Testing Semiconductor
Memories
Cheng-Wen Wu 吳誠文
Lab for Reliable Computing
Dept. Electrical Engineering
National Tsing Hua University
Outline
 Introduction
 RAM functional fault models and test
algorithms
 RAM fault-coverage analysis
 Cocktail-March for testing wordoriented memories
 Testing multi-port RAMs
 Testing CAMs
 Testing flash memories
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Introduction
 Memory testing is a more and more important issue
 RAMs are key components for electronic systems
 Memories represent about 30% of the semiconductor market
 Embedded memories are dominating the chip yield
 Memory testing is more and more difficult
 Growing density, capacity, and speed
 Emerging new architectures and technologies
 Embedded memories: access, diagnostics & repair, heterogeneity,
custom design, power & noise, scheduling, compression, etc.
 Cost drives the need for more efficient test methodologies
 IFA, fault modeling and simulation, test algorithm development and
evaluation, diagnostics, DFT, BIST, BIRA, BISR, etc.
 Test automation is required
 Failure analysis, fault simulation, ATG, and diagnostics
 BIST/BIRA/BISR generation
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Typical RAM Production Flow
Wafer
Marking
Final Test
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Full Probe Test
Laser Repair
Post-BI Test
Burn-In (BI)
Visual Inspection
QA Sample Test
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Packaging
Pre-BI Test
Shipping
4
Scope of RAM Testing
 Parametric Test: DC & AC
 Reliability Screening
 Long-cycle testing
 Burn-in: static & dynamic BI
 Functional Test
 Device characterization
 Failure analysis
 Fault modeling
 Simple but effective (accurate & realistic?)
 Test algorithm generation
 Small number of test patterns (data backgrounds)
 High fault coverage
 Short test time
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RAM Models
 Behavior Level
 Verilog/VHDL
 Function Level
 Verilog/VHDL/Block diagram
 Normally not synthesizable
 Circuit Level
 Spice/Schematic
 Layout Level
 GDS-II/Geometry
☞Who should provide the model?
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Memory Function Model Example
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RAM Fault Models (Static)
 Address-Decoder Fault (AF)
 No cell accessed by certain address
 Multiple cells accessed by certain address
 Certain cell not accessed by any address
 Certain cell accessed by multiple addresses
 Stuck-At Fault (SAF)
 Cell (line) SA0 or SA1
 Transition Fault (TF)
 Cell fails to transit from 0 to 1 or 1 to 0
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RAM Fault Models (Static)
 Bridging Fault (BF)
 Short between cells
 AND type or OR type
 Stuck-Open Fault (SOF)
 Cell not accessible due to broken line
 Neighborhood Pattern Sensitive Fault (NPSF)
 Active (Dynamic) NPSF
 Passive NPSF
W
 Static NPSF
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N
BC
S
E
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RAM Fault Models (Static)
 Coupling Fault (CF)
 State Coupling Fault (CFst)
