Irredundant Sum-of-Products Expressions - J. T. Butler

Similar documents
On the Minimization of SOPs for Bi-Decomposable Functions

On the Minimization of SOPs for Bi-Decomposable Functions

A Fast Method to Derive Minimum SOPs for Decomposable Functions

Sum-of-Generalized Products Expressions Applications and Minimization

Large-Scale SOP Minimization Using Decomposition and Functional Properties

LUTMIN: FPGA Logic Synthesis with MUX-Based and Cascade Realizations

PLA Minimization for Low Power VLSI Designs

Logic Synthesis of EXOR Projected Sum of Products

Comparison of the Worst and Best Sum-Of-Products Expressions for Mult iple-valued Functions

x 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8 x 9 x 10 x 11 x 12 x 13 x 14 x 15 x 16

A New Viewpoint on Two-Level Logic Minimization

Olivier Coudert Jean Christophe Madre Henri Fraisse. Bull Corporate Research Center. Rue Jean Jaures Les Clayes-sous-bois, FRANCE

Inadmissible Class of Boolean Functions under Stuck-at Faults

Chapter 4 Optimized Implementation of Logic Functions

Preprint from Workshop Notes, International Workshop on Logic Synthesis (IWLS 97), Tahoe City, California, May 19-21, 1997

Fundamental Algorithms for System Modeling, Analysis, and Optimization

x 1 x 2 x 7 y 2 y 1 = = = WGT7 SB(7,4) SB(7,2) SB(7,1)

An Application of Autocorrelation Functions to Find Linear Decompositions for Incompletely Specified Index Generation Functions

LP Characteristic Vector of Logic Functions Norio Koda Department of Computer Science and Electronic Engineering Tokuyama College of Technology Tokuya

Analysis and Synthesis of Weighted-Sum Functions

An Algorithm for Bi-Decomposition of Logic Functions

Testability of SPP Three-Level Logic Networks

On the Number of Products to Represent Interval Functions by SOPs with Four-Valued Variables

On the Complexity of Error Detection Functions for Redundant Residue Number Systems

Logic Minimization. Two-Level. University of California. Prof. Srinivas Devadas. Prof. Richard Newton Prof. Sanjit Seshia. Prof.

Symmetrical, Dual and Linear Functions and Their Autocorrelation Coefficients

PAPER Head-Tail Expressions for Interval Functions

X1=0 X1=1 X1=p-1. f 0 f 1 f p-1

L4: Karnaugh diagrams, two-, and multi-level minimization. Elena Dubrova KTH / ICT / ES

Multi-Level Logic Optimization. Technology Independent. Thanks to R. Rudell, S. Malik, R. Rutenbar. University of California, Berkeley, CA

Multilevel Logic Synthesis Algebraic Methods

14:332:231 DIGITAL LOGIC DESIGN

ELC224C. Karnaugh Maps

Multi-Terminal Multi-Valued Decision Diagrams for Characteristic Function Representing Cluster Decomposition

Two-Level Logic Synthesis for Probabilistic Computation

14:332:231 DIGITAL LOGIC DESIGN. Combinational Circuit Synthesis

E&CE 223 Digital Circuits & Systems. Lecture Transparencies (Boolean Algebra & Logic Gates) M. Sachdev

A New Design Method for Unidirectional Circuits

Simplification of Boolean Functions. Dept. of CSE, IEM, Kolkata

A Fast Head-Tail Expression Generator for TCAM Application to Packet Classification

E&CE 223 Digital Circuits & Systems. Lecture Transparencies (Boolean Algebra & Logic Gates) M. Sachdev. Section 2: Boolean Algebra & Logic Gates

Simplifying Logic Circuits with Karnaugh Maps

Digital Circuit And Logic Design I. Lecture 4

This form sometimes used in logic circuit, example:

