State Assignment using Rules Jacob Boles Ece 572 Fall 99.

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Presentation transcript:

State Assignment using Rules Jacob Boles Ece 572 Fall 99

Introduction In this presentation I will show an example of state assignment by heuristic rules and compare it to the assignment down by partition pairs.

So that my example is more relevant and unique, I will use the simplified state machine for this machine A F B E C D X=0 X=1 X=0 X=1 X=0 A

State Assignment by Rules Rule 1 –States with most incoming branches should be assignment least number of 1’s in code. –This implies that state A which has the most incoming branches by far should be zero. All the other states have about the same number of incoming branches so we take no precedence A <= 000

State Assignment by Rules Rule 2 –State with common next state on the same input condition should be assigned adjacent codes. –In my example this only occurs for E&C&A E & C & A should be adjacent to each other A F B E C D X=0 X=1 X=0 X=1 X=0 STATES A,C and E transit to the same state A under x=0

State Assignment by Rules Rule 3 –Next state of same state should be adjacent codes according to adjacency of branch conditions. –This is a little harder to see but implies … A adj. B A adj. D D adj. E F adj. C Impossible to do all these with 3 bits! A F B E C D X=0 X=1 X=0 X=1 X=0

State Assignment by Rules Rule 4 –States that form a chain on same branch should be adjacent codes. A F B E C D X=0 X=1 X=0 X=1 X=0 Two chains: Chain A->B->F->C->D->E Chain B->C->A X=0

State Assignment by Rules Our assignment … Rule 2: E&C&A adjacent A 000 B 001 C 010 D 100 E 101 F 011 Rule 1: A <=000 Violates only 1 rules Rule 3 A adj. B A adj. D D adj. E F adj. C Rule 4: Chain A->B->F->C->D->E Chain B->C->A Impossible w/o violating Rule 1 Violates this rule

State Assignment by Rules Q0 = XC + X’D + [XD] Q1 = X’B + XF + [X’F + XB] Q2 = XA + [XD] + [X’F + XB] Assuming sharing of common logic: # gates = = 12 A 000 B 001 C 010 D 100 E 101 F 011 A F B E C D X=0 X=1 X=0 X=1 X=0 x=0 Symbolic In this example partition pair method does not give a good solution. Check with more advanced partition methods if this statement is valid

Comparison of results Easy to do Fast Efficient for small problems with limited number of variables Advantages Disadvantages Rules and heuristics Partitioning More complex Can be slow if problem is large or bad partition Will always find best solution if given time Better than trying every possibility Rules may not always hold true Inefficient for large variable problems.