Computer Architecture I: Digital Design Dr. Robert D. Kent

Computer Architecture I: Digital Design Dr. Robert D. Kent Lecture 2a Boolean Algebra & Calculus, Basic Gates, Digital Logic

Boolean Logic • First developed by George Boole (1850’s) in a study of 2-valued sets and their properties. He aimed to model intelligence and knowledge. • Later realized to be of fundamental importance in the design and construction of digital logic devices, namely the computer (Claude Shannon - 1930’s). • The discovery of the transistor (npn and pnp junctions) and other solid-state microelectronic components (Josephson, Bardeen, Cooper et al) led to manufacture of basic gate devices that realized the various primitive logic operations • not, and, or, xor, nand, nor, xnor

Boolean Logic • We will cover the following points, in order: • Definitions and Mathematics • Review of basic operations and their truth tables • Boolean postulates • Boolean expressions • Algebraic Simplification • Gate (diagrammatic) representations for circuit layout & design

Boolean Logic • We emphasize that we are studying • two-valued logic bits (0’s and 1’s) • the operations that act on bits • the calculus for manipulating the operators and expressions formed from them and the data being operated on

Boolean Algebra - Mathematics • A Boolean algebra is a system consisting of a set of elements, B, two binary operators (+ and ), parentheses to indicate the nested order of evaluation and an = operator to perform assignment of an expression. The algebra must further obey six fundamental postulates, or axioms: • All theorems to be derived depend on the postulates. • Postulates, or axioms, are the “ground rules” that underly everything there is to say (or derive) about a mathematical system • Theorems are “practical applications” of postulates – theorems can be proven based on the postulates

Boolean Algebra - Mathematics • Postulates: • P6: ExistenceThere exist at least two elements x,y in B such that x ≠ y • P1: Closure: There exists x,y in B such that two independent operations, . (dot) and + (plus) are defined: x + y in B x . y in B • P2: Identity: There exist identity elements 0,1 in B relative to the operations + and . , such that for every x in B: 0 + x = x + 0 = x 1 . x = x . 1 = x • P3: Commutativity: The operations + and . are commutative for all x,y in B: x + y = y + x x . y = y . x

Boolean Algebra - Mathematics • Postulates: (Continued) • P4: Distributivity: Each operation + and . is distributive over the other; that is, for all x,y,z in B: x . ( y + z ) = x . y + x . Z x + ( y . z ) = ( x + y ) . ( x + z ) • P5: Complementation: For every element x in B there exists an element ~x, called the complement of x, satisfying: x + ~x = 1 x . ~x = 0 • Very useful Theorem: Property of Idempotency: x + x = x x . x = x

Boolean Algebra - Mathematics • The various postulates satisfy a principle of duality, in that you obtain one form of postulate from the corresponding other one by interchanging the operations + and , and also the identity elements: Postulate Dual Postulate x + y x y 0 + x = x + 0 = x 1 x = x 1 = x x + y = y + x x y = y x x + ( y z ) = ( x + y ) ( x + z ) x ( y + z ) = ( x y ) +( x z ) x + x = 1 x x = 0 THM: x + x = x x x = x

Basic operations • There are seven (7) commonly used Boolean, or logic, operations:notand nandor noreor enor(xor) (xnor)

Boolean Algebraic Representation • It will be increasingly inconvenient to write out the Boolean operators using words. • We therefore adopt the notations:AlgebraicWord form A ( A’ ) not A AB (A B) A and B A + B A or B A + B A xor B A B A nand B A + B A nor B A + B A xnor B

Boolean Algebraic Representation • Truth tables for the fundamental logic operations

Theorems & Proof Techniques • The circuits inside a computer involve a huge number (millions to billions) of individual data bits, each of which can provide input to an operation. • To construct truth tables for such complex circuits is clearly impractical, if not impossible, given the huge number of variable bits. • Further, to prove that a circuit design is correct, or to simplify the expression of a circuit using truth tables is also clearly impractical.

Theorems & Proof Techniques • The methods of the Boolean Algebra, namely its calculus, provide general and powerful techniques for • establishing the correctness of derived equivalent expressions for circuits • simplifying the expressions to a more optimal form • optimality, here, refers to both simplicity and elegance of expression and provision of more efficient execution in hardware.

