IDPS:一个大规模并行启发式搜索算法

A. Mahanti, C. J. Daniels
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引用次数: 3

摘要

提出了一种高效的SIMD并行算法IDPS(迭代深化并行搜索)。通过在著名的搜索算法测试台问题15-puzzle上进行的实验,研究了四种IDPS变体的性能。在实验中,采用两种不同的静态负载均衡方案收集数据。在第一种方案下,4 K、8 K和16 K处理器的平均效率约为/sup 3/// //sub 4/。在第二种方案下,8k和16k处理器的平均效率分别为0.92和0.76。对于可容许搜索,对于显著大小的问题,可以得到线性或超线性的平均加速
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IDPS: a massively parallel heuristic search algorithm
Presents an efficient SIMD parallel algorithm, called IDPS (iterative deepening parallel search). The performance of four variants of IDPS is studied through experiments conducted on the well known test-bed problem for search algorithms, the 15-puzzle. During the experiments, data were gathered under two different static load-balancing schemes. Under the first scheme, an average efficiency of approximately /sup 3///sub 4/ was obtained for 4 K, 8 K, and 16 K processors. Under the second scheme, average efficiencies of 0.92 and 0.76 were obtained for 8 K and 16 K processors, respectively. It is also shown that for admissible search, linear or superlinear average speedup can be obtained for problems of significant size.<>
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