A Task Mapping Method for a Hypercube by Combining Subcubes

S. Horiike
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引用次数: 2

Abstract

This paper presents a new algorithm for mapping of tasks onto a hypercube. Given a weighted task graph, the algorithm finds good mapping in a reasonable computation time. When the target computer is ndimensional cube (n-cube), the proposed algorithm is composed of n stages. The algorithm starts with an initial state in which the tasks are mapped onto 2n 0cubes. At each stage k, the task graph is mapped onto 2n-k k-cubes. At the beginning of stage k, the tasks have already been mapped onto 2n-(k-1) (k-1)-cubes. The tasks are mapped onto k-cubes by combining a pair of (k-1)-cubes. 2n-k pairs of (k-1)-cubes are determined, and they are combined so that the mapping onto the k-cubes makes the communication cost as low as possible. When the target computer is n-dimensional cube (ncube), the proposed algorithm is composed of n stages. The algorithm starts with an initial state in which the tasks are mapped onto 2" 0-cubes. At each stage k (k=1,2,..,n), the task graph is mapped onto 2n-k k-cubes. At the beginning of stage k, the tasks are already mapped onto 2n-(k-1) (k-1)-cubes. The mapping onto k-cubes can be done by combining a pair of (k-1)-cubes. 2n-k pairs are determined among 2n-(k-1) (k-1)-cubes, and they are combined so that mapping onto the k-cubes makes the communication cost as low as possible.
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组合子数据集的超立方体任务映射方法
提出了一种将任务映射到超立方体上的新算法。给定一个加权任务图,该算法在合理的计算时间内找到较好的映射。当目标计算机为n维立方体(n-cube)时,该算法由n个阶段组成。该算法从一个初始状态开始,在初始状态下,任务被映射到2n个立方体上。在每个阶段k,任务图被映射到2n-k个立方体上。在阶段k开始时,任务已经被映射到2n-(k-1) (k-1)个立方体上。任务通过组合一对(k-1)个立方体映射到k个立方体上。确定了2n-k对(k-1)立方体,并将它们组合在一起,以便映射到k个立方体上,使通信成本尽可能低。当目标计算机为n维立方体(ncube)时,算法由n个阶段组成。该算法从一个初始状态开始,在初始状态下,任务被映射到2英寸的0立方上。在每个阶段k (k=1,2,…,n),任务图被映射到2n-k -k -立方体上。在阶段k开始时,任务已经被映射到2n-(k-1) (k-1)个立方体上。映射到k-立方体可以通过组合一对(k-1)-立方体来完成。在2n-(k-1) (k-1)个立方体中确定2n-k对,并将它们组合起来,以便映射到k个立方体上,使通信成本尽可能低。
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