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首页> 外文期刊>Journal of circuits, systems and computers >Improving Compression Ratios for Code-Based Test Pattern Compressions through Column-Wise Reordering Algorithms
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Improving Compression Ratios for Code-Based Test Pattern Compressions through Column-Wise Reordering Algorithms

机译：通过列 - 明智的重新排序算法提高基于代码的测试模式压缩的压缩比

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摘要

Chip testing is an effective way to reduce the number of defective or faulty chips that reach the market. However, as large-scale test patterns need to be transmitted into a circuit under test during testing, the transmission time dominates the test application time of the chip testing. Therefore, code-based compression methods are widely used in compressing test patterns because of their capability to reduce the transmission time and save storage space significantly. Current code-based compression methods cannot fully apply the inherent characteristics of test patterns yet. To address this problem, this study proposes two-stage test pattern preprocessing algorithms, thereby improving the efficiency of the code-based compression method. First, we propose a column-wise reordering for Hadamard matrix (CRHM) algorithm, which decomposes a test set consisting of test patterns into a primary component set (PCS) and a residual component set (RCS). The PCS inherits some is from the original test set (OTS), and other is belong to the RCS. As the number of is contained in the RCS is less than that in the OTS, the RCS can obtain a higher code-based compression ratio. The PCS can be generated by an on-chip generator, which does not consume transmission time. Second, we propose a novel column-wise reordering for the RCS (CRRCS) algorithm. The CRRCS solves the new location of each column of the RCS one by one in the list to decrease the entropy of the RCS. The entropy denotes the shortest length of the codeword required for the symbol to be encoded. The smaller entropy value refers to a higher compression ratio. For the sorted RCS, more high-frequency symbols can be replaced by shorter codewords. Experimental results based on seven code-based compression methods show that the proposed algorithms can increase the average compression ratio by a total of 19.91%, and the highest average compression ratio reaches 85.04% for ISCAS'89 benchmark circuits.
机译：芯片测试是减少到达市场的缺陷或缺陷码头数量的有效方法。然而，随着在测试期间需要传输到被测电路的大规模测试模式，传输时间占据了芯片测试的测试应用时间。因此，基于代码的压缩方法广泛用于压缩测试模式，因为它们能够减少传输时间并显着节省存储空间。基于代码的压缩方法尚不完全应用测试模式的固有特性。为了解决这个问题，本研究提出了两阶段测试模式预处理算法，从而提高了基于码的压缩方法的效率。首先，我们提出了一种针对Hadamard矩阵（CRHM）算法的列WISE重新排序，其将由测试模式组成的测试集分解为主分量集（PC）和残差组件集（RCS）。 PC继承一些来自原始测试集（OTS），而其他属于RCS。随着RCS中包含的数量小于OTS中的数量，RC可以获得更高的基于代码的压缩比。 PC可以由片上发生器生成，不会消耗传输时间。其次，我们提出了一种用于RCS（CRRCS）算法的新型专栏的重新排序。 CRRC在列表中逐个解决了RCS的每列的新位置，以减少RCS的熵。熵表示要编码的符号所需的码字的最短长度。较小的熵值是指更高的压缩比。对于排序的RCS，可以通过较短的码字替换更多的高频符号。基于七种基于码的压缩方法的实验结果表明，所提出的算法可以将平均压缩比增加了19.91％，最高平均压缩比对于ISCAS'89基准电路达到85.04％。

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