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Isomorphic strategy for processor allocation in k-ary n-cube systems

机译:K元n立方系统中处理器分配的同构策略

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摘要

Due to its topological generality and flexibility, the k-ary n-cube architecture has been actively researched for various applications. However, the processor allocation problem has not been adequately addressed for the k-ary n-cube architecture, even though it has been studied extensively for hypercubes and meshes. The earlier k-ary n-cube allocation schemes based on conventional slice partitioning suffer from internal fragmentation of processors. In contrast, algorithms based on job-based partitioning alleviate the fragmentation problem but require higher time complexity. This paper proposes a new allocation scheme based on isomorphic partitioning, where the processor space is partitioned into higher dimensional isomorphic subcubes. The proposed scheme minimizes the fragmentation problem and is general in the sense that any size request can be supported and the host architecture need not be isomorphic. Extensive simulation study reveals that the proposed scheme significantly outperforms earlier schemes in terms of mean response time for practical size k-ary and n-cube architectures. The simulation results also show that reduction of external fragmentation is more substantial than internal fragmentation with the proposed scheme.
机译:由于其拓扑通用性和灵活性,已积极研究了k元n立方体体系结构的各种应用。但是,尽管已经针对超立方体和网格技术进行了广泛研究,但对于k元n立方体体系结构,处理器分配问题尚未得到充分解决。基于常规切片划分的早期k-ary n-cube分配方案受处理器内部碎片的影响。相反,基于作业的分区算法减轻了碎片问题,但需要更高的时间复杂度。本文提出了一种基于同构划分的新分配方案,该方案将处理器空间划分为高维同构子立方体。所提出的方案最小化了碎片问题,并且在可以支持任何大小请求且主机体系结构不需要是同构的意义上是通用的。大量的仿真研究表明,对于实际大小的k-ary和n-cube体系结构,该方案在平均响应时间方面明显优于早期方案。仿真结果还表明,采用所提出的方案,减少外部碎片比内部碎片更重要。

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