Enhancing Fault Simulation Performance by Dynamic Fault Clustering

S. Mirkhani, Z. Navabi
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引用次数: 6

Abstract

Fault simulation algorithms used for large designs propagate a list of faults instead of a single fault in each simulation. Concurrent (Ulrich and Baker, 1974) and deductive (Armstrong, 1972) fault simulation algorithms are two examples of this kind of algorithm. In this paper, we utilize an optimization concept, which can be added to fault list propagating algorithms. In this concept, faults can be grouped into several disjoint fault sets. All faults in a group affect every line of the circuit in a similar way. Fault clustering is performed dynamically, based on a particular test vector, during the fault simulation process. This method causes less memory fragmentation, since there are a limited number of fault groups in each simulation time. On the other hand, it reduces faulty circuit calculation in fault simulation process compared with the traditional fault simulation methods. In addition, the generality of this concept makes it useful for behavioral fault simulation methods as well as traditional gate-level ones. We have implemented this method in the VHDL environment and tested it on ISCAS'85 benchmarks. Experimental results show that in large circuits the performance is at least doubled by this technique
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动态故障聚类提高故障仿真性能
用于大型设计的故障仿真算法在每次仿真中传播故障列表而不是单个故障。并发(Ulrich and Baker, 1974)和演绎(Armstrong, 1972)故障模拟算法就是这类算法的两个例子。在本文中,我们使用了一个优化的概念,它可以添加到故障列表传播算法中。在这个概念中,故障可以分为几个不相交的故障集。一组中的所有故障都以类似的方式影响电路的每条线路。在故障模拟过程中,基于特定的测试向量动态地进行故障聚类。这种方法导致较少的内存碎片,因为在每个模拟时间内故障组的数量有限。另一方面,与传统的故障仿真方法相比,减少了故障仿真过程中的故障电路计算。此外,该概念的通用性使得它不仅适用于传统的门级仿真方法,也适用于行为故障仿真方法。我们在VHDL环境中实现了该方法,并在ISCAS'85基准测试中进行了测试。实验结果表明,在大型电路中,该技术的性能至少提高了一倍
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