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A Parallel Genetic Algorithm for Automatic Generation of Test Sequences for Digital Circuits

机译:一种平行遗传算法,用于自动生成数字电路测试序列

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The paper deals with the problem of Automatic Generation of Test Sequences for digital circuits. Genetic Algorithms have been successfully proposed to solve this industrially critical problem; however, they have some drawbacks, e.g., they are ofter unable to detect some hard to test faults, and require a careful tuning of the algorithm parameters. In this paper, we describe a new parallel version of an existing GA-based ATPG, which exploits competing sub-populations to overcome these problems. The new approach has been implemented in the PVM environment and has been evaluated on a workstation network using some of the standard benchmark circuits. The results show that it is able to significantly improve the results quality (by testing some critical faults) at the expense of increased CPU time requirements.
机译:本文涉及数字电路自动生成测试序列的问题。已成功提出遗传算法来解决这一工业危急的问题;然而,它们具有一些缺点,例如,它们是无法检测到一些难以测试的故障,并且需要仔细调整算法参数。在本文中,我们描述了现有的GA基ATPG的新并行版本,利用竞争的子群来克服这些问题。新方法已经在PVM环境中实现,并使用了一些标准的基准电路在工作站网络上进行了评估。结果表明,它能够以提高CPU时间要求的代价,能够显着提高结果质量(通过测试某些关键故障)。

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