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Pipeline for parallel implementation of multi-objective particle swarm optimization

机译:多目标粒子群优化并行实现的管道

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Communication overhead is an issue in a parallel implementation of algorithm on loosely coupled systems. Pipeline is a technique used to achieve parallelism at instruction level by dividing task into different stages and for every stage, it's output is the input for next the stage. Thus, pipeline limits the communication overhead by restricting it to only for previous and next stage. Pipeline also performs faster by overlapping the instructions. In this paper, we propose new approach for parallel implementation of multi-objective particle swarm optimization (MOPSO) using logical pipeline, which focuses on overlapping the execution of functions. Logical pipeline for MOPSO is the disposition of three stages, each for calculating velocity, evaluation and updating of archive. We compared the results with the different parallel models for MOPSO and improvement in time is significant.
机译:通信开销是在松耦合系统上并行执行算法的一个问题。流水线技术是通过将任务划分为不同的阶段来在指令级实现并行性的技术,对于每个阶段,它的输出都是下一阶段的输入。因此,流水线通过将通信开销限制为仅用于上一级和下一级来限制通信开销。流水线通过重叠指令也可以更快地执行。在本文中,我们提出了一种使用逻辑流水线并行实现多目标粒子群优化(MOPSO)的新方法,该方法着重于功能的执行重叠。 MOPSO的逻辑流水线分为三个阶段,每个阶段用于计算速度,评估和更新档案。我们将结果与MOPSO的不同并行模型进行了比较,时间的改进意义重大。

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