Application of Correlation-Based Regression Analysis for Improvement of Power Distribution Network

Shiho HAGIWARA; Takumi UEZONO; Takashi SATO; Kazuya MASU

doi:10.1093/ietfec/e91-a.4.951

Application of Correlation-Based Regression Analysis for Improvement of Power Distribution Network

Shiho HAGIWARA, Takumi UEZONO, Takashi SATO, Kazuya MASU

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Stochastic approaches for effective power distribution network optimization are proposed. Considering node voltages obtained using dynamic voltage drop analysis as sample variables, multi-variate regression is conducted to optimize clock timing metrics, such as clock skew or jitter. Aggregate correlation coefficient (ACC) which quantifies connectivity between different chip regions is defined in order to find a possible insufficiency in wire connections of a power distribution network. Based on the ACC, we also propose a procedure using linear regression to find the most effective region for improving clock timing metrics. By using the proposed procedure, effective fixing point were obtained two orders faster than by using brute force circuit simulation.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E91-A No.4 pp.951-956

Publication Date: 2008/04/01

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Online ISSN: 1745-1337

DOI: 10.1093/ietfec/e91-a.4.951

Type of Manuscript: Special Section PAPER (Special Section on Selected Papers from the 20th Workshop on Circuits and Systems in Karuizawa)

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Shiho HAGIWARA, Takumi UEZONO, Takashi SATO, Kazuya MASU, "Application of Correlation-Based Regression Analysis for Improvement of Power Distribution Network" in IEICE TRANSACTIONS on Fundamentals, vol. E91-A, no. 4, pp. 951-956, April 2008, doi: 10.1093/ietfec/e91-a.4.951.
Abstract: Stochastic approaches for effective power distribution network optimization are proposed. Considering node voltages obtained using dynamic voltage drop analysis as sample variables, multi-variate regression is conducted to optimize clock timing metrics, such as clock skew or jitter. Aggregate correlation coefficient (ACC) which quantifies connectivity between different chip regions is defined in order to find a possible insufficiency in wire connections of a power distribution network. Based on the ACC, we also propose a procedure using linear regression to find the most effective region for improving clock timing metrics. By using the proposed procedure, effective fixing point were obtained two orders faster than by using brute force circuit simulation.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.4.951/_p

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@ARTICLE{e91-a_4_951,
author={Shiho HAGIWARA, Takumi UEZONO, Takashi SATO, Kazuya MASU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Application of Correlation-Based Regression Analysis for Improvement of Power Distribution Network},
year={2008},
volume={E91-A},
number={4},
pages={951-956},
abstract={Stochastic approaches for effective power distribution network optimization are proposed. Considering node voltages obtained using dynamic voltage drop analysis as sample variables, multi-variate regression is conducted to optimize clock timing metrics, such as clock skew or jitter. Aggregate correlation coefficient (ACC) which quantifies connectivity between different chip regions is defined in order to find a possible insufficiency in wire connections of a power distribution network. Based on the ACC, we also propose a procedure using linear regression to find the most effective region for improving clock timing metrics. By using the proposed procedure, effective fixing point were obtained two orders faster than by using brute force circuit simulation.},
keywords={},
doi={10.1093/ietfec/e91-a.4.951},
ISSN={1745-1337},
month={April},}

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TY - JOUR
TI - Application of Correlation-Based Regression Analysis for Improvement of Power Distribution Network
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 951
EP - 956
AU - Shiho HAGIWARA
AU - Takumi UEZONO
AU - Takashi SATO
AU - Kazuya MASU
PY - 2008
DO - 10.1093/ietfec/e91-a.4.951
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 4
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - April 2008
AB - Stochastic approaches for effective power distribution network optimization are proposed. Considering node voltages obtained using dynamic voltage drop analysis as sample variables, multi-variate regression is conducted to optimize clock timing metrics, such as clock skew or jitter. Aggregate correlation coefficient (ACC) which quantifies connectivity between different chip regions is defined in order to find a possible insufficiency in wire connections of a power distribution network. Based on the ACC, we also propose a procedure using linear regression to find the most effective region for improving clock timing metrics. By using the proposed procedure, effective fixing point were obtained two orders faster than by using brute force circuit simulation.
ER -