基于字典编码的热感知测试数据压缩

R. Karmakar, S. Chattopadhyay
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引用次数: 9

摘要

本文提出了一种基于字典编码的热感知测试数据压缩技术。庞大的测试数据量和芯片温度是测试工程师面临的两大挑战。芯片的温度可以在很大程度上通过使用高效的不关心填充最小化扫描链中的过渡计数来降低。另一方面,通过智能填充无关向量,从测试向量中获得更多相似的子向量,可以实现高压缩比。虽然这两个问题都依赖于不在意位填充,但现有的大部分工作都将它们视为独立的问题。在我们的工作中,我们将温度降低和压缩结合成一个问题并解决了它。我们提出了一种中间方法,在温度和压缩比之间进行权衡。在ISCAS'89和ITC'99基准上的实验结果表明,该方法可以灵活地实现温度和压缩比之间的平衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Thermal-Aware Test Data Compression Using Dictionary Based Coding
In this paper, we have proposed a new thermal-aware test data compression technique using dictionary based coding. Huge test data volume and chip temperature are two major challenges for test engineers. Temperature of a chip can be reduced to a large extent by minimizing transition count in scan chains using efficient don't-care filling. On the other hand, high compression ratio can be achieved by filling the don't-cares intelligently to get more similar sub-vectors from test vectors. Although, both of the problems rely on don't-care bit filling, most of the existing works have considered them as separate problems. In our work, we have combined both temperature reduction and compression into a single problem and solved it. We present an intermediate approach that performs a trade-off between temperature and compression ratio. Experimental results on ISCAS'89 and ITC'99 benchmarks show the flexibility of the proposed method to achieve a balance between temperature and compression ratio.
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