PAPER Design Methods of Radix Converters Using Arithmetic Decompositions

CHAPTER III BOOLEAN ALGEBRA

WEEK 3.1 MORE ON KARNAUGH MAPS

2009 Spring CS211 Digital Systems & Lab CHAPTER 2: INTRODUCTION TO LOGIC CIRCUITS

Doing Two-Level Logic Minimization 100 Times Faster. Olivier Coudert. Synopsys, Inc. 700 East Middlefield Road, Moutain View, CA

Combinatorial Logic Design Principles

The Karnaugh Map COE 202. Digital Logic Design. Dr. Muhamed Mudawar King Fahd University of Petroleum and Minerals

Boolean Matching Using Generalized Reed-Muller Forms

CHAPTER III BOOLEAN ALGEBRA

Chapter 2: Switching Algebra and Logic Circuits

On the number of segments needed in a piecewise linear approximation

MC9211 Computer Organization

CS/EE 181a 2010/11 Lecture 4

doi: /TCAD

UNIT 5 KARNAUGH MAPS Spring 2011

Decomposition of Multi-Output Boolean Functions - PRELIMINARY VERSION

Lecture 6: Gate Level Minimization Syed M. Mahmud, Ph.D ECE Department Wayne State University

Logic Synthesis. Basic Definitions. k-cubes

CS/EE 181a 2008/09 Lecture 4

A New Implicit Graph Based Prime and Essential Prime Computation Technique

Complete Bi-Decomposition of Multiple-Valued Functions Using MIN and MAX Gates

Karnaugh Maps Objectives

Chap 2. Combinational Logic Circuits

ECE 3060 VLSI and Advanced Digital Design

Digital Logic Design. Combinational Logic

A New Method to Express Functional Permissibilities for LUT based FPGAs and Its Applications

Logic Design. Chapter 2: Introduction to Logic Circuits

Lecture 5. Karnaugh-Map

Detecting Support-Reducing Bound Sets using Two-Cofactor Symmetries 1

PAPER Minimization of Reversible Wave Cascades

An Implementation of an Address Generator Using Hash Memories

Combinational Logic Fundamentals

Lecture 6: Manipulation of Algebraic Functions, Boolean Algebra, Karnaugh Maps

UNIT 4 MINTERM AND MAXTERM EXPANSIONS

Unit 2 Session - 6 Combinational Logic Circuits

Lecture 7: Karnaugh Map, Don t Cares

Class Website:

Derivative Operations for Lattices of Boolean Functions

REMARKS ON THE NUMBER OF LOGIC NETWORKS WITH SAME COMPLEXITY DERIVED FROM SPECTRAL TRANSFORM DECISION DIAGRAMS

On the Use of Transeunt Triangles to Synthesize Fixed-Polarity Reed-Muller Expansions of Functions

CHAPTER 5 KARNAUGH MAPS

Logic Synthesis and Verification

On LUT Cascade Realizations of FIR Filters

The complexity of SPP formula minimization

Section 4.1 Switching Algebra Symmetric Functions

Midterm1 Review. Jan 24 Armita

L9: Galois Fields. Reading material

An Efficient Heuristic Algorithm for Linear Decomposition of Index Generation Functions

Variable Reordering for Reversible Wave Cascades - PRELIMINARY VERSION

Generalized Haar Spectral Representations and Their Applications

Week-I. Combinational Logic & Circuits

Digital Circuit And Logic Design I. Lecture 3

Quality of Minimal Sets of Prime Implicants of Boolean Functions

IN the areas of machine learning, artificial intelligence, as

Textbook: Digital Design, 3 rd. Edition M. Morris Mano

COM111 Introduction to Computer Engineering (Fall ) NOTES 6 -- page 1 of 12

Transcription:

