Distributed priority queues on hypercube architectures

Sajal K. Das, M. C. Pinotti, F. Sarkar
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引用次数: 10

Abstract

We efficiently map a priority queue on the hypercube architecture in a load balanced manner, with no additional communication overhead. Two implementations for insert and deletemin operations are proposed on the single-port hypercube model. In a b-bandwidth, n-item priority queue in which every node contains b items in sorted order, the first implementation achieves optimal speed-up of O[min{log n, b(log n)/(log b+log log n)}] for inserting b pre-sorted items or deleting b smallest items, where b=O(n/sup 1/c/) with c>1. In particular, single insertion and deletion operations are cost-optimal and require O(log n/p+log p) time using O(log n/log log n) processors. The second implementation is more scalable since it uses a larger number of processors, and attains a 'nearly' optimal speed-up on the single-port hypercube. The insertion of log n pre-sorted items or the deletion of log n smallest items requires O(log log n)/sup 2/ time and O(log/sup 2/ n/log log n) processors. However, on the slightly more powerful pipelined hypercube model, we are able to reduce the time complexity to O(log log n) thus attaining optimal speed-up. To the best of our knowledge, our algorithms provide the first implementations of b-bandwidth distributed priority queues, which are load balanced and yet guarantee optimal speed-up.
超多维数据集架构上的分布式优先级队列
我们以负载均衡的方式在超多维数据集架构上有效地映射优先级队列,没有额外的通信开销。在单端口超立方体模型上提出了插入和删除操作的两种实现。在带宽为b,项数为n的优先级队列中,每个节点按排序顺序包含b个项,对于插入b个预排序项或删除b个最小项,第一种实现获得了O[min{log n, b(log n)/(log b+log log n)}]的最优加速,其中b=O(n/sup 1/c/),其中c>1。特别是,单个插入和删除操作是成本最优的,使用O(log n/log log n)个处理器需要O(log n/p+log p)时间。第二种实现更具可扩展性,因为它使用了更多的处理器,并且在单端口超立方体上实现了“近乎”最佳的加速。插入log n个预排序项或删除log n个最小项需要O(log log n)/sup 2/时间和O(log/sup 2/ n/log log n)个处理器。然而,在更强大的管道超立方体模型上,我们能够将时间复杂度降低到O(log log n),从而获得最佳的加速。据我们所知,我们的算法提供了b带宽分布式优先级队列的第一个实现,它是负载平衡的,但保证了最佳的加速。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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