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Test Pattern Generation for Approximate Circuits Based on Boolean Satisfiability

机译:基于布尔可满足性的近似电路测试图生成

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Approximate computing has gained growing attention as it provides trade-off between output quality and computation effort for inherent error tolerant applications such as recognition, mining, and media processing applications. As a result, several approximate hardware designs have been proposed in order to harness the benefits of approximate computing. While these circuits are subjected to manufacturing defects and runtime failures, the testing methods should be aware of their approximate nature. In this paper, we propose an automatic test pattern generation methodology for approximate circuits based on boolean satisfiability, which is aware of output quality and approximable vs non-approximable faults. This allows us to significantly reduce the number of faults to be tested, and test time accordingly, without sacrificing the output quality or test coverage. Experimental results show that, the proposed approach can reduce the fault list by 2.85× on average while maintaining high fault coverage.
机译:近似计算得到了越来越多的关注,因为它为固有的容错应用(例如识别,挖掘和媒体处理应用)提供了输出质量和计算工作之间的折衷。结果,已经提出了几种近似的硬件设计,以便利用近似计算的好处。当这些电路遭受制造缺陷和运行时故障时,测试方法应注意其近似性质。在本文中,我们提出了一种基于布尔可满足性的近似电路自动测试模式生成方法,该方法可了解输出质量以及近似故障与非近似故障。这使我们能够在不牺牲输出质量或测试覆盖范围的情况下,显着减少要测试的故障数量,并相应地缩短测试时间。实验结果表明,该方法在保持较高的故障覆盖率的同时,平均可减少2.85倍的故障列表。

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