A Message-Passing Based Algorithm for k-Terminal Reliability

Minh Lê, J. Weidendorfer
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Abstract

As the exact computation of the k-terminal reliability is an NP-Complete problem, runtime and memory requirements grow exponentially with the input size. Shared memory parallelization algorithms were developed for reducing runtime. However, even a relatively high amount of memory can already be exhausted within a short period of time. A message-passing based algorithm is proposed in order to circumvent the memory limitation of shared memory implementations. It is the first message-passing based algorithm for the k-terminal problem. The new algorithm is designed for the currently most efficient BDD-based method. New data structures such as the distributed BDD and a distributed hash table lead to good speedup results and load-balanced task distributions. Now the size of computable inputs are limited to the memory carried along by the available cores. The two-terminal reliability of a 17 node complete network was computed on 1024 cores of the SuperMUC within 7 minutes, using 1.28 Terabyte of memory and resulting in more than 6 billion BDD nodes.
基于消息传递的k-终端可靠性算法
由于k端可靠性的精确计算是np完全问题,运行时和内存需求随着输入大小呈指数增长。为了缩短运行时间,开发了共享内存并行化算法。然而,即使是相对较高的内存量也可能在短时间内耗尽。为了克服共享内存实现的内存限制,提出了一种基于消息传递的算法。这是针对k端问题的第一个基于消息传递的算法。新算法是针对目前最有效的基于bdd的方法而设计的。新的数据结构,如分布式BDD和分布式哈希表,带来了良好的加速结果和负载均衡的任务分布。现在可计算输入的大小受限于可用内核所携带的内存。在SuperMUC的1024核上,使用1.28 tb的内存,在7分钟内计算出17节点完整网络的两端可靠性,得到超过60亿个BDD节点。
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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