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Optimization Algorithm

Optimization Algorithm. Find all prime implicants. Include all essential prime implicants in the solution Select a minimum cost set of non-essential prime implicants to cover all minterms not yet covered: Obtaining a good simplified solution

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Optimization Algorithm

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  1. Optimization Algorithm • Find all prime implicants. • Include all essential prime implicants in the solution • Select a minimum cost set of non-essential prime implicants to cover all minterms not yet covered: • Obtaining a good simplified solution • Minimize the overlap among prime implicants as much as possible. • In particular, in the final solution, make sure that each prime implicant selected includes at least one minterm not included in any other prime implicant selected. Digital Systems Design

  2. Essential Selected C C 1 1 1 1 1 1 1 1 1 1 1 1 B B 1 1 A A 1 1 1 1 D D Minterms covered by essential prime implicants Selection Rule Example • Simplify F(A, B, C, D) given on the K-map. Digital Systems Design

  3. Four-Variable Map Simplification = S F(W, X, Y, Z) (0, 2,4,5,6,7, 8,10,13,15 ) m Digital Systems Design

  4. Four-Variable Map Simplification = S F(W, X, Y, Z) (3,4,5,7,9,1 3,14,15 ) m Digital Systems Design

  5. Prime-number detector (again) Digital Systems Design

  6. When we solved algebraically, we missed one simplification -- the circuit below has three less gate inputs. Digital Systems Design

  7. Another example KU College of Engineering Elec 204: Digital Systems Design

  8. Yet another example • Distinguished 1 cells • Essential prime implicants Digital Systems Design

  9. Product-of-Sums Simplification • F(A,B,C,D) = • F’ = CD+AB+BD’ • F = (C’+D’)(A’+B’)(B’+D) Digital Systems Design

  10. V = 1 V = 0 Y Y X X W W Z Z Five Variable or More K-Maps • For five variable problems, we use two adjacent K-maps. It becomes harder to visualize adjacent minterms for selecting PIs. You can extend the problem to six variables by using four K-Maps. Digital Systems Design

  11. Don't Cares in K-Maps • Sometimes a function table or map contains entries for which it is known: • the input values for the minterm will never occur, or • The output value for the minterm is not used • In these cases, the output value need not be defined • Instead, the output value is defined as a “don't care” • By placing “don't cares” ( an “x” entry) in the function table or map, the cost of the logic circuit may be lowered. • Example 1: A logic function having the binary codes for the BCD digits as its inputs. Only the codes for 0 through 9 are used. The six codes, 1010 through 1111 never occur, so the output values for these codes are “x” to represent “don’t cares.” Digital Systems Design

  12. Essential C C 1 1 x x x x 1 1 x x 1 1 B B x x A A x x 1 1 1 1 D D Minterms covered by essential prime implicants Selection Rule Example with Don't Cares Selected • Simplify F(A, B, C, D) given on the K-map. Digital Systems Design

  13. Don’t Care Conditions • F(A,B,C,D) = • d(A,B,C,D) = Digital Systems Design

  14. Examples: • F(A,B,C,D) = m(4,5,8,12,13); d=m(3,7,10,11,14,15); • F(A,B,C,D) = m(0,2,5,8,10,13); d=m(7,15); Digital Systems Design

  15. Multiple-Level Optimization • Multiple-level circuits - circuits that are not two-level (with or without input and/or output inverters) • Multiple-level circuits can have reduced gate input cost compared to two-level (SOP and POS) circuits • Multiple-level optimization is performed by applying transformations to circuits represented by equations while evaluating cost Digital Systems Design

  16. Transformations • Factoring - finding a factored form from SOP or POS expression • Algebraic – Without using of axioms specific to Boolean algebra such as complements or idempotence • Boolean - Uses axioms unique to Boolean algebra • Decomposition - expression of a function as a set of new functions Digital Systems Design

  17. Transformations (continued) • Substitution of G into F - expression function F as a function of G and some or all of its original variables • Elimination - Inverse of substitution • Extraction - decomposition applied to multiple functions simultaneously Digital Systems Design

  18. Transformation Examples • Algebraic Factoring F = A’C’D’ + A’BC’ + ABC + ACD’ G = 16 • Factoring: F = A’(C’D’ + BC’) + A (BC + CD’) G = 16 • Factoring again: F = A’C’( B +D’) + AC (B +D’) G = 12 • Factoring again: F = (A’C’+ AC) (B +D’) G = 10 Digital Systems Design

  19. Transformation Examples • Decomposition • The terms B +D’ and A’C’+ AC can be defined as new functions E and H respectively, decomposing F: F = E H, E = B +D’ , and H = A’C’+ AC G = 10 • This series of transformations has reduced G from 16 to 10, a substantial savings. The resulting circuit has three levels plus input inverters. Digital Systems Design

  20. Transformation Examples • Substitution of E into F • Returning to F just before the final factoring step: F = A’C’( B +D’) + AC (B +D’) G = 12 • Defining E = B + D’, and substituting in F: F = A’C’E + ACE G = 10 • This substitution has resulted in the same cost as the decomposition Digital Systems Design

  21. Transformation Examples • Elimination • Beginning with a new set of functions: X = B + C Y = A + B Z = A’X + C Y G = 10 • Eliminating X and Y from Z: Z = A’(B + C) + C (A + B) G = 10 • “Flattening” (Converting to SOP expression): Z = A’B + A’C + AC + BC G = 12 • This has increased the cost, but has provided an new SOP expression for two-level optimization. Digital Systems Design

  22. Transformation Examples • Two-level Optimization • The result of 2-level optimization is: Z = A’B + C G = 4 • This example illustrates that: • Optimization can begin with any set of equations, not just with minterms or a truth table • Increasing gate input count G temporarily during a series of transformations can result in a final solution with a smaller G Digital Systems Design

  23. Transformation Examples • Extraction • Beginning with two functions: E = A’B’D’+ A’BD H = B’CD’ + BCD G = 16 • Finding a common factor and defining it as a function: F = B’D’+ BD • We perform extraction by expressing E and H as the three functions: F = B’D’+ BD, E = A’F, H = CF G = 10 • The reduced cost G results from the sharing of logic between the two output functions Digital Systems Design

  24. Example: • Multiple Output Minimization: • F(A,B,C) = m(3,6,7) and G(A,B,C) = m(0,1,3) • Implement F and G using minimum number of gates. Digital Systems Design

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