Full-chip leakage current estimation based on statistical sampling techniques

Shaobo Liu; Qinru Qiu; Qing Wu

doi:10.1145/1366110.1366203

Full-chip leakage current estimation based on statistical sampling techniques

Shaobo Liu, Qinru Qiu, Qing Wu

Research output: Chapter in Book/Entry/Poem › Conference contribution

4 Scopus citations

Abstract

In this paper, we propose statistical sampling techniques for estimating full-chip leakage current under process variations. The stratified random sampling procedures are used to estimate the mean and variance of the full-chip leakage, under intra-die and inter-die process variations. Statistical quantile estimation method is then applied to estimate the cumulative distribution function. Experimental results show that, comparing to simple random sampling, the proposed approaches improve the estimation speed by 2.7X, on average.

Original language	English (US)
Title of host publication	GLSVLSI 2008
Subtitle of host publication	Proceedings of the 2008 ACM Great Lakes Symposium on VLSI
Pages	391-394
Number of pages	4
DOIs	https://doi.org/10.1145/1366110.1366203
State	Published - 2008
Externally published	Yes
Event	GLSVLSI 2008: 18th ACM Great Lakes Symposium on VLSI 2008 - Orlando, FL, United States Duration: Mar 4 2008 → Mar 6 2008

Publication series

Name	Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI

Other

Other	GLSVLSI 2008: 18th ACM Great Lakes Symposium on VLSI 2008
Country/Territory	United States
City	Orlando, FL
Period	3/4/08 → 3/6/08

Keywords

Leakage estimation
Statistical sampling
VLSI

ASJC Scopus subject areas

General Engineering

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10.1145/1366110.1366203

Cite this

Liu, S, Qiu, Q & Wu, Q 2008, Full-chip leakage current estimation based on statistical sampling techniques. in GLSVLSI 2008: Proceedings of the 2008 ACM Great Lakes Symposium on VLSI. Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI, pp. 391-394, GLSVLSI 2008: 18th ACM Great Lakes Symposium on VLSI 2008, Orlando, FL, United States, 3/4/08. https://doi.org/10.1145/1366110.1366203

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title = "Full-chip leakage current estimation based on statistical sampling techniques",

abstract = "In this paper, we propose statistical sampling techniques for estimating full-chip leakage current under process variations. The stratified random sampling procedures are used to estimate the mean and variance of the full-chip leakage, under intra-die and inter-die process variations. Statistical quantile estimation method is then applied to estimate the cumulative distribution function. Experimental results show that, comparing to simple random sampling, the proposed approaches improve the estimation speed by 2.7X, on average.",

keywords = "Leakage estimation, Statistical sampling, VLSI",

author = "Shaobo Liu and Qinru Qiu and Qing Wu",

year = "2008",

doi = "10.1145/1366110.1366203",

language = "English (US)",

isbn = "9781595939999",

series = "Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI",

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booktitle = "GLSVLSI 2008",

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AU - Liu, Shaobo

AU - Qiu, Qinru

AU - Wu, Qing

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N2 - In this paper, we propose statistical sampling techniques for estimating full-chip leakage current under process variations. The stratified random sampling procedures are used to estimate the mean and variance of the full-chip leakage, under intra-die and inter-die process variations. Statistical quantile estimation method is then applied to estimate the cumulative distribution function. Experimental results show that, comparing to simple random sampling, the proposed approaches improve the estimation speed by 2.7X, on average.

AB - In this paper, we propose statistical sampling techniques for estimating full-chip leakage current under process variations. The stratified random sampling procedures are used to estimate the mean and variance of the full-chip leakage, under intra-die and inter-die process variations. Statistical quantile estimation method is then applied to estimate the cumulative distribution function. Experimental results show that, comparing to simple random sampling, the proposed approaches improve the estimation speed by 2.7X, on average.

KW - Leakage estimation

KW - Statistical sampling

KW - VLSI

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DO - 10.1145/1366110.1366203

M3 - Conference contribution

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SN - 9781595939999

T3 - Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI

SP - 391

EP - 394

BT - GLSVLSI 2008

T2 - GLSVLSI 2008: 18th ACM Great Lakes Symposium on VLSI 2008

Y2 - 4 March 2008 through 6 March 2008

ER -

Full-chip leakage current estimation based on statistical sampling techniques

Abstract

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Keywords

ASJC Scopus subject areas

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