using partial implications for redundancy identification and fault equivalence

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2002 Partial Implications, etc . 1 Using Partial Implications for Redundancy Identification and Fault Equivalence Vishwani D. Agrawal Agere Systems, Murray Hill, New Jersey v[email protected] http://cm.bell-labs.com/cm/cs/who/va

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Using Partial Implications for Redundancy Identification and Fault Equivalence. Vishwani D. Agrawal Agere Systems, Murray Hill, New Jersey v [email protected] http://cm.bell-labs.com/cm/cs/who/va. Talk Outline. Problem statement Background Implication graph Partial implications - PowerPoint PPT Presentation

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Page 1: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 1

Using Partial Implications for Redundancy Identification and

Fault Equivalence

Vishwani D. AgrawalAgere Systems, Murray Hill, New Jersey

[email protected]://cm.bell-labs.com/cm/cs/who/va

Page 2: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 2

Talk Outline•Problem statement•Background•Implication graph•Partial implications•Transitive closure•Redundancy identification•A new method for fault equivalence•Conclusion

Page 3: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 3

Problem Statement•Many problems can be solved by

implication graphs and transitive closure.

•We will study two problems:•Redundancy identification•Fault equivalence

Page 4: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 4

Background•Implication graphs:

• Chakradhar, et al., Book’90• Larrabee, IEEE-TCAD’92

•Transitive closure:• ATPG: Chakradhar, et al., IEEE-TCAD’93• Redundancy, Agrawal, et al., ATS’96

•Partial implications:• Henftling, et al., EDAC’95• Gaur, et al., DELTA’02, Gaur, MS Thesis’02

•Fault equivalence:• Bushnell and Agrawal, Book’00

Page 5: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 5

Implication graph

•Nodes• Two nodes per signal; nodes a and a correspond

to signal a.• A node has two states (true,false); represents the

signal state.•Edges

• A directed edge from node a to b means “a=1” implies “b=1”.

An implication graph is a representation of logical implications between pairs of signals of a digital circuit.

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2002 Partial Implications, etc. 6

Building an Implication Graph

» If C is ‘1’ then that implies that A and B must be ‘1’, but the reverse is not true. Similarly, if either A or B is ‘0’ then C will be ‘0’. But if we want to represent the implications of A and B on C then partial implications are necessary.

AC + BC + ABC = 0

A

BC

AB + C = 0

A B C

A B C

Page 7: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 7

Partial Implications

• AC + BC + ABC = 0

A

BC

AB + C = 0

A B C

A B C

Reference: Henftling, et al., EDAC, 1995

Page 8: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 8

Observability VariablesObservability variable of a signal represents

whether or not that signal is observable at a PO. It can be true or false.

A

BC

OCOA + BOA + OCBOA = 0

B

OCB + OA = 0OB

OA OC = 1

(PO)OA

OC

Page 9: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 9

Adding Observability Variables to Implication Graph

A B C

A B C

OCOA + BOA + OCBOA = 0 BOA

OC

OC OA

OC OA

OB can be added similarly.

Page 10: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 10

Transitive Closure•Transitive closure of a directed graph

contains the same set of nodes as the original graph.

•If there is a directed path from node a to b, then the transitive closure contains an edge from a to b.

ab

c

ab

cd dA graph Transitive closure

Page 11: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 11

Stuck-at Faults• This is a type of fault, which causes a line to

hold a constant logic value, irrespective of change of state at previous stages.

• There are two types of stuck-at-faults:• Stuck-at-1• Stuck-at-0

• Detection of a fault requires the fault to be activated and its effect observable at a PO.

• Fault a s-a-1 is detectable, iff following conditions can be simultaneously satisfied:• a = 0• Oa = 1

Page 12: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 12

Redundant Faults•A fault that has no test is called an

untestable fault.•Any untestable fault in a combinational

circuit is a redundant fault because it does not cause any change in the input/output logic function of the circuit.

•Identification of redundant faults is useful because they can be removed

• from testing consideration, or• from hardware

Page 13: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 13

Redundancy Identification•ATPG based method

• It uses exhaustive test pattern generation to determine whether or not a target fault has a test.

• All redundant faults can be found, but the ATPG cost is high (exponential in circuit size).

