Logic optimization

Logic optimization, a part of logic synthesis in electronics, is the process of finding an equivalent representation of the specified logic circuit under one or more specified constraints. Generally the circuit is constrained to minimum chip area meeting a prespecified delay.

Introduction

With the advent of logic synthesis, one of the biggest challenges faced by the electronic design automation (EDA) industry was to find the best netlist representation of the given design description. While two-level logic optimization had long existed in the form of the Quine–McCluskey algorithm, later followed by the Espresso heuristic logic minimizer, the rapidly improving chip densities, and the wide adoption of HDLs for circuit description, formalized the logic optimization domain as it exists today.

Today, logic optimization is divided into various categories:

Based on circuit representation

  • Two-level logic optimization
  • Multi-level logic optimization

Based on circuit characteristics

  • Sequential logic optimization
  • Combinational logic optimization

Based on type of execution

  • Graphical optimization methods
  • Tabular optimization methods
  • Algebraic optimization methods

While a two-level circuit representation of circuits strictly refers to the flattened view of the circuit in terms of SOPs (sum-of-products) which is more applicable to a PLA implementation of the design a multi-level representation is a more generic view of the circuit in terms of arbitrarily connected SOPs, POSs (product-of-sums), factored form etc. Logic optimization algorithms generally work either on the structural (SOPs, factored form) or functional (BDDs, ADDs) representation of the circuit.

Two-level versus multi-level representations

If we have two functions F1 and F2:

The above 2-level representation takes six product terms and 24 transistors in CMOS Rep.

A functionally equivalent representation in multilevel can be:

P = B + C.
F1 = AP + AD.
F2 = A'P + A'E.

While the number of levels here is 3, the total number of product terms and literals reduce because of the sharing of the term B + C.

Similarly, we distinguish between sequential and combinational circuits, whose behavior can be described in terms of finite-state machine state tables/diagrams or by Boolean functions and relations respectively.

Circuit minimization in Boolean algebra

In Boolean algebra, circuit minimization is the problem of obtaining the smallest logic circuit (Boolean formula) that represents a given Boolean function or truth table. The unbounded circuit minimization problem was long-conjectured to be -complete, a result finally proved in 2008,[1] but there are effective heuristics such as Karnaugh maps and the Quine–McCluskey algorithm that facilitate the process.

Purpose

The problem with having a complicated circuit (i.e. one with many elements, such as logic gates) is that each element takes up physical space in its implementation and costs time and money to produce in itself. Circuit minimization may be one form of logic optimization used to reduce the area of complex logic in integrated circuits.

Example

While there are many ways to minimize a circuit, this is an example that minimizes (or simplifies) a boolean function. Note that the boolean function carried out by the circuit is directly related to the algebraic expression from which the function is implemented.[2] Consider the circuit used to represent . It is evident that two negations, two conjunctions, and a disjunction are used in this statement. This means that to build the circuit one would need two inverters, two AND gates, and an OR gate.

We can simplify (minimize) the circuit by applying logical identities or using intuition. Since the example states that A is true when B is false or the other way around, we can conclude that this simply means . In terms of logical gates, inequality simply means an XOR gate (exclusive or). Therefore, . Then the two circuits shown below are equivalent:

You can additionally check the correctness of the result using a truth table.

Graphical two-level logic minimization methods

Graphical minimization methods for two-level logic include:

