weak sram cell fault model and a dft technique

Weak SRAM Cell Fault ModelWeak SRAM Cell Fault Model andand

a DFT Techniquea DFT TechniqueMohammad Sharifkhani,

with special thanks to

Andrei PavlovUniversity 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

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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

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

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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:

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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

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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

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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

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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

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

Typical process

corner

SNM=100% @ zero

VTH deviation

Driver strongest

impact, load

weakest impact

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

Typical + slow

process corners

For slow:

SNM>100% @ zero

VTH deviation

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

Typical + slow +

fast process

corners

For fast:

SNM<100% @

zero VTH deviation

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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)

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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%)

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

Defect ResistanceDefect Resistance

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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

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SNM vs. Bridge ResistanceSNM vs. Bridge Resistance

Rbridge SNM

SNM vs. Rbridge

uniform

dependence

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

Conditions Conditions

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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

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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

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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

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SNM vs. Global VSNM vs. Global VDDDD

Typical + slow +

fast process

corners (extreme

cases)

SNM linearly

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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

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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

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SNM vs. Word Line VoltageSNM vs. Word Line Voltage

Typical + slow

process corners

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SNM vs. Word Line VoltageSNM vs. Word Line Voltage

Typical + slow +

fast process

corners

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SNM vs. TemperatureSNM vs. Temperature

Weak

dependence

10% max (fast )

2.5% min (slow)

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

TechniqueTechnique

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Weak cell fault modelWeak cell fault model

SNM vs. node-

node R

@Rnode-node

[50k,500k] –

linear

dependence

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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

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Vnode A

Vnode B

SNMtyp

SNMweak

VDD

VDD

Vweak

Vgood

Programmable detection conceptProgrammable detection concept

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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

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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

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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

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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

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Proposed DFT Simulation ResultsProposed DFT Simulation Results

• Rweak=200k

(~65% SNM)

• Five “0”,

three ”1”

• Weak cell is

detected!

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Proposed DFT Simulation ResultsProposed DFT Simulation Results

• Rweak=200k

(~65% SNM)

• Three “0”,

five ”1”

• Weak cell is

not detected

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Proposed DFT detection capabilityProposed DFT detection capability

• Rweak=100k-

500k

• Five “0”,

three ”1”

• Weak cell

flips for

Rweak<200k

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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