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Practical algorithms for selection on coarse-grained parallel computers

机译:在粗粒度并行计算机上进行选择的实用算法

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In this paper, we consider the problem of selection on coarse-grained distributed memory parallel computers. We discuss several deterministic and randomized algorithms for parallel selection. We also consider several algorithms for load balancing needed to keep a balanced distribution of data across processors during the execution of the selection algorithms. We have carried out detailed implementations of all the algorithms discussed on the CM-5 and report on the experimental results. The results clearly demonstrate the role of randomization in reducing communication overhead.
机译:在本文中,我们考虑了在粗粒度分布式内存并行计算机上的选择问题。我们讨论了几种并行选择的确定性和随机算法。我们还考虑了在选择算法执行期间需要几种负载平衡算法,以在处理器之间保持数据的均衡分配。我们已经对CM-5上讨论的所有算法进行了详细的实现,并报告了实验结果。结果清楚地证明了随机化在减少通信开销方面的作用。

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