VLSI Yield Optimization Based on the Redundancy at the Sub-Processing-Element Level

Tianxu ZHAO; Yue HAO; Yong-Chang JIAO

VLSI Yield Optimization Based on the Redundancy at the Sub-Processing-Element Level

Tianxu ZHAO, Yue HAO, Yong-Chang JIAO

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An optimal allocation model for the sub-processing-element (sub-PE) level redundancy is developed, which is solved by the genetic algorithms. In the allocation model, the average defect density D and the parameter δ are also considered in order to accurately analyze the element yield, where δ is defined as the ratio of the support circuit area to the total area of a PE. When the PE's area is imposed on the constraint, the optimal solutions of the model with different D and δ are calculated. The simulation results indicate that, for any fixed average defect density D, both the number of the optimal redundant sub-circuit added into a PE and the PE's yield decrease as δ increases. Moreover, for any fixed parameter δ, the number of the optimal redundant sub-circuit increases, while the optimal yield of the PE decreases, as D increases.

Publication: IEICE TRANSACTIONS on Information Vol.E84-D No.11 pp.1471-1475

Publication Date: 2001/11/01

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Type of Manuscript: Special Section PAPER (Special Issue on Function Integrated Information Systems)

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Tianxu ZHAO, Yue HAO, Yong-Chang JIAO, "VLSI Yield Optimization Based on the Redundancy at the Sub-Processing-Element Level" in IEICE TRANSACTIONS on Information, vol. E84-D, no. 11, pp. 1471-1475, November 2001, doi: .
Abstract: An optimal allocation model for the sub-processing-element (sub-PE) level redundancy is developed, which is solved by the genetic algorithms. In the allocation model, the average defect density D and the parameter δ are also considered in order to accurately analyze the element yield, where δ is defined as the ratio of the support circuit area to the total area of a PE. When the PE's area is imposed on the constraint, the optimal solutions of the model with different D and δ are calculated. The simulation results indicate that, for any fixed average defect density D, both the number of the optimal redundant sub-circuit added into a PE and the PE's yield decrease as δ increases. Moreover, for any fixed parameter δ, the number of the optimal redundant sub-circuit increases, while the optimal yield of the PE decreases, as D increases.
URL: https://global.ieice.org/en_transactions/information/10.1587/e84-d_11_1471/_p

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@ARTICLE{e84-d_11_1471,
author={Tianxu ZHAO, Yue HAO, Yong-Chang JIAO, },
journal={IEICE TRANSACTIONS on Information},
title={VLSI Yield Optimization Based on the Redundancy at the Sub-Processing-Element Level},
year={2001},
volume={E84-D},
number={11},
pages={1471-1475},
abstract={An optimal allocation model for the sub-processing-element (sub-PE) level redundancy is developed, which is solved by the genetic algorithms. In the allocation model, the average defect density D and the parameter δ are also considered in order to accurately analyze the element yield, where δ is defined as the ratio of the support circuit area to the total area of a PE. When the PE's area is imposed on the constraint, the optimal solutions of the model with different D and δ are calculated. The simulation results indicate that, for any fixed average defect density D, both the number of the optimal redundant sub-circuit added into a PE and the PE's yield decrease as δ increases. Moreover, for any fixed parameter δ, the number of the optimal redundant sub-circuit increases, while the optimal yield of the PE decreases, as D increases.},
keywords={},
doi={},
ISSN={},
month={November},}

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TY - JOUR
TI - VLSI Yield Optimization Based on the Redundancy at the Sub-Processing-Element Level
T2 - IEICE TRANSACTIONS on Information
SP - 1471
EP - 1475
AU - Tianxu ZHAO
AU - Yue HAO
AU - Yong-Chang JIAO
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E84-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2001
AB - An optimal allocation model for the sub-processing-element (sub-PE) level redundancy is developed, which is solved by the genetic algorithms. In the allocation model, the average defect density D and the parameter δ are also considered in order to accurately analyze the element yield, where δ is defined as the ratio of the support circuit area to the total area of a PE. When the PE's area is imposed on the constraint, the optimal solutions of the model with different D and δ are calculated. The simulation results indicate that, for any fixed average defect density D, both the number of the optimal redundant sub-circuit added into a PE and the PE's yield decrease as δ increases. Moreover, for any fixed parameter δ, the number of the optimal redundant sub-circuit increases, while the optimal yield of the PE decreases, as D increases.
ER -