On the minimization of SOP s for Bi-Decomposable Functions T. Sasao* & J. T. Butler *Kyushu Institute of Technology, Iizuka, JAPAN Naval Postgraduate School Monterey, CA -5 U.S.A. Outline Introduction s Orthodox Functions Experimental Results Conclusions Introduction Product (implicant) - The AND of variables or their complement (e.g. x x is a product of f x x x PI - prime implicant p of function f - f is for all assignments of values to the variables such that p is, and deleting any variable produces a product that does not have this property. (e.g. x x x is a PI of f.) Introduction SOP - sum-of-products expression is the OR of products. F x xx is an SOP. ISOP - irredundant SOP is an SOP in which removing any product or literal changes the function. F x x x is not an ISOP, because removing x x does not change the function; i.e. F x. Introduction MSOP minimum sum-of-products - ISOP of a function f with the fewest PIs. ( MSOP : f ) = number of product terms in an MSOP of f Introduction A function f (X,Y) has an OR bidecomposition if it can be expressed as f ( X, Y) h ( X ) h ( Y ) 5 6

Introduction A function f (X,Y) has an AND bidecomposition if it can be expressed as f ( X, Y) h( X) h ( Y ) Lemma. Let h (X ) and h (X ) be functions not identically, where X and X are disjoint. Then, (MSOP: h h) (MSOP: h) (MSOP: h) (MSOP : hh) (MSOP : h) (MSOP : h) It is tempting to believe that Lemma. is true with the two are replaced by. Consider the two statements separately. Proposition.: Let h (X ) and h (X ) be functions not identically, where X and X are disjoint. Then, (MSOP: h h) (MSOP: h) (MSOP: h) Proof: Please see our paper. Proof: We claim that an SOP formed as the OR of an MSOP of h with a MSOP of h is an MSOP of h h. On the contrary, assume there is an MSOP of h h that has fewer PIs than the MSOPs of h and h combined. Because X and X are disjoint, a a PI p of h h is an

Proof : implicant of h or h, but not both. But, p must be a PI, otherwise it is not a PI of h h. The OR of all PIs of h, must form a complete cover of h ; similarly, for the OR of all PIs of h. However, the fact that h h has fewer PIs than the sum of PIs from the MSOPs of h and h implies there Proof : is an SOP of h or h or both with fewer PIs than in the MSOPs for h and h, which is impossible. It must be that the OR of an MSOP of h with an MSOP of h is an MSOP of h h. Q.E.D. Proposition.: Let h (X ) and h (X ) be functions not identically, where X and X are disjoint. Then, (MSOP: hh ) (MSOP: h) (MSOP: h) However, Proposition. is not true. Voight-Wegener [] showed a 5- variable counterexample. We show a -variable counterexample in the Karnaugh Map on the next slide. We know there is no simpler counterexample. 5 6 x x x x Counterexample to Proposition. f x x x x x x x x x x x x x x x T. Sasao and J. T. Butler Consider f = f(x)f(y), where X and Y are disjoint. f Counterexample to Proposition. x xx xxx x x x xx xx xx y y y yyy y y y y y y y yy

Expanding f = f(x)f(y) by applying distributivity yields and an SOP with 5 PIs. f x x x x x x x x x xx x x xx y yy yy y yy y yy y y y y In this example, (MSOP: h h ) is only one smaller than (MSOP:h )(MSOP:h ). This suggests an interesting question. Are there functions where (MSOP: h h ) is much less than (MSOP:h )(MSOP:h ) Incompletely specified function x x x _ Orthodox Functions Independent set of minterms - Given f, let M(f) be the set of f s minterms. Then, a subset, MI(f) of M(f) is an independent set of minterms of f iff no PI of f covers more than one minterm in MI(f). Orthodox Functions A maximum independent set of minterms, MIS, of f is an independent set of minterms with the largest number minterms. Orthodox Functions Given f, (f) is the number of elements in the MIS of minterms of f. MISs are used in ESPRESSO to obtain a lower bound on the number of products in an MSOP.