Theorems & Proof Techniques • The cornerstones of Boolean Calculus are:Axioms Algebraic representation Theorems • … which lead to more complicated and powerful theorems. • Proofs are established through the application and re-application of the prior axioms and theorems, usually also based on the clever use and manipulation of the algebraic representation.

Theorems & Proof Techniques • REMEMBER!Mathematical proof is a formal and rigorous technique that must be practiced and studied seriously in order to develop into a natural and faithful tool. This is not just a hardware or logic design issue - it also appears in • formal software engineering • proofs of algorithmic correctness • artificial intelligence • genetic algorithms • … and many other places in computer science!

Formal Proofs: Theorem 1 • T1: The element X’ is uniquely determined by X, as in P5. • Proof: Assume there are two elements X1’ and X2’, both determined by X. (Note: there can only be two in B) • it follows from P5 that X + X1’ = 1 X + X2’ = 1 X X1’ = 0 X X2’ = 0 • The following steps apply: X1’ = X1’ .1 = X2’ .X + X2’ . X1’ = X1’ .(X+X2’) = X2’ .(X + X1’) = X1’ .X + X1’ . X2’ = X2’ .1 = X. X1’ + X1’ . X2’ = X2’ = 0 + X1’ . X2’ = X. X2’ + X1’ . X2’ So: X1’ = X2’ QED! Since the original assumption was that X1’ and X2’ were different, we have proven the contradiction, namely that both are identical and therefore X’ is uniquely determined by X.

Formal Proofs: Theorem 2 Note the duality in the two proofs. Change + to . and 1’s to 0’s. • T2: For each X in B: (a) X + 1 = 1 (b) X . 0 = 0 • Proof of (a): X + 1 = 1 . (X + 1) = (X + X’) . (X + 1) = X + (X’. 1) = X + X’ = 1 QED! • Proof of (b): X . 0 = 0 + (X . 0) = (X . X’) + (X . 0) = X . (X’ + 0) = X . X’ = 0 QED!

Formal Proofs: Idempotent Theorem • Idempotent Theorem: For each X in B: (a) X + X = X (b) X . X = X • Proof of (a): X + X = (X + X) . 1 = (X + X) . (X + X’) = X + (X . X’) = X + 0 = X QED! • Proof of (b): By duality.

Formal Proofs: Involution Theorem • Involution Theorem (Double Negation) For each X in B, X’’ = X. • Proof:Let X’ be the complement of X, and X’’ be the complement of X’. It follows that: X + X’ = 1 X . X’ = 0 X’ + X’’ = 1 X’ . X’’ = 0 • Then: X’’ = X’’ + 0 = X’’ + X . X’ = (X’’ + X) . (X’’ + X’) = (X’’ + X) . 1 = (X’’ + X) . (X’ + X) = X + (X’ . X’’) = X + 0 = X QED!

Formal Proofs: Absorption Theorem • Absorption Theorem: For every X, Y in B: (a) X + X . Y = X (b) X . (X + Y) = X • Proof of (a): X + X . Y = X . 1 + X . Y = X . (1 + Y) = X . 1 = X QED! • Proof of (b): By duality.

Formal Proofs: Collapse Theorem • Collapse Theorem: For every X, Y in B: (a) X + X’ . Y = X + Y (b) X . (X’ + Y) = X . Y • Proof of (a): X + X’ . Y = (X + X’) . (X + Y) = 1 . (X + Y) = (X + Y) QED! • Proof of (b): By duality.

Formal Proofs: De Morgan’s Theorems • De Morgan’s Theorems: For every X, Y in B: (a) (X + Y)’ = X’ . Y’ (b) (X . Y)’ = X’ + Y’ • Proof of (a): Letting A=(X+Y) and B=X’.Y’, then (a) states: A’ = B.If true, then it must follow that: A + A’ = A + B = (X+Y) + (X’.Y’) = [(X+Y) + X’] . [(X+Y) + Y’] = [(X+X’) + Y] . [(Y+Y’) + X] = [1 + Y] . [1 + X] = 1 . 1 = 1 Self-consistent! QED • Proof of (b): By duality.

