weak sram cell fault model and a dft technique mohammad sharifkhani, with special thanks to andrei...

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Weak SRAM Cell Fault Weak SRAM Cell Fault Model Model and and a DFT Technique a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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Page 1: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

Weak SRAM Cell Fault ModelWeak SRAM Cell Fault Model andand

a DFT Techniquea DFT TechniqueMohammad Sharifkhani,

with special thanks to

Andrei PavlovUniversity of Waterloo

Page 2: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

2

OutlineOutline

Background and motivationSRAM issues: noise, SNM, weak cells

SRAM SNM sensitivity analysisvs. process variationvs. non-catastrophic defect resistancevs. operating conditions

Programmable weak SRAM cell fault model

DFT for weak cell detectionDetection conceptImplementation

Conclusions

Page 3: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

3

Static

Process offsets and mismatches

Operating conditions variations

Dynamic

Cross-talk

Ripples in power rails

-particles

Most of dynamic sources are quasi-static

Noise SourcesNoise Sources

Page 4: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

4

D

D

D

D

y

x

v

u

SNM

450

What is SNM?What is SNM?

2SNMD

Seevinck et al, JSSC’87

SNM = max static noise, which can be tolerated by an SRAM cell without changing its logical state

Page 5: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

5

Vnode A

Vnode B

SNMtyp

VDD

VDD

Vgood

What is a weak SRAM cell?What is a weak SRAM cell?BLBBL

WL

driver-1 driver-2

load-2load-1

access-1 access-2

A BLet’s consider a standard

6T SRAM cell:

Page 6: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

6

Vnode A

Vnode B

SNMtyp

SNMweak

VDD

VDD

Vweak

Vgood

What is a weak SRAM cell?What is a weak SRAM cell?

Weak cell = a cell with inadequate SNM that can be easily flipped

Page 7: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

7

Why Test Weak SRAM Cells?Why Test Weak SRAM Cells?

Because weak SRAM cells:

Prone to stability faults

Manifest reliability problems

Can signify defects, which…

Escape regular march tests

Page 8: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

8

What Does SNM Depend On?What Does SNM Depend On?Process variation (mismatch / offset):

VTH spreadLEFF, WEFF spread

Resistance of non-catastrophic defects:RBREAK

RBRIDGE

Operation conditions:VBL

VDD

VWL

T0C

Page 9: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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Static Noise MarginStatic Noise Marginas a Function of Process Variation as a Function of Process Variation

all results for 0.13um technology, all results for 0.13um technology, read-accessed cellread-accessed cell,,

i.e. V i.e. VWLWL=V=VBLBL=V=VDDDD

Page 10: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

10

SNM vs. VSNM vs. VTHTH (Single Transistor) (Single Transistor)

Typical process

corner

SNM=100% @ zero

VTH deviation

Driver strongest

impact, load

weakest impact

Page 11: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

11

SNM vs. VSNM vs. VTH TH (Single Transistor)(Single Transistor)

Typical + slow

process corners

For slow:

SNM>100% @ zero

VTH deviation

Page 12: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

12

SNM vs. VSNM vs. VTH TH (Single Transistor)(Single Transistor)

Typical + slow +

fast process

corners

For fast:

SNM<100% @

zero VTH deviation

Page 13: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

13

SNM vs. VSNM vs. VTH TH (Multiple Transistors)(Multiple Transistors)

Typical process

corner

One VTH changes,

while some other

are biased

Strong SNM

decline for some

VTH combinations

(at max asymmetry)

Page 14: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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SNM vs. LSNM vs. Leffeff and W and Weff eff (Single Transistor)(Single Transistor)

SNM=100% for

typical geometry

Geometry

variations – weak

impact on SNM

(max 7%)

Page 15: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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Static Noise MarginStatic Noise Marginas a Function of Non-Catastrophic as a Function of Non-Catastrophic

Defect ResistanceDefect Resistance

Page 16: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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SNM vs. Break ResistanceSNM vs. Break Resistance

Rbreak SNM

SNM vs. gate

breaks weak

dependence

SNM vs. driver

breaks strong

dependence

Page 17: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

17

SNM vs. Bridge ResistanceSNM vs. Bridge Resistance

Rbridge SNM

SNM vs. Rbridge

uniform

dependence

Page 18: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

18

Static Noise MarginStatic Noise Marginas a Function of Operation as a Function of Operation

Conditions Conditions

Page 19: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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SNM vs. Bit Line VoltageSNM vs. Bit Line Voltage

Typical process

If VBL>0.8V

SNM=100%

If VBL<0.35V

SNM=0% - hard

failure ( normal write)

If 0.35V<VBL>0.8V

SNM linearly

Page 20: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

20

SNM vs. Bit Line VoltageSNM vs. Bit Line Voltage

Typical + slow

process corners

VBL>0.8V

SNM>100%

VBL<0.35V

SNM=0% - hard

failure (or normal

write)