 Coupled (victim) cell is forced to 0 or 1 if coupling
(aggressor) cell is in given state
 Inversion Coupling Fault (CFin)
 Transition in coupling cell complements (inverts)
coupled cell
 Idempotent Coupling Fault (CFid)
 Coupled cell is forced to 0 or 1 if coupling cell
transits from 0 to 1 or 1 to 0
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RAM Fault Models (Dynamic)
 Recovery Fault (RF)
 Sense Amplifier Recovery Fault (SARF)
 Sense amp saturation after reading/writing long run
of 0 or 1
 Write Recovery Fault (WRF)
 Write followed by reading/writing at different location
resulting in reading/writing at same location
 Write-after-write recovery fault
 Read-after-write recovery fault
 Results in functional faults---detected at high
speed (e.g., GALROW/GALCOL)
 Disturb Fault (DF)
 Victim cell forced to 0 or 1 if we read or write
aggressor cell (may be the same cell)
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RAM Fault Models (Dynamic)
 Data Retention Fault (DRF)
 DRAM
 Refresh Fault
 Refresh-Line Stuck-At Fault
 Leakage Fault
 Sleeping Sickness---loose data in less than
specified hold time (typically tens of ms)
 SRAM
 Leakage Fault
 Static Data Losses---defective pull-up
 Checkerboard pattern triggers max leakage
 BIST good for sync with refresh mechanism
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Test Time Complexity (100MHz)
S ize
N lo g N
1M
0 .0 1 s
0 .1 s
0 .2 s
11s
3h
16M
0 .1 6 s
1 .6 s
3 .9 s
11m
33d
64M
0 .6 6 s
6 .6 s
17s
1 .5 h
1 .4 3 y
256M
2 .6 2 s
26s
1 .2 3 m
12h
23y
1G
1 0 .5 s
1 .8 m
5 .3 m
4d
366y
4G
42s
7m
2 2 .4 m
32d
57c
2 .8 m
28m
1 .6 h
255d
915c
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N
2
10N
16G
N
1 .5
N
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RAM Test Algorithm
 A test algorithm (or simply test) is a finite
sequence of test elements
 A test element contains a number of memory
operations (access commands)
 Data pattern (background) specified for the Read
operation
 Address (sequence) specified for the Read and
Write operations
 A march test algorithm is a finite sequence of
march elements
 A march element is specified by an address order
and a number of Read/Write operations
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Classical Test Algorithms
 Zero-One Algorithm [Breuer & Friedman 1976]
 Also known as MSCAN
 For SAF
 Solid background (pattern)
 Complexity is 4N
{ ( w 0 );  ( r 0 );  ( w1);  ( r1)}
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Classical Test Algorithms
 Checkerboard Algorithm
 Zero-one algorithm with checkerboard pattern
 Complexity is 4N
 For SAF and DRF
1
0
1
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0
1
0
1
0
1
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Classical Test Algorithms
 Galloping Pattern (GALPAT)
 Complexity is 4N**2---only for characterization
 All AFs,TFs, CFs, and SAFs are located
1. Write background 0;
2. For BC = 0 to N-1
{ Complement BC;
For OC = 0 to N-1, OC != BC;
{ Read BC; Read OC; }
Complement BC; }
3. Write background 1;
4. Repeat Step 2;
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BC