Example x x x Two MISs for S {,} (x,x,x ) are. x x x PI s are shown as red circles. {,,} {,,} 5 Orthodox Functions A function f is orthodox if Number of minterms in an MIS of f. (f) = (MSOP:f). Number of products in an MSOP of f. 6 Example The function S x x {,} (x,x,x ) is orthodox. x An MIS of this function has elements (e.g.{,,}), and its MSOP has PIs. Orthodox Functions The significance of orthodox functions is due to: Theorem: Let h (X ) and h (X ) be orthodox, such that X and X are disjoint. Then, (MSOP : hh) (MSOP : h) (MSOP : h) Orthodox Functions Thus, if a function is orthodox and has an AND bi-decomposition, an MSOP for it can be obtained by minimizing the two subfunctions separately and combining them using distribution. Therefore, the complexity of minimization can be reduced. Orthodox Functions Any function in which the MSOP consists of essential PIs only is orthodox. That is, essential PIs cover minterms covered by no other PI, which form an MIS. Its cardinality is the number of PIs in the MSOP. Thus, the function is orthodox. 5

Orthodox Functions Functions that are orthodox.. Unate functions. Parity functions. Symmetric functions. All functions with or fewer variables Orthodox Functions Functions with 5 or more variables Number of Variables 5 6 Percent that are orthodox % 6 % % 66 % 6 % % Experimental Results How are orthodox functions distributed with respect to the number of true minterms We analyzed randomly chosen functions on n variables, for 5 n. The results are as follows. Experimental Results Percentage That Are Orthodox.... 6. 5...... n= n = n = n = n = n = n = n =5 n = n =6..5 5..5 5. 6.5 5..5. Percentage of Minterms That Are True Experimental Results To what extent are benchmark functions orthodox We determined which MCNC benchmark functions are orthodox. Interestingly, most are orthodox. See the tables on the next slides. 5 Experimental Results Benchmark Function 5xp sym apex b cps duke ex* Out. *Incompletely specified Ordx. Unate 5 * 6 6

Experimental Results Experimental Results Benchmark Function Out. Ordx. Unate Benchmark Function Out. Ordx. Unate inc misex misex misex misexc pdc* rd5 * rd rd apex spla t vg 6 6 *Incompletely specified *Incompletely specified Conclusions For functions of the form f = f f, applying distributivity to the MSOPs of f and f does not always produce an MSOP for f. We introduce a class of functions, called orthodox functions, where this DOES produce an MSOP Conclusions cont d We show that. all unate functions. all parity functions. all symmetric functions. all functions with or fewer variables 5. most MCNC benchmark functions 6. few random functions with many variables are orthodox. References. B. Voight and I. Wegener, ''A remark on minimal polynomials of Boolean functions,' CSL', nd Workshop on Computer Science Logic Proceedings, pp. -,. References. R. K. Brayton, C. T. McMullen, G. D. Hachtel, and A. L. Sangiovanni-Vincentelli, Logic Minimization Algorthims for VLSI Synthesis, Boston, MA, Kluwer Academic Pub.,.. R. S. Michalski and Z. Kulpa, A system of programs for the synthesis of switching circuits using the method of dispoint stars, Proc. of IFIP Congress, pp. 6-65, April.. W. J. Paul, '' Realizing Boolean functions on disjoint set of variables,' Theoretical Computer Science, pp. -6, 6.

References. R. L. Rudell and A. Sangiovanni-Vincentelli, ''Multiplevalued minimization for PLA optimization,'' IEEE Trans. Computer-Aided Design, vol. CAD-6, 5, pp. -, September. 5. T. Sasao and M. Matsuura, DECOMPOS: An integrated system for functional decomposition,'' International Workshop on Logic Synthesis, Lake Tahoe, pp. -, June. 6. B. Voight and I. Wegener, ''A remark on minimal polynomials of Boolean functions,' CSL', nd Workshop on Computer Science Logic Proceedings, pp. -,.