0.35V<VBL>0.8V

SNM linearly

Page 21: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

21

SNM vs. Bit Line VoltageSNM vs. Bit Line Voltage

Typical + slow + fast

process corners

VBL>0.8V

SNM<100%

VBL<0.35V

SNM=0% - hard

failure (or normal

write)

0.35V<VBL>0.8V

SNM linearly

Page 22: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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SNM vs. Global VSNM vs. Global VDDDD

Typical + slow +

fast process

corners (extreme

cases)

SNM linearly

Page 23: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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SNM vs. Local VSNM vs. Local VDDDD

Local resistive

break in local VDD

Typical + slow +

fast process

corners (extreme

cases)

@VDD_LOCAL<0.8V

SNM=0

@VDD_LOCAL>0.8V

SNM linearly

Page 24: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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SNM vs. Word Line VoltageSNM vs. Word Line Voltage

Typical process

Read-accessed

SRAM cell (SNM

deviation @VWL=VDD0%)

@VWL <VTH_ACCESS

SNM=max

@VWL >VTH_ACCESS

SNM linearly

Page 25: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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SNM vs. Word Line VoltageSNM vs. Word Line Voltage

Typical + slow

process corners

Page 26: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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SNM vs. Word Line VoltageSNM vs. Word Line Voltage

Typical + slow +

fast process

corners

Page 27: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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SNM vs. TemperatureSNM vs. Temperature

Weak

dependence

10% max (fast )

2.5% min (slow)

Page 28: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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Proposed Weak Cell Fault Model Proposed Weak Cell Fault Model and a Programmable DFT and a Programmable DFT

TechniqueTechnique

Page 29: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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Weak cell fault modelWeak cell fault model

SNM vs. node-

node R

@Rnode-node

[50k,500k] –

linear

dependence

Page 30: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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BLBBLWL

node A node B

node A node B

Weak cell fault modelWeak cell fault model

• Resistor between

nodes A and B

• Which is equivalent to

• Negative feedback for

inverters of an SRAM

cell

Page 31: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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Vnode A

Vnode B

SNMtyp

SNMweak

VDD

VDD

Vweak

Vgood

Programmable detection conceptProgrammable detection concept

Page 32: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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Vnode A

Vnode B

SNMtyp

SNMweak

VDD

VDD

Vweak

Vgood

VTEST

Programmable detection conceptProgrammable detection concept

@ VTEST:

•weak cell flips

•good cell does not flip

Page 33: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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Vnode B

R = 0 10.5

Vnode A

node voltage R

Proposed DFT conceptProposed DFT concept

R number of cells with state "0" in a set of cellsn

n

• Changing of ratio R

brings nodes to

different potentials

• Weak cell will flip and

will be detected

• Good cell will retain

data

Page 34: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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write 0/1 ratio R

Ø prechargeØ enable n WLsØ short BLsØ disable n WLsØ release BLs

read n cells back

invert ratio R

more 0/1 ratiosto test?

select next 0/1 ratio

FINISH

yes

no

START

Proposed DFT AlgorithmProposed DFT Algorithm

1. Write background

ratio of zeroes and

ones

2. Normal precharge

3. Enable n word

lines

4. Right after that

short bit lines

5. Release word lines

6. Release bit lines

Page 35: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

35

WD

Word Line decoder

WD logic

WD

WLn

WL3

WL2WL1

Proposed DFT ImplementationProposed DFT Implementation

1. Write background

ratio of zeroes and

ones

2. Normal precharge

3. Enable n word lines

4. Right after that short

bit lines

5. Release word lines

6. Release bit lines

Page 36: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

36

Proposed DFT Simulation ResultsProposed DFT Simulation Results

• Rweak=200k

(~65% SNM)

• Five “0”,

three ”1”

• Weak cell is

detected!

Page 37: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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Proposed DFT Simulation ResultsProposed DFT Simulation Results

• Rweak=200k

(~65% SNM)

• Three “0”,

five ”1”

• Weak cell is

not detected

Page 38: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

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Proposed DFT detection capabilityProposed DFT detection capability

• Rweak=100k-

500k

• Five “0”,

three ”1”

• Weak cell

flips for

Rweak<200k

Page 39: Weak SRAM Cell Fault Model and a DFT Technique Mohammad Sharifkhani, with special thanks to Andrei Pavlov University of Waterloo

39

ConclusionsConclusions

Weak SRAM cells can escape march tests

need DFT

Cell stability is sensitive to process and

operation disturbances

Weak cell fault model is essential in developing

test techniques

Proposed DFT efficiently detects weak SRAM

cells, i.e. cells with inadequate SNM