NDLI: Performance-Oriented Statistical Parameter Reduction of Parameterized Systems via Reduced Rank Regression

Content Provider	IEEE Xplore Digital Library
Author	Zhuo Feng Peng Li
Copyright Year	2006
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX (Zhuo Feng; Peng Li)
Abstract	Process variations in modern VLSI technologies are growing in both magnitude and dimensionality. To assess performance variability, complex simulation and performance models parameterized in a high-dimensional process variation space are desired. However, the high parameter dimensionality, imposed by a large number of variation sources encountered in modern technologies, can introduce significant complexion in circuit analysis and may even render performance variability analysis completely intractable. We address the challenge brought by high-dimensional process variations via a new performance-oriented parameter dimension reduction technique. The basic premise behind our approach is that the dimensionality of performance variability is determined not only by the statistical characteristics of the underlying process variables, but also by the structural information imposed by a given design. Using the powerful reduced rank regression (RRR) and its extension as a vehicle for variability modeling, we are able to systematically identify statistically significant reduced parameter sets and compute not only reduced-parameter but also reduced-parameter-order models that are far more efficient than what was possible before. For a variety of interconnect modeling problems, it is shown that the proposed parameter reduction technique can provide more than one order of magnitude reduction in parameter dimensionality. Such parameter reduction immediately leads to reduced simulation cost in sampling-based performance analysis, and more importantly, highly efficient parameterized interconnect reduced order models. As a general parameter dimension reduction methodology, it is anticipated that the proposed technique is broadly applicable to a variety of statistical circuit modeling problems, thereby offering a useful framework for controlling the complexity of statistical circuit analysis
Starting Page	868
Ending Page	875
File Size	10877492
Page Count	8
File Format	PDF
ISBN	1595933891
ISSN	10923152
DOI	10.1109/ICCAD.2006.320091
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-11-05
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Association for Computing Machinery, Inc. (ACM)
Subject Keyword	Space technology Power system modeling Circuit simulation Circuit analysis Performance analysis Integrated circuit interconnections Very large scale integration Vehicles Power system interconnection Analytical models
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Computer Science Applications Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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