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Efficient techniques for clustering and scheduling onto embedded multiprocessors

机译：用于在嵌入式多处理器上集群和调度的高效技术

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摘要

Multiprocessor mapping and scheduling algorithms have been extensively studied over the past few decades and have been tackled from different perspectives. In the late 1980's, the two-step decomposition of scheduling nto clustering and cluster-scheduling - was introduced. Ever since, several clustering and merging algorithms have been proposed and individually reported to be efficient. However, it is not clear how effective they are and how well they compare against single-step scheduling algorithms or other multistep algorithms. In this paper, we explore the effectiveness of the two-phase decomposition of scheduling and describe efficient and novel techniques that aggressively streamline interprocessor communications and can be tuned to exploit the significantly longer compilation time that is available to embedded system designers. We evaluate a number of leading clustering and merging algorithms using a set of benchmarks with diverse structures. We present an experimental setup for comparing the single-step against the two-step scheduling approach. We determine the importance of different steps in scheduling and the effect of different steps on overall schedule performance and show that the decomposition of the scheduling process indeed improves the overall performance. We also show that the quality of the solutions depends on the quality of the clusters generated in the clustering step. Based on the results, we also discuss why the parallel time metric in the clustering step may not provide an accurate measure for the final performance of cluster-scheduling.
机译：在过去的几十年中，对多处理器映射和调度算法进行了广泛的研究，并已从不同角度进行了研究。在1980年代后期，引入了调度nto聚类和聚类调度的两步分解方法。从那时起，已经提出了几种聚类和合并算法，并分别报告了它们的有效性。但是，尚不清楚它们与单步调度算法或其他多步算法相比有多有效，以及有多出色。在本文中，我们探讨了调度的两阶段分解的有效性，并描述了有效且新颖的技术，该技术积极地简化了处理器之间的通信，并且可以进行调整以利用嵌入式系统设计人员可利用的更长的编译时间。我们使用一组具有不同结构的基准来评估许多领先的聚类和合并算法。我们提供了一个实验设置，用于比较单步计划和两步计划方法。我们确定了调度中不同步骤的重要性以及不同步骤对整体调度性能的影响，并表明调度过程的分解确实提高了整体性能。我们还表明，解决方案的质量取决于在聚类步骤中生成的聚类的质量。基于结果，我们还讨论了为什么聚类步骤中的并行时间度量标准可能无法为聚类调度的最终性能提供准确的度量。

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