See also

References

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  5. Aiken, Howard H.; Blaauw, Gerrit; Burkhart, William; Burns, Robert J.; Cali, Lloyd; Canepa, Michele; Ciampa, Carmela M.; Coolidge, Jr., Charles A.; Fucarile, Joseph R.; Gadd, Jr., J. Orten; Gucker, Frank F.; Harr, John A.; Hawkins, Robert L.; Hayes, Miles V.; Hofheimer, Richard; Hulme, William F.; Jennings, Betty L.; Johnson, Stanley A.; Kalin, Theodore; Kincaid, Marshall; Lucchini, E. Edward; Minty, William; Moore, Benjamin L.; Remmes, Joseph; Rinn, Robert J.; Roche, John W.; Sanbord, Jacquelin; Semon, Warren L.; Singer, Theodore; Smith, Dexter; Smith, Leonard; Strong, Peter F.; Thomas, Helene V.; Wang, An; Whitehouse, Martha L.; Wilkins, Holly B.; Wilkins, Robert E.; Woo, Way Dong; Little, Elbert P.; McDowell, M. Scudder (1952) [January 1951]. "Chapter V: Minimizing charts". Synthesis of electronic computing and control circuits (second printing, revised ed.). Write-Patterson Air Force Base: Harvard University Press (Cambridge, Massachusetts, USA) / Geoffrey Cumberlege Oxford University Press (London). pp. preface, 50–67. Retrieved 2017-04-16. […] Martha Whitehouse constructed the minimizing charts used so profusely throughout this book, and in addition prepared minimizing charts of seven and eight variables for experimental purposes. […] Hence, the present writer is obliged to record that the general algebraic approach, the switching function, the vacuum-tube operator, and the minimizing chart are his proposals, and that he is responsible for their inclusion herein. […] (NB. Work commenced in April 1948.)
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  15. Händler, Wolfgang (2013) [1961]. "Zum Gebrauch von Graphen in der Schaltkreis- und Schaltwerktheorie". In Peschl, Ernst Ferdinand; Unger, Heinz. Colloquium über Schaltkreis- und Schaltwerk-Theorie - Vortragsauszüge vom 26. bis 28. Oktober 1960 in Bonn - Band 3 von Internationale Schriftenreihe zur Numerischen Mathematik [International Series of Numerical Mathematics] (ISNM) (in German). 3. Institut für Angewandte Mathematik, Universität Saarbrücken, Rheinisch-Westfälisches Institut für Instrumentelle Mathematik: Springer Basel AG / Birkhäuser Verlag Basel. pp. 169–198. doi:10.1007/978-3-0348-5770-3. ISBN 978-3-0348-5771-0. ISBN 3-0348-5771-3.
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Further reading

  • De Micheli, Giovanni (1994). Synthesis and Optimization of Digital Circuits. McGraw-Hill. ISBN 0-07-016333-2. (NB. Chapters 7-9 cover combinatorial two-level, combinatorial multi-level, and respectively sequential circuit optimization.)
  • Hachtel, Gary D.; Somenzi, Fabio (2006) [1996]. Logic Synthesis and Verification Algorithms. Springer Science & Business Media. ISBN 978-0-387-31005-3.
  • Kohavi, Zvi; Jha, Niraj K. (2009). "4–6". Switching and Finite Automata Theory (3rd ed.). Cambridge University Press. ISBN 978-0-521-85748-2.
  • Knuth, Donald Ervin (2010). "chapter 7.1.2: Boolean Evaluation". The Art of Computer Programming. 4A. Addison-Wesley. pp. 96–133. ISBN 0-201-03804-8.
  • Rutenbar, Rob A. Multi-level minimization, Part I: Models & Methods (PDF) (lecture slides). Carnegie Mellon University (CMU). Lecture 7. Archived (PDF) from the original on 2018-01-15. Retrieved 2018-01-15. ; Rutenbar, Rob A. Multi-level minimization, Part II: Cube/Cokernel Extract (PDF) (lecture slides). Carnegie Mellon University (CMU). Lecture 8. Archived (PDF) from the original on 2018-01-15. Retrieved 2018-01-15.
  • Tomaszewski, Sebastian P.; Celik, Ilgaz U.; Antoniou, George E. (2003). "WWW-based Boolean function minimization" (PDF). International Journal of Applied Mathematics and Computer Science. 13 (part 4): 577–584. Archived (PDF) from the original on 2018-01-15. Retrieved 2018-01-15.
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