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Stochastic Computing: Techniques and Applications

  • Warren J. Gross
  • Vincent C. Gaudet

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Vincent C. Gaudet, Warren J. Gross, Kenneth C. Smith
    Pages 1-11
  3. Brian R. Gaines
    Pages 13-37
  4. Chris Winstead
    Pages 39-76
  5. Armin Alaghi, Paishun Ting, Vincent T. Lee, John P. Hayes
    Pages 77-102
  6. Marc Riedel, Weikang Qian
    Pages 103-120
  7. Hsuan Hsiao, Jason Anderson, Yuko Hara-Azumi
    Pages 137-152
  8. Phil Knag, Siddharth Gaba, Wei Lu, Zhengya Zhang
    Pages 153-164
  9. Xiaotao Jia, You Wang, Zhe Huang, Yue Zhang, Jianlei Yang, Yuanzhuo Qu et al.
    Pages 165-183
  10. Naoya Onizawa, Warren J. Gross, Takahiro Hanyu
    Pages 185-199
  11. François Leduc-Primeau, Saied Hemati, Vincent C. Gaudet, Warren J. Gross
    Pages 201-215

About this book

Introduction

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.


Keywords

Stochastic computing Probabilistic computation Stochastic logic Approximate computing Fault-tolerant computing Randomized bit-streams VLSI Logic functions Logic gates VLSI CAD

Editors and affiliations

  • Warren J. Gross
    • 1
  • Vincent C. Gaudet
    • 2
  1. 1.Department of Electrical and Computer EngineeringMcGill UniversityMontréalCanada
  2. 2.ECE DepartmentUniversity of WaterlooWaterlooCanada

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-03730-7
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-030-03729-1
  • Online ISBN 978-3-030-03730-7
  • Buy this book on publisher's site