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Stochastic Computing: Techniques and Applications

  • A comprehensive volume containing tutorial, design methodologies, and applications: material previously not available in one place.
  • Provides a contemporary view of the field of stochastic computing, as seen from the perspective of its leading researchers
  • A chapter on the history of stochastic computing - will provide context to the recent work

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-xvi
  2. Introduction to Stochastic Computing

    • Vincent C. Gaudet, Warren J. Gross, Kenneth C. Smith
    Pages 1-11
  3. Origins of Stochastic Computing

    • Brian R. Gaines
    Pages 13-37
  4. Tutorial on Stochastic Computing

    • Chris Winstead
    Pages 39-76
  5. Accuracy and Correlation in Stochastic Computing

    • Armin Alaghi, Paishun Ting, Vincent T. Lee, John P. Hayes
    Pages 77-102
  6. Synthesis of Polynomial Functions

    • Marc Riedel, Weikang Qian
    Pages 103-120
  7. Generating Stochastic Bitstreams

    • Hsuan Hsiao, Jason Anderson, Yuko Hara-Azumi
    Pages 137-152
  8. RRAM Solutions for Stochastic Computing

    • Phil Knag, Siddharth Gaba, Wei Lu, Zhengya Zhang
    Pages 153-164
  9. Spintronic Solutions for Stochastic Computing

    • Xiaotao Jia, You Wang, Zhe Huang, Yue Zhang, Jianlei Yang, Yuanzhuo Qu et al.
    Pages 165-183
  10. Brain-Inspired Computing

    • Naoya Onizawa, Warren J. Gross, Takahiro Hanyu
    Pages 185-199
  11. Stochastic Decoding of Error-Correcting Codes

    • François Leduc-Primeau, Saied Hemati, Vincent C. Gaudet, Warren J. Gross
    Pages 201-215

About this book

This book covers the history and recent developments of stochastic computing. Stochastic computing (SC) was first introduced in the 1960s for logic circuit design, but its origin can be traced back to von Neumann's work on probabilistic logic. In SC, real numbers are encoded by random binary bit streams, and information is carried on the statistics of the binary streams. SC offers advantages such as hardware simplicity and fault tolerance. Its promise in data processing has been shown in applications including neural computation, decoding of error-correcting codes, image processing, spectral transforms and reliability analysis.

There are three main parts to this book. The first part, comprising Chapters 1 and 2, provides a history of the technical developments in stochastic computing and a tutorial overview of the field for both novice and seasoned stochastic computing researchers. In the second part, comprising Chapters 3 to 8, we review both well-established and emerging design approaches for stochastic computing systems, with a focus on accuracy, correlation, sequence generation, and synthesis. The last part, comprising Chapters 9 and 10, provides insights into applications in machine learning and error-control coding.


Reviews

“The editors have done a good job in selecting and organizing the chapters to present a clear and convenient introduction to a computational approach that … will be new and inspiring to many readers.” (H. Van Dyke Parunak, Computing Reviews, October 04, 2019)

Editors and Affiliations

  • Department of Electrical and Computer Engineering, McGill University, Montréal, Canada

    Warren J. Gross

  • ECE Department, University of Waterloo, Waterloo, Canada

    Vincent C. Gaudet

About the editors

Warren J. Gross received the B.A.Sc. degree in electrical engineering from the University of Waterloo, Waterloo, ON, Canada, in 1996, and the M.A.Sc. and Ph.D. degrees from the University of Toronto, Toronto, ON, Canada, in 1999 and 2003, respectively. He is a Professor and Louis-Ho Faculty Scholar in Technological Innovation in the Department of Electrical and Computer Engineering, McGill University, Montreal, QC, Canada.  He currently serves as Chair of the Department. His research interests are in the design and implementation of signal processing systems and custom computer architectures.

Dr. Gross served as the Chair for the IEEE Signal Processing Society Technical Committee on Design and Implementation of Signal Processing Systems. He served as the General Co-Chair for the IEEE GlobalSIP 2017 and the IEEE SiPS 2017 and the Technical Program Co-Chair for SiPS 2012. He also served as an Organizer for the Workshop on Polar Coding in Wireless Communications at WCNC 2018 and WCNC 2017, the Symposium on Data Flow Algorithms and Architecture  for Signal Processing Systems (GlobalSIP 2014), and the IEEE ICC 2012 Workshop on Emerging Data Storage Technologies. He served as an Associate Editor for the IEEE Transactions on Signal Processing and as a Senior Area Editor. He is a Licensed Professional Engineer in the Province of Ontario.


Vincent Gaudet received the B.Sc. in Computer Engineering from the University of Manitoba in 1995, the M.A.Sc. from the University of Toronto in 1997, and the Ph.D. from the University of Toronto in 2003. Since 2010 he has been with the Department of Electrical and Computer Engineering at the University of Waterloo. He previously held appointments as a faculty member at the University of Alberta (2002-2010) and as a Research Associate at Télécom-Bretagne in Brest, France (2002). In 2008-2009 he was on sabbatical leave at Northeastern University in Boston, MA, and atTohoku University in Sendai, Japan.

His research interests focus on energy-efficient microelectronic circuits for information processing, and more specifically, on high-performance circuits for graph-based decoding of error-control codes such as Turbo and Low-Density Parity-Check (LDPC) codes. He is also interested in stochastic computing and multiple-valued logic. He has taught several courses in analog and digital microelectronic circuit design, at the undergraduate and graduate levels, and previously served as the Associate Chair for Undergraduate Studies (2013-2016).

Prof. Gaudet is a Senior Member of the IEEE and is licensed as a Professional Engineer. He has served as Associate Editor for the IEEE Transactions on Circuits and Systems, Parts I and II, and is a Technical Editor for the IEEE International Solid-State Circuits Conference. He was previously Chair (2016-2017) of the IEEE Computer Society Technical Committee on Multiple-Valued Logic and is an elected member (2013-2018) of the IEEE Signal Processing Society Technical Committee on Design and Implementation of Signal-Processing Systems. He was the Program Chair for the 2012 IEEE International Symposium on Multiple-Valued Logic (ISMVL) in Victoria, BC, and General Chair of ISMVL 2015 in Waterloo. He was the recipient of the 2009 Petro Canada Young Innovator Award and the Fall 2015 EngSoc Teaching Excellence Award. He has been serving as Department Chair since July 2016.

Bibliographic Information

  • Book Title: Stochastic Computing: Techniques and Applications

  • Editors: Warren J. Gross, Vincent C. Gaudet

  • DOI: https://doi.org/10.1007/978-3-030-03730-7

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer Nature Switzerland AG 2019

  • Hardcover ISBN: 978-3-030-03729-1Published: 04 March 2019

  • eBook ISBN: 978-3-030-03730-7Published: 18 February 2019

  • Edition Number: 1

  • Number of Pages: XVI, 215

  • Number of Illustrations: 99 b/w illustrations, 34 illustrations in colour

  • Topics: Circuits and Systems, Logic Design, Probability Theory and Stochastic Processes

Buy it now

Buying options

eBook USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book USD 99.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access