Attend this webinar and learn how our team at Analog Value Ltd uses Mentor's tightly integrated Solido Variation Designer and Symphony Mixed-Signal Verification Platform solutions to enable fast variation-aware mixed-signal design and verification. We will illustrate how a time-domain 2-step ADC benefits from a fast and accurate variation-aware mixed-signal solution using machine learning techniques —to deliver the best-performing and highest-quality ADCs.
At advanced process nodes, it becomes increasingly challenging to obtain and measure the impact of statistical variation on the performance of an ADC using existing verification methodologies. Then, they need to run top-level mixed-signal simulations to determine and account for the impact of statistical variation on the ADC's overall performance measured in Effective Number of Bits, ENOB.
In addition, traditional nominal and corner simulation-based mixed-signal verification flows are slow and inefficient.
Design teams are left to extrapolate the impact of statistical variation and estimate the ADC design performance. Director of system architecture at Analog Value Ltd. Previously he was an analog design team leader at N-trig, developing the touch and pen solution until it was acquired by Microsoft. Tibi also held several senior roles where he was a principal engineer at PMC-Sierra. Electronic Design Automation.
Connectivity Electrification Autonomous Architecture.
High-Sigma Verification and Design
Contact IC Design. On-demand Web Seminar. View On-demand Web Seminar. Go URL. This Go URL can be used to navigate to this page. It is easier to copy and paste in an email than the long URL. Share This Resource. Overview At advanced process nodes, it becomes increasingly challenging to obtain and measure the impact of statistical variation on the performance of an ADC using existing verification methodologies. About the Presenter.
The correct environment configuration ensures designers are optimizing the accuracy and performance of their signoff verification flows. Automated waiver management enables designers to quickly and accurately identify error results that can be safely ignored during verification.
This is a preview of subscription content, log in to check access. Springer, NY Google Scholar. Hesterberg TC Advances in importance sampling. Hohenbichler M, Rackwitz R First-order concepts in system reliability. Li X Maximum-information storage system: concept, implementation and application. Li X Rethinking memory redundancy: optimal bit cell repair for maximum-information storage.
McConaghy T High-dimensional statistical modeling and analysis of custom integrated circuits. Niederreiter H Random number generation and quasi-Monte Carlo methods. Schenkel F et al Mismatch analysis and direct yield optimization by spec-wise linearization and feasibility-guided search. Singhee A, Rutenbar RA Statistical blockade: very fast statistical simulation and modeling of rare circuit events, and its application to memory design.
Solido Design Automation Inc. Synopsys Inc. Wilson EB Probable inference, the law of succession, and statistical inference. Saskatoon Canada 2. Saskatoon Canada 3. Saskatoon Canada. Personalised recommendations. Cite chapter How to cite? ENW EndNote. Buy options.This book targets custom IC designers who are encountering variation issues in their designs, especially for modern process nodes at 45nm and below, such as statistical process variations, environmental variations, and layout effects.2020 BMW Additive Manufacturing and 3D Printing Campus
High-Sigma Verification and Design. Variation-Aware Design. About this book Introduction This book targets custom IC designers who are encountering variation issues in their designs, especially for modern process nodes at 45nm and below, such as statistical process variations, environmental variations, and layout effects.
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 sigma statistical design and presents a novel sigma-driven corners flow, which is a fast, accurate, and scalable method suitable for sigma design and verification.
Variation-Aware Design: A Hands-on Field Guide
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. Solido Design Automation, Inc.
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Variation aware design of custom integrated circuits a hands on field guide. Upcoming SlideShare. Like this document? Why not share! Embed Size px. Start on. Show related SlideShares at end. WordPress Shortcode. Springer Follow. Published in: TechnologyBusiness. Full Name Comment goes here. Are you sure you want to Yes No. The more time you have before the deadline - the less price of the order you will have.
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The low time impact on the overall optimization processes enables IC designers to perform yield optimization with the most accurate yield estimation method, MC simulations using foundry statistical device models considering local and global variations.
Yield-Aware Analog IC Design and Optimization in Nanometer-scale Technologies
In addition to describing a newly developed yield estimation technique, the authors also provide detailed background on automatic analog IC sizing and optimization. Describes a new yield estimation methodology to reduce the time impact caused by Monte Carlo simulations, enabling its adoption in analog integrated circuits sizing and optimization processes with population-based algorithms; Enables designers to reduce the number of redesign iterations, by considering the robustness of solutions at early stages of the analog IC design flow; Includes detailed background on automatic analog IC sizing and optimization.
Buy options.View All Events. IC designers using advanced nodes are acutely aware of how variation effects in the silicon itself are causing increased analysis and design efforts in order to yield chips at acceptable levels.
Four authors from Solido are so passionate about this topic that they combined their years of experience into a book that I had a chance to read and review. Analog, AMS and even high-speed digital designers would benefit from the design ideas suggested in this book. The book has seven chapter that propose a variation-aware flow as shown below that is both fast and accurate:.
Chapter 1: Introduction IC designers have been using combinations of Process, Voltage Temperature PVT corners for years to determine how their design will work under varying conditions. The third step in the variation-aware flow is an automated one where worst-case corners are automatically extracted for your specific design and process called Fast PVT, in contrast to older methodologies where a designer would guess at which PVT corners to use as worst-case or simply create hundreds to thousands of corners for analysis.
This is a precursor to chapters 4 and 5, the statistical chapters. Chapter 4: Three-sigma Statistical Analysis To design with target yields of two to three sigma 95 to Comparison of three-sigma approaches. Chapter 5: High-sigma Statistical Analysis To achieve high sigma analysis several possible approaches are considered:. Distribution of flip-flop setup time.
Data is from a Monte Carlo run with 1, samples. Chapter 6: Variation-aware Design To actually change transistor sizes in your design so that it yields optimally across variation there are several design methods:. A tool to help integrate manual and automated design should be able to guide the user towards making the greatest benefit design choices first. Older, brute-force Monte Carlo approaches take too much simulation time, and may not be catching the worst-case conditions needed to ensure that your IC design is tolerant to variations.
I appreciated that the authors made this a field guide showing many approaches and sharing their actual design experience, rather than an EDA tool product pitch. Guests have limited access. Join our community today! You are currently viewing SemiWiki as a guest which gives you limited access to the site.
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