Variation-aware Design of Custom Integrated Circuits : A Hands-on Field Guide
Language: English
Published by Springer, 2012
- Hardcover
- Used
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- Title
- Variation-aware Design of Custom Integrated Circuits : A Hands-on Field Guide
- Author
- Mcconaghy, Trent; Breen, Kristopher; Dyck, Jeffrey; Gupta, Amit
- Publisher
- Springer
- Publication year
- 2012
- Condition
- As New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 146142268X
- ISBN 13
- 9781461422686
"Synopsis" may belong to another edition of this title.
From the Back Cover
- Documents the state-of-the-art in industrial-scale, variation-aware, custom integrated circuit design
- Describes the capabilities and benefits of modern Variation-Aware tools and shows how to benchmark such tools during evaluations
- Discusses the algorithms used in state-of-the-art Variation-Aware CAD tools and explains the algorithms' behaviors, experimental results and limitations
- Reviews the most important concepts in variation-aware design, including types of variables and variation, useful variation-aware design terminology, and an overview and comparison of high-level design flows.
- Describes and compares a suite of approaches and flows for PVT corner-driven design and verification. Presents Fast PVT, a novel, confidence-driven global optimization technique for PVT corner extraction and verification that is both rapid and reliable.
- Presents a visually-oriented overview of probability density functions, Monte Carlo sampling, and yield estimation.
- Describes a suite of methods used for 2-3 sigma statistical design and presents a novel sigma-driven corners flow, which is a fast, accurate, and scalable method suitable for 2-3 sigma design and verification.
- Describes and compares high-sigma design and verification techniques and presents a novel technique for high-sigma statistical corner extraction and verification, demonstrating its fast, accurate, scalable, and verifiable qualities across a variety of applications.
- Compares manual design and automated sizing and introduces an integrated approach to aid the sizing step in PVT, 3σ statistical and high-sigma statistical design.
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