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Combinational and Sequential Flexibility in Logic Networks

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Title: Combinational and Sequential Flexibility in Logic Networks


1
Combinational and Sequential Flexibility in Logic
Networks
290N The Unknown Component Problem Lecture 3
2
Overview
  • Logic networks
  • Flexibility
  • Complete vs. compatible flexibility
  • Combinational case
  • Satisfiability dont-cares
  • Observability dont-cares
  • External dont-cares
  • Complete combinational flexibility
  • Computational procedures
  • Implementation
  • Sequential case
  • Input dont-care sequences
  • Output dont-care sequences
  • External specification
  • Complete sequential flexibility

3
Logic Network
  • Logic network is a direct acyclic graph

Primary outputs (POs)
Internal nodes
Primary inputs (PIs)
4
Fanin/Fanout of a Node
  • Node has only one output.
  • Node can have any number of inputs (fanins) and
    can be an input to any number of nodes (fanouts)

FO1
FO2
FO3
Fanouts
N
Node
FI2
FI3
FI1
Fanins
5
Transitive Fanin/Fanout of a Node
Transitive fanout (TFO)
Node
Transitive fanin (TFI)
6
Flexibility at a Node
External specification
Logic Network
  • A flexibility at a node is a relation between the
    nodes inputs and outputs, such that any
    well-defined sub-relation used at the node leads
    to a logic network that conforms to the external
    specification.

7
Complete vs Compatible Flexibility
  • Definition. The complete flexibility (CF) is the
    maximum flexibility possible at a node, assuming
    that other nodes are fixed.
  • Definition. A compatible flexibility (CF) is a
    flexibility at a node, assuming that other nodes
    can change, to some extent.
  • Typically, compatible flexibilities are assigned
    to all of the nodes in one pass over the network.
    Then, each node is minimized independently.
  • On the other hand, complete flexibility at a
    node, once computed, should be used before moving
    on to other nodes.

8
Flexibility of Nodes in the Network
  • Internal flexibility (dont-cares)
  • Satisfiability dont-cares
  • Some input combinations that never occur at a
    node
  • Observability dont-cares
  • Under some input combinations, the value produced
    at the output of the node does not matter
  • External flexibility (dont-cares)
  • Some input combinations never occur (unused
    codes, unreachable states)
  • Complete flexibility (dont-cares)
  • The sum of the three above

9
Satisfiability Dont-Cares
  • (x,y)(1,0) is a dont-care for node F

10
Observability Dont-Cares
  • (a,c)(1,1) is a dont-care for node F

z1
z2
F
a
b
c
11
Global and Local Flexiblity
Local Space
Global Space
12
Computing CF - global step
Original network Rspec( X, Z ) (can be also
given as an external specification)
Perturbed network R( X, yi, Z )
13
Computing CF - local step
14
Computing CF - local step
The same computation applies for multiple-output
nodes, i.e. where
15
Sequential Flexibility for FSM
Mo
  • Output dont-care sequences of Mx exist because
    Mo does not distinguish some string
  • observability dont-cares

Mx
  • Input dont-care sequences of Mx exist because Mi
    does not produce some strings
  • satisfiability dont-cares

Mi
16
FSM Networks
  • Problem Given a network of finite state
    machines, compute the Complete Sequential
    Flexibility at a node

17
Problem Formulation
Specification S (i,o) Context F
(i,v,u,o) Unknown X (u,v)
Problem Given S and F, find the Most General
Solution (MGS) of
Solution
18
Definitions
  • Most General Solution (MSG) is the automaton
    solution of the language equation F ? X ? S, such
    that any other automaton solution is contained in
    it.
  • Complete Sequential Flexibility (CSF) is the
    maximum set of FSM behaviors (represented by a
    pseudo-non-deterministic FSM), such that
    implementing any sub-behavior of CSF, and
    replacing the sub-network by the implemented
    part, does not violate the specification of the
    total network.
  • CSF is maximum sub-behavior of MGS, which is
    prefix-closed and u-progressive
  • for unknown to be an FSM, it must be progressive
    in its inputs

19
Algorithm to Compute
Algorithm CompleteSequentialFlexibility Input
FSM F, FSM (or automaton) S Output pseudo-non-
deterministic FSM X begin 01 X Complete ( S,
non-accepting ) 02 X Complement ( X ) 03 X
Support (X, (i,v,u,o)) lift 03 X Product
( F, X ) 04 X Support ( X, (u,v) ) -
restrict 05 X Determinize Complement( X
) 06 X PrefixCloseuProgressive( X,
u ) return X end
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