Power-aware X-filling is a preferable approach to avoiding IR-drop-induced yield loss in at-speed scan testing. However, the ability of previous X-filling methods to reduce launch switching activity may be unsatisfactory, due to low effect (insufficient and global-only reduction) and/or low scalability (long CPU time). This paper addresses this reduction quality problem with a novel GA (Genetic Algorithm) based X-filling method, called GA-fill. Its goals are (1) to achieve both effectiveness and scalability in a more balanced manner and (2) to make the reduction effect of launch switching activity more concentrated on critical areas that have higher impact on IR-drop-induced yield loss. Evaluation experiments are being conducted on both benchmark and industrial circuits, and the results have demonstrated the usefulness of GA-fill.
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Yuta YAMATO, Xiaoqing WEN, Kohei MIYASE, Hiroshi FURUKAWA, Seiji KAJIHARA, "A GA-Based X-Filling for Reducing Launch Switching Activity toward Specific Objectives in At-Speed Scan Testing" in IEICE TRANSACTIONS on Information,
vol. E94-D, no. 4, pp. 833-840, April 2011, doi: 10.1587/transinf.E94.D.833.
Abstract: Power-aware X-filling is a preferable approach to avoiding IR-drop-induced yield loss in at-speed scan testing. However, the ability of previous X-filling methods to reduce launch switching activity may be unsatisfactory, due to low effect (insufficient and global-only reduction) and/or low scalability (long CPU time). This paper addresses this reduction quality problem with a novel GA (Genetic Algorithm) based X-filling method, called GA-fill. Its goals are (1) to achieve both effectiveness and scalability in a more balanced manner and (2) to make the reduction effect of launch switching activity more concentrated on critical areas that have higher impact on IR-drop-induced yield loss. Evaluation experiments are being conducted on both benchmark and industrial circuits, and the results have demonstrated the usefulness of GA-fill.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E94.D.833/_p
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@ARTICLE{e94-d_4_833,
author={Yuta YAMATO, Xiaoqing WEN, Kohei MIYASE, Hiroshi FURUKAWA, Seiji KAJIHARA, },
journal={IEICE TRANSACTIONS on Information},
title={A GA-Based X-Filling for Reducing Launch Switching Activity toward Specific Objectives in At-Speed Scan Testing},
year={2011},
volume={E94-D},
number={4},
pages={833-840},
abstract={Power-aware X-filling is a preferable approach to avoiding IR-drop-induced yield loss in at-speed scan testing. However, the ability of previous X-filling methods to reduce launch switching activity may be unsatisfactory, due to low effect (insufficient and global-only reduction) and/or low scalability (long CPU time). This paper addresses this reduction quality problem with a novel GA (Genetic Algorithm) based X-filling method, called GA-fill. Its goals are (1) to achieve both effectiveness and scalability in a more balanced manner and (2) to make the reduction effect of launch switching activity more concentrated on critical areas that have higher impact on IR-drop-induced yield loss. Evaluation experiments are being conducted on both benchmark and industrial circuits, and the results have demonstrated the usefulness of GA-fill.},
keywords={},
doi={10.1587/transinf.E94.D.833},
ISSN={1745-1361},
month={April},}
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TY - JOUR
TI - A GA-Based X-Filling for Reducing Launch Switching Activity toward Specific Objectives in At-Speed Scan Testing
T2 - IEICE TRANSACTIONS on Information
SP - 833
EP - 840
AU - Yuta YAMATO
AU - Xiaoqing WEN
AU - Kohei MIYASE
AU - Hiroshi FURUKAWA
AU - Seiji KAJIHARA
PY - 2011
DO - 10.1587/transinf.E94.D.833
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E94-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2011
AB - Power-aware X-filling is a preferable approach to avoiding IR-drop-induced yield loss in at-speed scan testing. However, the ability of previous X-filling methods to reduce launch switching activity may be unsatisfactory, due to low effect (insufficient and global-only reduction) and/or low scalability (long CPU time). This paper addresses this reduction quality problem with a novel GA (Genetic Algorithm) based X-filling method, called GA-fill. Its goals are (1) to achieve both effectiveness and scalability in a more balanced manner and (2) to make the reduction effect of launch switching activity more concentrated on critical areas that have higher impact on IR-drop-induced yield loss. Evaluation experiments are being conducted on both benchmark and industrial circuits, and the results have demonstrated the usefulness of GA-fill.
ER -