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Classical Test Algorithms
 Sliding (Galloping) Row/Column/Diagonal
 Based on GALPAT, but instead of a bit, a complete
row, column, or diagonal is shifted
 Complexity is 4N**1.5
1
1
1
1
1
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Classical Test Algorithms
 Butterfly Algorithm
 Complexity is 5NlogN
1. Write background 0;
2. For BC = 0 to N-1
{ Complement BC; dist = 1;
While dist <= mdist /* mdist < 0.5 col/row length */
6
{ Read cell @ dist north from BC;
Read cell @ dist east from BC;
1
Read cell @ dist south from BC;
9
4
5 ,1 0
2
Read cell @ dist west from BC;
3
Read BC; dist *= 2; }
8
Complement BC; }
3. Write background 1; repeat Step 2;
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Classical Test Algorithms
 Moving Inversion (MOVI) Algorithm [De Jonge &
Smeulders 1976]
 For functional and AC parametric test
 Functional (13N): for AF, SAF, TF, and most CF
{  ( w 0 );  ( r 0 , w 1, r 1 );  ( r 1, w 0 , r 0 );  ( r 0 , w 1, r 1 );  ( r 1, w 0 , r 0 )}
 Parametric (12NlogN): for Read access time
 2 successive Reads @ 2 different addresses with
different data for all 2-address sequences differing
in 1 bit
 Repeat T2~T5 for each address bit
 GALPAT---all 2-address sequences
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Classical Test Algorithms
 Surround Disturb Algorithm
 Examine how the cells in a row are affected when
complementary data are written into adjacent cells
of neighboring rows
1. For each cell[p,q] /* row p and column q */
{ Write 0 in cell[p,q-1];
Write 0 in cell[p,q];
Write 0 in cell[p,q+1];
Write 1 in cell[p-1,q];
Read 0 from cell[p,q+1];
Write 1 in cell[p+1,q];
Read 0 from cell[p,q-1];
Read 0 from cell[p,q]; }
2. Repeat Step 1 with complementary data;
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1
0
0
0
1
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Classical Test Algorithms
 Zero-one and checkerboard algorithms do not
have sufficient coverage
 Other algorithms are too time-consuming for large
RAM
 Test time is the key factor of test cost
 Complexity ranges from N2 to NlogN
 Need linear-time test algorithms with small
constants
 March test algorithms
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March Tests
 Zero-One (MSCAN) { ( w 0 );  ( r 0 );  ( w1);  ( r1)}
 Modified Algorithmic Test Sequence (MATS)
[Nair,
Thatte & Abraham 1979]
 OR-type address decoder fault
{ ( w 0 );  ( r 0 , w1);  ( r1)}
 AND-type address decoder fault
{ ( w1);  ( r1, w 0 );  ( r 0 )}
 MATS+ [Abadir & Reghbati 1983]
 For both OR- & AND-type AFs and SAF
{ ( w 0 );  ( r 0 , w 1);  ( r1, w 0 )}
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March Tests
 Marching 1/0 [Breuer & Friedman 1976]
 For AF, SAF, and TF
{ ( w 0 );  ( r 0 , w 1, r 1);  ( r 1, w 0 , r 0 );
 ( w 1);  ( r 1, w 0 , r 0 );  ( r 0 , w 1, r 1)}
 MATS++ [Goor 1991]
 Also for AF, SAF, and TF
 Complete and irredundant
{ ( w 0 );  ( r 0 , w1);  ( r1, w 0 , r 0 )}
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March Tests
 March X
 For AF, SAF, TF, & CFin
