使利用三个替代FSP并行化变得非常容易； （3）YEWPAR FSP实现是有效的，并且具有与已发布算法相当的顺序性能； （4）在10个标准FSP实例上提供了三个并行FSP版本的系统性能评估，其中有多达240名工人在Beowulf群集上。
Parallelism may reduce the time to find exact solutions for many Operations Research (OR) problems, but parallelising combinatorial search is extremely challenging. YewPar is a new combinatorial search framework designed to allow domain specialists to benefit from parallelism by reusing sophisticated parallel search patterns. This paper shows (1) that it is low effort to encode and parallelise a typical OR problem (Flowshop Scheduling FSP) in YewPar even for scalable clusters; (2) that the YewPar library makes it extremely easy to exploit three alternate FSP parallelisations; (3) that the YewPar FSP implementations are valid, and have sequential performance comparable with a published algorithm; and (4) provides a systematic performance evaluation of the three parallel FSP versions on 10 standard FSP instances with up to 240 workers on a Beowulf cluster.