Formal Proofs versus Truth Tables • All of the previous theorems can be proven using the technique of proof by exhaustion, based on the use of truth tables. • By listing all possible combinations of values (0 and 1) for each variable, its complement and all sub-expressions, one proceeds toward the goal of establishing that each possible expression value on the right and left sides of the theorem relation are equivalent. • This is referred to as perfect induction.

Boolean Expressions • In digital design, circuits are expressed as formulae. • Examples: f(x,y,z) = (x’ + y) z f(x,y) = xy’ + x’y • In general, f(x) is a multi-nomial of degree one in each of the element variables xk in x. • The usual goal is to express f(x) in the simplest form possible. • Such forms typically involve the minimum number of literals (i.e. variable elements, including complements and repeated elements) • They represent hardware designs that are partially or fully optimal. 3 literals 4 literals variables

Boolean Expressions • When the expression of f is of the form:f = A + BC + DEFit is called a Sum of Products, or Disjunctive Normal Form (DNF). • When the expression of f is of the form:f = (A) . (B + D) . (D + E + F) it is called a Product of Sums, or Conjunctive Normal Form (CNF). SOP POS

Boolean Expressions - Canonical Forms • When the SOP expression of F(A,B,C) involves terms in which all variables appear (some or all may be complemented), it is called a Sum of Minterms:F(A,B,C) = ABC + A’BC + AB’C’ a minterm has all 3 variables • When the POS expression of f involves terms in which all variables appear (some or all may be complemented), it is called a Sum of Maxterms: F = (A+B+C) . (A’+B+C) . (A+B’+C’) a maxterm has all 3 variables • If f(x) depends on N variables, the maximum number of terms it can have is 2N.

Boolean Expressions - Canonical Forms K X Y Z FK 0 0 0 0 0 1 0 0 1 1 2 0 1 0 0 3 0 1 1 1 4 1 0 0 1 5 1 0 1 0 6 1 1 0 0 7 1 1 1 0 • It is usually the case that F(x) is not given a priori. Rather, its boolean value is given for each specific set of x values. • These are conveniently expressed in a truth table, as in: The row index value is just the decimal equivalent to the binary sequence of variable values in each row.

Boolean Expressions - Canonical Forms K X Y Z FK 0 0 0 0 0 1 0 0 1 1 2 0 1 0 0 3 0 1 1 1 4 1 0 0 1 5 1 0 1 0 6 1 1 0 0 7 1 1 1 0 • It is usually the case that f(x) is not given a priori. Rather, its boolean value is given for each specific set of x values. • These are conveniently expressed in a truth table. • Example: The minterm canonical form is obtained by collecting all minterms for which FK = 1, namely: F = X’Y’Z + X’YZ + XY’Z’ Note: We write the variable name itself when its corresponding entry in the table is 1 - otherwise, we write the complement of the variable.

Boolean Expressions - Canonical Forms K X Y Z FK 0 0 0 0 0 1 0 0 1 1 2 0 1 0 0 3 0 1 1 1 4 1 0 0 1 5 1 0 1 0 6 1 1 0 0 7 1 1 1 0 • It is usually the case that f(x) is not given a priori. Rather, its boolean value is given for each specific set of x values. • These are conveniently expressed in a truth table. • Example: This shorthand notation is often useful. Note that the row values listed in brackets are the decimal equivalents to the binary sequence of variable values. The minterm canonical form is obtained by collecting all minterms for which FK = 1, namely: F = X’Y’Z + X’YZ + XY’Z’ = SUM m(1,3,4)

Boolean Expressions - Canonical Forms K X Y Z FK 0 0 0 0 0 1 0 0 1 1 2 0 1 0 0 3 0 1 1 1 4 1 0 0 1 5 1 0 1 0 6 1 1 0 0 7 1 1 1 0 • It is usually the case that f(x) is not given a priori. Rather, its boolean value is given for each specific set of x values. • These are conveniently expressed in a truth table. • Example: Maxterm Expression The maxterm canonical form is obtained by collecting all maxterms for which FK = 0, namely: F = (X+Y+Z)(X+Y’+Z)(X’+Y+Z’) (X’+Y’+Z) (X’+Y’+Z’)

