Study on Expansion of Convolutional Compactors over Galois Field
Summary :
Convolutional compactors offer a promising technique of compacting test responses. In this study we expand the architecture of convolutional compactor onto a Galois field in order to improve compaction ratio as well as reduce X-masking probability, namely, the probability that an error is masked by unknown values. While each scan chain is independently connected by EOR gates in the conventional arrangement, the proposed scheme treats q signals as an element over GF(2q), and the connections are configured on the same field. We show the arrangement of the proposed compactors and the equivalent expression over GF(2). We then evaluate the effectiveness of the proposed expansion in terms of X-masking probability by simulations with uniform distribution of X-values, as well as reduction of hardware overheads. Furthermore, we evaluate a multi-weight arrangement of the proposed compactors for non-uniform X distributions.
- Publication
- IEICE TRANSACTIONS on Information Vol.E91-D No.3 pp.706-712
- Publication Date
- 2008/03/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1093/ietisy/e91-d.3.706
- Type of Manuscript
- Special Section PAPER (Special Section on Test and Verification of VLSIs)
- Category
- Test Compression
Authors
Keyword
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Masayuki ARAI, Satoshi FUKUMOTO, Kazuhiko IWASAKI, "Study on Expansion of Convolutional Compactors over Galois Field" in IEICE TRANSACTIONS on Information,
vol. E91-D, no. 3, pp. 706-712, March 2008, doi: 10.1093/ietisy/e91-d.3.706.
Abstract: Convolutional compactors offer a promising technique of compacting test responses. In this study we expand the architecture of convolutional compactor onto a Galois field in order to improve compaction ratio as well as reduce X-masking probability, namely, the probability that an error is masked by unknown values. While each scan chain is independently connected by EOR gates in the conventional arrangement, the proposed scheme treats q signals as an element over GF(2q), and the connections are configured on the same field. We show the arrangement of the proposed compactors and the equivalent expression over GF(2). We then evaluate the effectiveness of the proposed expansion in terms of X-masking probability by simulations with uniform distribution of X-values, as well as reduction of hardware overheads. Furthermore, we evaluate a multi-weight arrangement of the proposed compactors for non-uniform X distributions.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e91-d.3.706/_p
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@ARTICLE{e91-d_3_706,
author={Masayuki ARAI, Satoshi FUKUMOTO, Kazuhiko IWASAKI, },
journal={IEICE TRANSACTIONS on Information},
title={Study on Expansion of Convolutional Compactors over Galois Field},
year={2008},
volume={E91-D},
number={3},
pages={706-712},
abstract={Convolutional compactors offer a promising technique of compacting test responses. In this study we expand the architecture of convolutional compactor onto a Galois field in order to improve compaction ratio as well as reduce X-masking probability, namely, the probability that an error is masked by unknown values. While each scan chain is independently connected by EOR gates in the conventional arrangement, the proposed scheme treats q signals as an element over GF(2q), and the connections are configured on the same field. We show the arrangement of the proposed compactors and the equivalent expression over GF(2). We then evaluate the effectiveness of the proposed expansion in terms of X-masking probability by simulations with uniform distribution of X-values, as well as reduction of hardware overheads. Furthermore, we evaluate a multi-weight arrangement of the proposed compactors for non-uniform X distributions.},
keywords={},
doi={10.1093/ietisy/e91-d.3.706},
ISSN={1745-1361},
month={March},}
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TY - JOUR
TI - Study on Expansion of Convolutional Compactors over Galois Field
T2 - IEICE TRANSACTIONS on Information
SP - 706
EP - 712
AU - Masayuki ARAI
AU - Satoshi FUKUMOTO
AU - Kazuhiko IWASAKI
PY - 2008
DO - 10.1093/ietisy/e91-d.3.706
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E91-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2008
AB - Convolutional compactors offer a promising technique of compacting test responses. In this study we expand the architecture of convolutional compactor onto a Galois field in order to improve compaction ratio as well as reduce X-masking probability, namely, the probability that an error is masked by unknown values. While each scan chain is independently connected by EOR gates in the conventional arrangement, the proposed scheme treats q signals as an element over GF(2q), and the connections are configured on the same field. We show the arrangement of the proposed compactors and the equivalent expression over GF(2). We then evaluate the effectiveness of the proposed expansion in terms of X-masking probability by simulations with uniform distribution of X-values, as well as reduction of hardware overheads. Furthermore, we evaluate a multi-weight arrangement of the proposed compactors for non-uniform X distributions.
ER -
English