{ ( w 0 );  ( r 0 , w1);  ( r1, w 0 );  ( r 0 )}
 March C [Marinescu 1982]
 For AF, SAF, TF, & all CFs---redundant
{ ( w 0 );  ( r 0 , w 1);  ( r1, w 0 );
 ( r 0 );  ( r 0 , w 1);  ( r 1, w 0 );  ( r 0 )}
 March C- [Goor 1991]
 Also for AF, SAF, TF, & all CFs---irredundant
{ ( w 0 );  ( r 0 , w 1);  ( r1, w 0 );
 ( r 0 , w 1);  ( r1, w 0 );  ( r 0 )}
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March Tests
 Limitations
 Sequential faults in address decoders
 RF
 NPSF
 (9N-2) for 2-CF [Marinescu 1982]
 (2NlogN+11N) for 3-CF [Cockburn 1994]
 Solutions
 Address sequence variation
 Hopping
 Pseudorandom
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Coverage of March Tests
SAF
TF
AF
SOF
C F in
C F id
C F st
M AT S + + M arch X M arch Y M arch C 1
1
1
1
1
1
1
1
1
1
1
1
1
.002
1
.002
.75
1
1
1
.375
.5
.5
1
.5
.625
.625
1
☞ Extended March C- (11N) has a 100% coverage of SOF
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Testing Word-Oriented RAM
 Background bit is replaced by background word
 MATS++:
{ ( wa );  ( ra , wa ' );  ( ra ' , wa , ra )}
 Conventional method is to use logm+1 different
backgrounds for m-bit words
 m=8: 00000000, 01010101, 00110011, and
00001111
 Apply the test algorithm logm+1=4 times, so
complexity is 4*6N/8=3N
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Cocktail-March Algorithms
 Motivation:
 Repeating the same algorithm for all logm+1
backgrounds has redundancy
 Different algorithm targets different faults
 Approach:
 Use multiple backgrounds in a single algorithm run
 Merge and forge different algorithms and
backgrounds into a single algorithm
 Good for word-oriented memories
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March-CW
 Algorithm:
 March C- for solid background (0000)
 Then a 5N March for each of other standard
backgrounds (0101, 0011):
 Result:
{ ( wa , wa ' , ra ' , wa , ra )}
 Complexity is (10+5logW)N, where W is word
length and N is word count
 Test time is reduced by 39% if W=4, as compared
with extended March C Improvement increases as W increases
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Comparison (Full Coverage)
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Testing NPSF
 NPSF test approaches
 Tiling
 Multi-background march
 Easy BIST implementation
 5-cell neighborhood
B
S
E
W
N
B
S
E
W
N
B
E
B ase cell: B
D eleted neighborhood cells: N , E, W , S
N eighborhood cells: B and N , E, W , S
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NPSF Models
 Static NPSF (SNPSF)
 BC forced to a certain state due to a certain deleted
neighborhood (DN) pattern
 Passive NPSF (PNPSF)
 BC frozen due to a certain DN pattern
 Active NPSF (ANPSF)
 BC content changes due to a change in DN pattern
 Change: a transition in one DN cell, with other DN cells & BC
containing a certain pattern
 Assumptions:
 Single NPSF
 Address scramble table is available
 Memory is bit-oriented
 Word-oriented memory is tested as multiple bit-oriented ones
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Test Strategy
 Multi-Background March
 To generate all neighborhood patterns
Solid BG
(FC < 30%)
