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An adaptive system-level diagnosis approach for hypercube multiprocessors

机译:超立方体多处理器的自适应系统级诊断方法

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This paper proposes a hierarchical adaptive system-level diagnosis approach for hypercube systems. Three measures for diagnosis cost (diagnosis time, number of tests and number of test links) are analyzed for the proposed algorithm. It is proved that the diagnosis cost required by this algorithm is lower than in the previous diagnosis algorithms in most of the fault cases. It is shown that the diagnosis cost for the proposed algorithm depends on the number of faulty units in the system and the cost is extremely low when only a small number of faulty units exist. It is shown that this algorithm is even characterized by lower costs than a pessimistic diagnosis algorithm which trades lower diagnosis cost for a lower degree of accuracy.
机译:本文提出了一种针对超立方体系统的分层自适应系统级诊断方法。针对所提出的算法,分析了三种诊断成本的度量方法(诊断时间,测试数量和测试链接数量)。事实证明,在大多数故障情况下,该算法所需的诊断成本比以前的诊断算法要低。结果表明,该算法的诊断成本取决于系统中故障单元的数量,当故障单元数量很少时,诊断成本非常低。结果表明,与悲观诊断算法相比,该算法的特征在于成本更低,而悲观诊断算法却以较低的诊断成本换取了较低的准确性。

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