Dynamic Reconfiguration in Real-Time Systems : Energy, Performance, and Thermal Perspectives

Weixun Wang

ISBN 10: 1461402778 / ISBN 13: 9781461402770

Published by Springer New York, Springer US, 2012

About this Item

Druck auf Anfrage Neuware - Printed after ordering - Given the widespread use of real-time multitasking systems, there are tremendous optimization opportunities if reconfigurable computing can be effectively incorporated while maintaining performance and other design constraints of typical applications. The focus of this book is to describe the dynamic reconfiguration techniques that can be safely used in real-time systems. This book provides comprehensive approaches by considering synergistic effects of computation, communication as well as storage together to significantly improve overall performance, power, energy and temperature. Provides a comprehensive introduction to optimization and dynamic reconfiguration techniques in real-time embedded systems; Covers state-of-the-art techniques and ongoing research in reconfigurable architectures;Focuses on algorithms tuned for dynamic reconfiguration techniques in real-time systems; Provides reference for anyone designing low-power systems, energy-/temperature-constrained devices, and power-performance efficient systems which execute tasks with timing constraints.

Seller Inventory # 9781461402770

Bibliographic Details

• Title: Dynamic Reconfiguration in Real-Time Systems : Energy, Performance, and Thermal Perspectives
• Publisher: Springer New York, Springer US
• Publication Date: 2012
• Language: English
• ISBN 10: 1461402778
• ISBN 13: 9781461402770
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 17D millimeters 241 millimeters width by 160 millimeters height by 17 millimeters depth
• Weight: 529 grams

About this title

Synopsis

Given the widespread use of real-time multitasking systems, there are tremendous optimization opportunities if reconfigurable computing can be effectively incorporated while maintaining performance and other design constraints of typical applications. The focus of this book is to describe the dynamic reconfiguration techniques that can be safely used in real-time systems. This book provides comprehensive approaches by considering synergistic effects of computation, communication as well as storage together to significantly improve overall performance, power, energy and temperature. 

About the Author

Weixun Wang is a software engineer in Amazon.com, Seattle,WA. He received his B.E. degree in software engineering from the Software Institute, Nanjing University, China, in 2007, and a Ph.D. degree in computer engineering from the University of Florida in 2011. His research interests include energy-aware computing, design automation of embedded systems, computer architecture, reconfigurable architectures and real-time scheduling. He has published more than 10 papers in these fields. He is a member of IEEE.

Prabhat Mishra is an Associate Professor in the Department of Computer and Information Science and Engineering (CISE) at the University of Florida. His research interests include design automation of embedded systems, hardware/software verification, VLSI CAD, and low-power reconfigurable architectures. He received his B.E. from Jadavpur University, Kolkata, in 1994, M.Tech. from the Indian Institute of Technology, Kharagpur in 1996, and Ph.D. from the University of California, Irvine, in 2004 - all in Computer Science. He has published two books (Springer 2005 and MK 2008), nine book chapters and more than 80 research articles in premier journals and conferences. He is a senior member of ACM and a senior member of IEEE.

Sanjay Ranka is a Professor in the Department of Computer Information Science and Engineering at University of Florida. His current research interests are energy efficient computing, high performance computing, data mining and informatics. Sanjay has also held positions as a tenured faculty member at Syracuse University and as a researcher/visitor at IBM T.J. Watson Research Labs and Hitachi America Limited. Sanjay earned his Ph.D. (Computer Science) from the University of Minnesota and a B. Tech. in Computer Science from IIT, Kanpur, India. He has coauthored two books: Elements of Neural Networks (MIT Press) and Hypercube Algorithm (Springer Verlag), 75 journal articles and 125 refereed conference articles. He is a fellow of the IEEE and AAAS.