Another BG
0 0 0
0 0 0
0 0 0
0 0 0
0 X 0
0 0 0
0 0 0
0 X 1
1 1 1
1 1 1
1 X 0
0 0 0
1 1 1
1 X 1
1 1 1
1 0 1
1 0 1
1 0 1
1 0 1
1 X 1
1 0 1
0 1 0
0 X 0
0 1 0
0 1 0
0 X 1
1 0 1
1 0 1
1 X 0
0 1 0
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Testing PNPSF
 March 17N:
( w a );
( w b , ra , w a );
( rb , w a );
(ra , w b );
( ra ,w b );
(rb , w a );
M arch E lem ents
(rb , w a , ra , w b );
(ra )
NW BES
A lg1:
(w 0);
(w 1, r1, w 0);
(r0); 0 0
00
A lg2:
(w 1);
(w 0, r0, w 1);
(r1); 1 1
11
A lg3:
(w 0);
(w 1);
(r1);
11
00
A lg4:
(w 1);
(w 0);
(r0);
11
00
A lg5:
(w 0);
(w 1);
(r1);
00
11
A lg6:
(w 1);
(w 0);
(r0);
00
11
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Data Background Generation
 Data backgrounds
 BG1: all zero
 BG2: Ar[0], LSB of row address
 BG3: Ar[1], second bit of row address
 BG4: Ar[0]Ar[1]
00 01 10 11
00 0 0 0 0
01 0 0 0 0
10 0 0 0 0
11 0 0 0 0
B G .1
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00 01 10 11
00 0 0 0 0
01 1 1 1 1
10 0 0 0 0
11 1 1 1 1
B G .2
00 01 10 11
00 0 0 0 0
01 0 0 0 0
10 1 1 1 1
11 1 1 1 1
B G .3
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00 01 10 11
00 0 0 0 0
01 1 1 1 1
10 1 1 1 1
11 0 0 0 0
B G .4
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Testing ANPSF
(w0) ;
(w1) ;
(w0) ;
( r0 ,w1,w0) ;
(r0)
( r1 ,w0,w1) ;
( r0 ,w1) ;
(r1)
( r1 ,w0) ;
0 0 0
0
0
0 0
0
0
0 0 0
0
0 0
0
1 1 1
1
1
1 1
1
1
1 1 1
1
1 1
1
0
1 1
1
0
0 0
1
(r0)
1
0 0
0
1
1 1
0
 March 12N:
(w a);
(w b, ra, w a);
(rb, w a);
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(ra, w b);
(rb, w a, w b);
(ra)
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Time Complexity
00 01 10 11
00
01
10
11
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
00 01 10 11
00
01
10
11
0
1
0
1
BG.1
0
0
0
0
0
0
0
0
1
1
1
1
BG.5
0
1
0
1
1
0
1
0
00
01
10
11
0
1
0
1
BG.2
1
1
1
1
00
01
10
11
0
1
0
1
0
1
0
1
1
0
1
0
0
1
0
1
0
1
0
1
0
1
0
1
00 01 10 11
00
01
10
11
0
0
0
0
BG.3
00 01 10 11
00 01 10 11
00
01
10
11
1
0
1
0
00 01 10 11
1
0
1
0
BG.6
0
0
0
0
1
1
1
1
1
1
1
1
BG.7
0
0
0
0
1
1
1
1
BG.4
00 01 10 11
00
01
10
11
1
1
1
1
0
0
0
0
00 01 10 11
00
01
10
11
0
1
0
1
1
0
1
0
1
0
1
0
0
1
0
1
BG.8
 12 N/BG X 8 BG = 96N
 Detects all NPSFs
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Multi-Port Memories
 Popular architectures
 k-port (k > 1)
 n-read-1-write
 FIFO
Address A
Port A
Data A
Control A
Storage
Address B
Port B
Data B
Control B
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2-Port Topology
BL A
W LA
BL A
BL A
BL A
3
Interport W L short
W LA
W LB
1
W LB
Interport BL short
W LA
2

W LA

BL B
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BL B
BL B
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W LB
W LB
BL B
40
Inter-Port Word-Line Short
F au lt-F ree
Port A
Port B
Address 1
Address 2
F au lty
Cell 1
Address 1
Cell 1
Address 2
Cell 2
Address 3
Cell 3
Cell 2
* Functional test complexity: O(N3)
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Inter-Port Bit-Line Short
F au lt-F ree
Port A
Port B
Address
Address


F au lty
Address

Cell 
Address

Cell 
Address

Cell 
Address

Cell 
Cell 
Cell 