Boolean Expressions - Canonical Forms K X Y Z FK 0 0 0 0 0 1 0 0 1 1 2 0 1 0 0 3 0 1 1 1 4 1 0 0 1 5 1 0 1 0 6 1 1 0 0 7 1 1 1 0 • It is usually the case that f(x) is not given a priori. Rather, its boolean value is given for each specific set of x values. • These are conveniently expressed in a truth table. • Example: In mathematics we encounter SUM and PRODuct of terms and we use the notations: SUM FKFK PROD FK FK Greek capital sigma The maxterm canonical form is obtained by collecting all maxterms for which FK = 0, namely: F = (X+Y+Z)(X+Y’+Z)(X’+Y+Z’) (X’+Y’+Z) (X’+Y’+Z’) = PROD M(0,2,5,6,7) SHORTHAND NOTATION! Greek capital pi

Algebraic Simplification • Algebraic simplification is usually applied to canonical minterm and maxterm expressions. • The number of individual terms and variable combinations can be minimized in many cases. • The power of algebraic simplification is quite limited and we will need to replace these techniques by other, even more powerful techniques.

Gate Representations • Gate (diagrammatic) representations are used for circuit layout & design. • These gates, or logic devices, are manufactured and used to construct actual microelectronic circuits, such as memories, ALU’s, CU’s, CPU’s, buses and so on. Transistor types: (a) NPN, and (b) PNP with base (B), collector (C) and emitter (E) wires.

Gate Representations • Each logic operation has its own gate diagram and truth table: not (inverter) and / nand or / nor xor / xnor X X XY XY X Y X Y X+Y X+Y X Y X Y X Y X Y X Y X Y

Gate Representations • Manufacturing of gate level logic devices sometimes benefits the lower cost of production of certain types of gates • nand, nor • A very powerful property of Boolean Algebra is that all of the basic gate types (boolean operations) can be expressed in terms of just one specific gate • nand, nor • This implies that an entire computer (except for a few items!) can be constructed from a single gate type. • Although true in principle, there are many reasons why a variety of gate types are actually used.

Gate Representations • Theorem: For each X, Y in B, X + Y = (X . Y’) + (X’ . Y) In words, X xor Y = ( X and ( not Y ) ) or ( ( not X ) and Y )And, as an equivalent circuit, XY’ X X Y X Y Y’ X’ (XY’)+(X’Y) Y X’Y

Gate Representations • All of the previous theorems can also be re-developed using only the nor gate as the fundamentally primitive gate type. • In principle, all gates can be represented in terms of any one gate, with the exception of the not (inverter/complementer) • You cannot construct a binary operator from a purely unary one.

Gate Representations • Example: Express the Inverter (complementer) using only a NAND gate • Use the idempotency relationship, namely: X = X.X • Now, since the complement of X is just X’, it follows that X’ = (X.X)’ = not( X and X) = X nand X • In diagrammatic form: X X’ X X’

Gate Representations • Example: Express the Inverter (complementer) using only a NOR gate • Once again, use the idempotency relationship, namely: X = X + X • Now, since the complement of X is just X’, it follows that X’ = (X+X)’ = not( X or X) = X nor X • In diagrammatic form: X X’ X X’

Gate Representations • The circle associated with logic gates corresponds to an inversion (complementation) operation • By moving the position of the circle(s), one can often achieve simple results • Example: X’’ = (X’ ) ‘ = X X X’ X X X

Gate Representations • Example: De Morgan’s Theorem (X+Y)’ = (X’).(Y’) By manipulating the circles (moving them along lines and through gates) one can often achieve simplified, or alternative, expressions. X (X+Y)’ Y X X’ (X’).(Y’) Y Y’

Summary • We have considered the Boolean Algebra • formal mathematical definition • algebraic representation (0 and 1) • postulates • theorems • formal proof techniques • Boolean expressions • SOP and POS forms • minterms and maxterms • Gate diagrams for circuit logic • We will now continue to study algebraic simplification, followed by general reduction techniques for simplifying complex boolean expressions.

Computer Architecture I: Digital Design Dr. Robert D. Kent