•Fault independent method• This method analyzes circuit topology and

function locally without targeting a specific fault.

• Many (not all) redundant faults can be found at a lower cost.

Page 14: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 14

Redundancy Identification by Transitive Closure

a

b

c

d

e

s-a-0

s-a-0

a b cd

Oc OdImplication graph (some nodes

and edges not shown)Circuit with tworedundant faults

ImplicationPartial implicationTransitive closure edge

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2002 Partial Implications, etc. 15

Method Summarized• Obtain an implication graph from the circuit topology and

compute transitive closure.• Examine all nodes:

• S-a-0 is redundant if the signal implies its complement.• S-a-1 is redundant if the complement of the signal implies the

signal.• Both faults are redundant if the signal and its complement imply

each other.• S-a-0 is redundant if the signal implies its false observability

variable.• S-a-1 is redundant if the complement of the signal implies its false

observability variable.• S-a-0 is redundant if the observability variable implies the

complement of the signal.• S-a-1 is redundant if the observability variable implies the signal.• Both faults are redundant if the observability variable and its

complement imply each other.

Page 16: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 16

Classification of Redundant Faults by TCAND

Circuit Total red.+aborted

faults*

Tot. red. faults ident.

Unexcit-able red.

faults

Unpropag-atable red.

faults

Undriv-able red.

faults

C1908 6+3 2 0 0 2

C2670 99+18 23+2 3 3 17+2

C3540 99+40 74 0 8 66

C5315 59 32 1 1 30

C6288 33 31 15 16 0

C7552 67+76 34 3 0 31

*HITEC, Nierman and Patel, EDAC’91

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2002 Partial Implications, etc. 17

Complexity of TCAND

SUNSparc 5

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2002 Partial Implications, etc. 18

Limitation of Method•Observability variable of a fanout stem is not

analyzed.•Only the redundant faults due to false

controllability of fanout stem can be identified.

s-a-0Three redundant s-a-0faults identified bytransitive closure

s-a-1

Two redundantstem faults not identifiedby transitive closure

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Some Conclusions• Partial implications help find more redundant

faults than the transitive closure without partial implications.

• The results have been compared with FIRE (another fault-independent program), which did equal to or worse that transitive closure with partial implication.

• Transitive closure computation run times were linear in the number of nodes for the implication graphs of benchmark circuits, although the known worst-case complexity is O(N3) for N nodes.

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2002 Partial Implications, etc. 20

Fault Equivalence• Two faults of a Boolean circuit are called

equivalent if they transform the circuit such that the two faulty circuits have identical output functions.

• Equivalent faults are indistinguishable and have exactly the same set of tests.

• Many fault equivalences can be determined by structural analysis based on gate fault equivalences and circuit interconnects; this is done in practice.

• Some fault equivalences require equivalence checking of faulty circuits; too complex and not generally done.

Page 21: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 21

Gate Fault Equivalence

sa0

sa0

sa0 sa1

sa1

sa1

sa0

sa0sa0

sa1

sa1sa1

sa0sa0sa1sa1 sa0sa0

sa1sa1

sa0

sa0

sa0

sa1

sa1sa1

Page 22: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 22

Sa0 and Sa1 Variables

A

BC

OA

AAsa0

s-a-0

Variable Asa0 assumes a true statewhen A=1 and OA is true

Asa1 is similarly defined.

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2002 Partial Implications, etc. 23

Equivalence by Imp. Graph

A B C

A B C

BC

A

OC OA

OC OA

Asa0 Csa0

s-a-0 s-a-0

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2002 Partial Implications, etc. 24

An Open Question•Can implication graph/transitive closure

recognize functional fault equivalence. These are not found by structural analysis.

•Example: e = b, for both faults.

a

b

e

s-a-1

s-a-1

Page 25: Using Partial Implications for Redundancy Identification and Fault Equivalence

2002 Partial Implications, etc. 25

Conclusion•Partial implications improve

redundancy identification.•Present limitation of the method is the

identification of redundancy due to the false observability of fanout stem; open problem.

•New formulation of fault equivalence may find some functional equivalences.

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2002 Partial Implications, etc. 26

THANK YOU