* Functional test complexity: O(N2)
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Address Scrambling
Logical Addr
A
B
C
D
A - word line select
B - I/O select
C - bit line select
Physical Addr
7
6
5
4
3
2
1
0
8
7
row
6
5
4
3
2
1
0
D - bit position in a word
column
A d d ress A
b it3
b it2
b it1
b it0
D ata w o rd A
3
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Reading Neighboring Cells
 Read neighboring cells to detect inter-port faults:
rN, rS, rE, and rW
N
W
B
S
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E
0
0
0
1
1
1
0
0/1
1
1
1/0
0
1
1
1
0
0
0
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TAGS-PS
March Test
Section 1
Port 1
Section 2
Single-port
Test Algorithm
Multi-port
AF Test
Section 3
Inter-port
Test
Port 2
Port m
(a)
Port 1
Port 2
Single-port
Test Algorithm
Multi-port
AF Test
Inter-port
MPF Test
Port m
(b)
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Dual-Port RAM Test
Section 1
Section 2
Section 3
Port 1
w0
r0 w 1 r 1 w 0 r0 w 1 r 1 r 1 w 0 r0
r0
r0 w 1 r 1 w 0
- -
Port 2
-
- -
-
- -
r0 w 1 r 1 w 0
- -
- - -
- - -
- -
- -
r0 w 1 r 1 w 0
N
S
r 1r 0
N
(a)
Section 1
Section 2
Port 1
w0
r0 w 1 r 1 w 0 r0 w 1 r 1 r 1 w 0 r0
Port 2
-
r 1r 0
N
S
N
S
r 0r 1
- - -
- - -
r0
r0 w 1 r 1 w 0
- -
-
- -
r0 w 1 r 1 w 0
- -
- -
Section 3
(b)
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r 0r 1
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Compacted Dual-Port RAM Test
S e c tio n 1
P o rt 1
w0
P o rt 2
-
r0 w 1
N
r 1r
S
0
r1w0
N
r 0r
S
1
- - r1
r0 w 1 -
- - r0
r0
r1w0 -
-
S e c tio n 2
(c )
P o rt 1
w0
P o rt 2
-
r0 w 1
N
r 1r
S
0
r1w0
N
r 0r
S
1
- -
- -
r0
r0 w 1
r1w0
(d )
* Time complexity: 10N
mbist1.10
Cheng-Wen Wu, NTHU
47
Four-Port RAM Test
AF Test
Port 1
w0
r0 w 1
Port 2
-
r 1r
Port 3
-
r 1r
Port 4
-
r 1r
r 1w 0
- -
- -
- -
- -
- -
- -
r 1w 0
- -
- -
- -
- -
r 1w 0
- -
- -
r0 w 1
r 1w 0
N
S
r
N
r
S
r0 w 1
N
S
r
N
r
S
r 1r
N
S
r
N
r
S
r 1r
0
0
0
0
0
0
1
1
1
S
N
r
S
r
N
r0 w 1
S
N
r
S
r
N
r 1r
0
0
0
0
1
1
N
S
0
r
N
0
r
S
1
Inter-port Test
* Time complexity: 17N
mbist1.10
Cheng-Wen Wu, NTHU
48
Testing 6-Read-1-Write RAM
M0
M1
P o rt 1
w0
-
w1
P o rt 2
-
r0 r
P o rt 3
-
r
P o rt 4
M2
-
M3
w0
-
w1
r
N
-
r
N
r1 r
N
r
N
-
r
N
-
S
r0 r
N
r
S
r
N
r
N
-
r
N
-
r
S
r
r
N
r
S
r
N
r
N
-
r
N
-
S
r1 r
S
r0 r
N
r1 r
N
r0 -
r1 -
S
r1 r
S
r
N
r1 r
N
r0 -
r1 -
r1 r
S
r
-
r0 r
S
r
N
r
r
r
S
r
N
P o rt 5
-
P o rt 6
-
r0 r
P o rt 7
-
r
r
w0
-
S
1
-
N
r
N
w1
r
r0 r
1
-
N
S
N
w0
M6
r1 r
r1 r
1
-
M5
N
S
N
M4
0
0
0
0
0
0
0
0
1
1
1
1
1
1
T e st fo r p o rts o f
d ista n c e 1
S
1
S
1
S
1
r
0
0
0
0
0
0
0
0
1
1
1
1
1
1
T e st fo r p o rts o f
d ista n c e 2
1
1
1
1
0
0
0
0
T e st fo r p o rts o f
d ista n c e 3
* Time complexity: 13N
mbist1.10
Cheng-Wen Wu, NTHU
49
Flash Memory Testing
 Testing nonvolatile memories:
 Masked ROM---exhaustive; pseudorandom
 PROM (OTP) & EPROM---dummy row
 EEPROM & flash memory---dummy row?
 Testing flash memory core is hard
 Customized core and I/O
 Isolation (accessibility)
 Reliability issues: disturbances, over
program/erase, under program/erase, data
retention, cell endurance, etc.
