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A FAST AND EFFICIENT ISOMORPHIC TASK ALLOCATION SCHEME FOR K-ARY N-CUBE SYSTEMS

机译:K-ary N-Cube系统的快速有效的同构任务分配方案

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摘要

A good task allocation algorithm should find available processors for incoming jobs, if they exist, with minimum overhead. Due to its topological generality and flexibility the k-ary n-cube architecture has been chosen for the task allocation problem. We propose a fast and efficient isomorphic processor allocation scheme for k-ary n-cube systems by using isomorphic partitioning where the processor space is partitioned into higher dimensional isomorphic subcube and by using Subcube recognition ability algorithm (SRA) which uses simple coordinate calculation and spatial subtraction. Thus the proposed scheme seeks to reduce the search space drastically, and hence can locate a free subcube very quickly providing scalable, faster, processor allocation, complete recognition ability with minimal overhead and minimizes the fragmentation.
机译:一个好的任务分配算法应该以最小的开销找到用于传入作业的可用处理器(如果存在)。由于其拓扑通用性和灵活性,已选择k元n多维数据集架构用于任务分配问题。我们通过使用将处理器空间划分为高维同构子立方体的同构分区,以及使用简单坐标计算和空间的子立方体识别能力算法(SRA),为k元n立方系统提出了一种快速有效的同构处理器分配方案减法。因此,所提出的方案试图大幅度地减少搜索空间,并因此可以非常快速地定位自由子多维数据集,从而提供可扩展,更快的处理器分配,具有最小开销的完整识别能力并最小化碎片。

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