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Synthesis of Finite State Machines

Logic Optimization

  • Book
  • © 1997

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Table of contents (12 chapters)

  1. From Symbolic to Logic Representations

  2. Constrained Encoding

  3. Generalized Prime Implicants

  4. Implicit Techniques for Encoding

  5. Conclusions

Keywords

About this book

Synthesis of Finite State Machines: Logic Optimization is the second in a set of two monographs devoted to the synthesis of Finite State Machines (FSMs). The first volume, Synthesis of Finite State Machines: Functional Optimization, addresses functional optimization, whereas this one addresses logic optimization. The result of functional optimization is a symbolic description of an FSM which represents a sequential function chosen from a collection of permissible candidates. Logic optimization is the body of techniques for converting a symbolic description of an FSM into a hardware implementation. The mapping of a given symbolic representation into a two-valued logic implementation is called state encoding (or state assignment) and it impacts heavily area, speed, testability and power consumption of the realized circuit.
The first part of the book introduces the relevant background, presents results previously scattered in the literature on the computational complexity of encoding problems, and surveys in depth old and new approaches to encoding in logic synthesis.
The second part of the book presents two main results about symbolic minimization; a new procedure to find minimal two-level symbolic covers, under face, dominance and disjunctive constraints, and a unified frame to check encodability of encoding constraints and find codes of minimum length that satisfy them.
The third part of the book introduces generalized prime implicants (GPIs), which are the counterpart, in symbolic minimization of two-level logic, to prime implicants in two-valued two-level minimization. GPIs enable the design of an exact procedure for two-level symbolic minimization, based on a covering step which is complicated by the need to guarantee encodability of the final cover. A new efficient algorithm to verify encodability of a selected cover is presented. If a cover is not encodable, it is shown how to augment itminimally until an encodable superset of GPIs is determined. To handle encodability the authors have extended the frame to satisfy encoding constraints presented in the second part.
The covering problems generated in the minimization of GPIs tend to be very large. Recently large covering problems have been attacked successfully by representing the covering table with binary decision diagrams (BDD). In the fourth part of the book the authors introduce such techniques and extend them to the case of the implicit minimization of GPIs, where the encodability and augmentation steps are also performed implicitly.
Synthesis of Finite State Machines: Logic Optimization will be of interest to researchers and professional engineers who work in the area of computer-aided design of integrated circuits.

Authors and Affiliations

  • University of California, Berkeley, USA

    Tiziano Villa, Robert K. Brayton, Alberto Sangiovanni-Vincentelli

  • Intel Corporation, USA

    Timothy Kam

Bibliographic Information

  • Book Title: Synthesis of Finite State Machines

  • Book Subtitle: Logic Optimization

  • Authors: Tiziano Villa, Timothy Kam, Robert K. Brayton, Alberto Sangiovanni-Vincentelli

  • DOI: https://doi.org/10.1007/978-1-4615-6155-2

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Science+Business Media New York 1997

  • Hardcover ISBN: 978-0-7923-9892-9Published: 30 April 1997

  • Softcover ISBN: 978-1-4613-7821-1Published: 04 October 2012

  • eBook ISBN: 978-1-4615-6155-2Published: 06 December 2012

  • Edition Number: 1

  • Number of Pages: XIII, 381

  • Topics: Circuits and Systems, Electrical Engineering, Computer-Aided Engineering (CAD, CAE) and Design

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