IEICE TRANSACTIONS on Fundamentals
Power Distribution Network Optimization for Timing Improvement with Statistical Noise Model and Timing Analysis
Summary :
We propose an optimization method for power distribution network that explicitly deals with timing. We have found and focused on the facts that decoupling capacitance (decap) does not necessarily improve gate delay depending on the switching timing within a cycle and that power wire expansion may locally degrade the voltage. To resolve the above facts, we devised an efficient sensitivity calculation of timing to decap size and power wire width for guiding optimization. The proposed method, which is based on statistical noise modeling and timing analysis, accelerates sensitivity calculation with an approximation and adjoint sensitivity analysis. Experimental results show that decap allocation based on the sensitivity analysis efficiently minimizes the worst-case circuit delay within a given decap budget. Compared to the maximum decap placement, the delay improvement due to decap increases by 3.13% even while the total amount of decaps is reduced to 40%. The wire sizing with the proposed method also efficiently reduces required wire resource necessary to attain the same circuit delay by 11.5%.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E95-A No.12 pp.2261-2271
- Publication Date
- 2012/12/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E95.A.2261
- Type of Manuscript
- Special Section PAPER (Special Section on VLSI Design and CAD Algorithms)
- Category
- Device and Circuit Modeling and Analysis
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Takashi ENAMI, Takashi SATO, Masanori HASHIMOTO, "Power Distribution Network Optimization for Timing Improvement with Statistical Noise Model and Timing Analysis" in IEICE TRANSACTIONS on Fundamentals,
vol. E95-A, no. 12, pp. 2261-2271, December 2012, doi: 10.1587/transfun.E95.A.2261.
Abstract: We propose an optimization method for power distribution network that explicitly deals with timing. We have found and focused on the facts that decoupling capacitance (decap) does not necessarily improve gate delay depending on the switching timing within a cycle and that power wire expansion may locally degrade the voltage. To resolve the above facts, we devised an efficient sensitivity calculation of timing to decap size and power wire width for guiding optimization. The proposed method, which is based on statistical noise modeling and timing analysis, accelerates sensitivity calculation with an approximation and adjoint sensitivity analysis. Experimental results show that decap allocation based on the sensitivity analysis efficiently minimizes the worst-case circuit delay within a given decap budget. Compared to the maximum decap placement, the delay improvement due to decap increases by 3.13% even while the total amount of decaps is reduced to 40%. The wire sizing with the proposed method also efficiently reduces required wire resource necessary to attain the same circuit delay by 11.5%.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E95.A.2261/_p
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@ARTICLE{e95-a_12_2261,
author={Takashi ENAMI, Takashi SATO, Masanori HASHIMOTO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Power Distribution Network Optimization for Timing Improvement with Statistical Noise Model and Timing Analysis},
year={2012},
volume={E95-A},
number={12},
pages={2261-2271},
abstract={We propose an optimization method for power distribution network that explicitly deals with timing. We have found and focused on the facts that decoupling capacitance (decap) does not necessarily improve gate delay depending on the switching timing within a cycle and that power wire expansion may locally degrade the voltage. To resolve the above facts, we devised an efficient sensitivity calculation of timing to decap size and power wire width for guiding optimization. The proposed method, which is based on statistical noise modeling and timing analysis, accelerates sensitivity calculation with an approximation and adjoint sensitivity analysis. Experimental results show that decap allocation based on the sensitivity analysis efficiently minimizes the worst-case circuit delay within a given decap budget. Compared to the maximum decap placement, the delay improvement due to decap increases by 3.13% even while the total amount of decaps is reduced to 40%. The wire sizing with the proposed method also efficiently reduces required wire resource necessary to attain the same circuit delay by 11.5%.},
keywords={},
doi={10.1587/transfun.E95.A.2261},
ISSN={1745-1337},
month={December},}
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TY - JOUR
TI - Power Distribution Network Optimization for Timing Improvement with Statistical Noise Model and Timing Analysis
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2261
EP - 2271
AU - Takashi ENAMI
AU - Takashi SATO
AU - Masanori HASHIMOTO
PY - 2012
DO - 10.1587/transfun.E95.A.2261
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E95-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2012
AB - We propose an optimization method for power distribution network that explicitly deals with timing. We have found and focused on the facts that decoupling capacitance (decap) does not necessarily improve gate delay depending on the switching timing within a cycle and that power wire expansion may locally degrade the voltage. To resolve the above facts, we devised an efficient sensitivity calculation of timing to decap size and power wire width for guiding optimization. The proposed method, which is based on statistical noise modeling and timing analysis, accelerates sensitivity calculation with an approximation and adjoint sensitivity analysis. Experimental results show that decap allocation based on the sensitivity analysis efficiently minimizes the worst-case circuit delay within a given decap budget. Compared to the maximum decap placement, the delay improvement due to decap increases by 3.13% even while the total amount of decaps is reduced to 40%. The wire sizing with the proposed method also efficiently reduces required wire resource necessary to attain the same circuit delay by 11.5%.
ER -
English
