The run length based coding schemes have been very effective for the test data compression in case of current generation SoCs with a large number of IP cores. The first part of paper presents a survey of the run length based codes. The data compression of any partially specified test data depends upon how the unspecified bits are filled with 1s and 0s. In the second part of the paper, the five different approaches for "don't care" bit filling based on nature of runs are proposed to predict the maximum compression based on entropy. Here the various run length based schemes are compared with maximum data compression limit based on entropy bounds. The actual compressions claimed by the authors are also compared. For various ISCAS circuits, it has been shown that when the X filling is done considering runs of zeros followed by one as well as runs of ones followed by zero (i.e., Extended FDR), it provides the maximum data compression. In third part, it has been shown that the average test power and peak power is minimum when the don't care bits are filled to make the long runs of 0s as well as 1s.
This paper presents a method to compress partially specified test data for a given SoC in Automatic Test Equipment (ATE). A method "Hamming Distance Based 2-Dimensional Reordering with Power Efficient Don't Care Bit Filling" is presented for compression of test data in which two dimensional i.e. row and columnwise test vector reordering and power optimized don't care bit filling method is applied. The advantage of the approach is a good compression with very low test power achieved without adding area overhead. The advantages are shown by experimental results with ISCAS benchmark circuits.
Test data compression is the major issues for the external testing of IP core-based SoC. From a large pool of diverse available techniques for compression, run length-based schemes are most appropriate for IP cores. To improve the compression and to reduce the test power, the test data processing schemes like "don't care bit filling" and "reordering" which do not require any modification in internal structure and do not demand use of any test development tool can be used for SoC-containing IP cores with hidden structure. The proposed "Weighted Transition Based Reordering-Columnwise Bit Filling-Difference Vector (WTR-CBF-DV)" is a modification to earlier proposed "Hamming Distance based Reordering-Columnwise Bit Filling and Difference vector." This new method aims not only at very high compression but also aims at shift in test power reduction without any significant on-chip area overhead. The experiment results on ISCAS89 benchmark circuits show that the test data compression ratio has significantly improved for each case. It is also noteworthy that, in most of the case, this scheme does not involve any extra silicon area overhead compared to the base code with which it used. For few cases, it requires an extra XOR gate and feedback path only. As application of this scheme increases run length of zeroes in test set, as a result, the number of transitions during scan shifting is reduced. This may lower scan power. The proposed scheme can be easily integrated into the existing industrial flow.
Test power and test time have been the major issues for current scenario of VLSI testing. The test data compression is the well known method used to reduce the test time. The don't care bit filling method can be used for effective test data compression as well as reduction in scan power. In this paper we describe the algorithm for don't care assignment like MT(Minimum Transition)-fill technique and hamming distance based technique.The selective Huffman ,optimal Huffman and modified selective Huffman coding are applied on the mapping set to give the optimum Compression and weighted transition matrix is used for scan power Using these techniques find compression and scan power parameters like average power and peak power and conclude that MT-fill technique gives low peak and average powers and Hamming distance based modified selective Huffman coding technique gives higher compression ratio compare to another methods like selective and optimal Huffman coding.
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