Embedded Memories for Nano-Scale VLSIs
Embedded Memories for Nano-Scale VLSIs provides a comprehensive and in-depth view on the state-of-the-art embedded memory technologies. The material covers key technology attributes and advanced design techniques in nano-scale VLSI design. It also discuss
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Kevin Zhang Editor
Embedded Memories for Nano-Scale VLSIs 1 23
Embedded Memories for Nano-Scale VLSIs
Series on Integrated Circuits and Systems Series Editor:
Anantha Chandrakasan Massachusetts Institute of Technology Cambridge, Massachusetts
Embedded Memories for Nano-Scale VLSIs Kevin Zhang (Ed.) ISBN 978-0-387-88496-7 Carbon Nanotube Electronics Ali Javey and Jing Kong (Eds.) ISBN 978-0-387-36833-7 Wafer Level 3-D ICs Process Technology Chuan Seng Tan, Ronald J. Gutmann, and L. Rafael Reif (Eds.) ISBN 978-0-387-76532-7 Adaptive Techniques for Dynamic Processor Optimization: Theory and Practice Alice Wang and Samuel Naffziger (Eds.) ISBN 978-0-387-76471-9 mm-Wave Silicon Technology: 60 GHz and Beyond Ali M. Niknejad and Hossein Hashemi (Eds.) ISBN 978-0-387-76558-7 Ultra Wideband: Circuits, Transceivers, and Systems Ranjit Gharpurey and Peter Kinget (Eds.) ISBN 978-0-387-37238-9 Creating Assertion-Based IP Harry D. Foster and Adam C. Krolnik ISBN 978-0-387-36641-8 Design for Manufacturability and Statistical Design: A Constructive Approach Michael Orshansky, Sani R. Nassif, and Duane Boning ISBN 978-0-387-30928-6 Low Power Methodology Manual: For System-on-Chip Design Michael Keating, David Flynn, Rob Aitken, Alan Gibbons, and Kaijian Shi ISBN 978-0-387-71818-7 Modern Circuit Placement: Best Practices and Results Gi-Joon Nam and Jason Cong ISBN 978-0-387-36837-5 CMOS Biotechnology Hakho Lee, Donhee Ham and Robert M. Westervelt ISBN 978-0-387-36836-8 Continued after index
Kevin Zhang Editor
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Editor Kevin Zhang Intel Corporation 2501 NW. 229th Ave. Hillsboro, OR 97124 USA [email protected]
ISBN 978-0-387-88496-7 e-ISBN 978-0-387-88497-4 DOI 10.1007/978-0-387-88497-4 Library of Congress Control Number: 2008936472 c Springer Science+Business Media, LLC 2009 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper springer.com
Contents
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kevin Zhang 2 Embedded Memory Architecture for Low-Power Application Processor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hoi Jun Yoo and Donghyun Kim
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3 Embedded SRAM Design in Nanometer-Scale Technologies . . . . . . . . . . 39 Hiroyuki Yamauchi 4