 Long program/erase time
mbist1.10
Cheng-Wen Wu, NTHU
50
Flash Memory Overview
 Flash memory can be programmed and erased
electrically
 Has the advantages of EPROM and EEPROM
 A stacked gate transistor with both the control
gate (CG) and floating gate (FG):
Control gate
Floating gate
Drain
Source
n+
n+
P-Si
mbist1.10
D
G
S
Cheng-Wen Wu, NTHU
51
Flash Memory Program & Erase
• Program(1 to 0): channel hot-electron (CHE) injection or FowlerNordheim (FN) electron tunneling
• Erase (0 to 1): FN electron tunneling
• By the entire chip or large blocks (flash erasure)
• Different products have different program/erase mechanisms
Program
mbist1.10
Erase
Cheng-Wen Wu, NTHU
52
Flash Memory Cell Types
 Stacked-gate
Split-gate
Select-gate
 Operations: Read, Program, Erase (Flash Erase)
 As opposed to Read and Write in RAM
mbist1.10
Cheng-Wen Wu, NTHU
53
Programming Scheme Comparison
C H E In je c tio n
C h a n n e l F N Tu n n e lin g
H ig h p o w e r (d u a l
e x te rn a l s u p p lie s )
L o w p o w e r (s in g le
e x te rn a l s u p p ly )
L o w o x id e fie ld s tre s s
H ig h o x id e fie ld s tre s s
F a s te r p ro g ra m
o p e ra tio n (b y te p ro g ra m
lim ite d b y p o w e r)
S lo w e r p ro g ra m
o p e ra tio n (im p ro v e d b y
pa g e p ro g ra m )
mbist1.10
Cheng-Wen Wu, NTHU
54
NOR-Array Structure
mbist1.10
Cheng-Wen Wu, NTHU
55
NAND-Array Structure
Select (drain)
WL 1
WL 2
WL 3
WL 4
WL 16
Select (source)
BL i
mbist1.10
Cheng-Wen Wu, NTHU
56
Disturbance Example (I)
Program Disturbance
BL 0
WL
SL
BL 1
BL 2
SL
BL 3
0V
0
0V
6V
Drain-Disturb on "Programmed Cell"
WL
10V
1
0V
10V
0V
6V
Programming
WL
10V
0V
0V
Gate-Disturb on "Erased Cell"
2
NOR-Type Common Ground – Standard (Stacked Gate)
mbist1.10
Cheng-Wen Wu, NTHU
57
Disturbance Example (II)
Read Disturbance
BL 0
WL
0
WL
1
SL
BL 1
BL 2
SL
BL 3
5V
0V
1V
Soft-Program on "Selected Cell"
WL
2
mbist1.10
Cheng-Wen Wu, NTHU
58
Disturbance Example (III)
Program Disturbance
BL 0
SSL
BL 2
BL 1
3.3V
0V
3.3V
3.3V
Gate-Disturb on "Erased Cell"
0V
WL
10V
0
2.8V
WL
1
0V
18V
18V
Program '1'
Program '0'
2.8V
WL
2
GSL
mbist1.10
10V
0V
10V
2.8V
Gate-Disturb on "Programmed Cell"
0V
0V
Cheng-Wen Wu, NTHU
0V
59
Disturbance Example (IV)
Read Disturbance
BL 0
BL 1
Erase Disturbance
BL 2
5V
BL 0
0.7V
5V
SSL
5V
WL
0
5V
5V
WL
0
21V
0V
21V
0V
21V
WL
1
0V
0V
WL
1
21V
0V
21V
0V
21V
WL
2
21V
0V
21V
0V
21V
V th =+2V
WL
2
5V
SSL
BL 2
BL 1
Floating
Floating
V th =-3V
5V
soft-program
GSL
5V
mbist1.10
5V
GSL
Cheng-Wen Wu, NTHU
Floating
Floating
60
Gate Program Disturb Fault (GPDF)
Conditions:
G
1.Victim cell initial value is a logic ‘1’
2.Aggressor “10” (program)
Control Gate
S
Floating Gate
D
Victim “10” (program)
V(L)
Source
Drain
V(H)
V(H)
Substrate
V(L)
B
V(Gd)
mbist1.10
Cheng-Wen Wu, NTHU
61
Gate Erase Disturb Fault (GEDF)
Conditions:
G
1.Victim cell initial value is a logic ‘0’
2.Aggressor “10” (program)
Control Gate
S
Floating Gate
Source
D
Victim “01” (erase)
V(L)
Drain
V(H)
V(H)
Substrate
V(L)
B
V(Gd)
mbist1.10
Cheng-Wen Wu, NTHU
62
Drain Program Disturb Fault (DPDF)
Conditions:
1.Victim cell initial value is a logic ‘1’
2.Aggressor “10” (program) Victim “10” (program)
V(H)
• During programming, erased cells on
unselected rows on a bit-line that is being
programmed may have a fairly deep
depletion region formed under them
V(H)
• Electrons entering this depletion region can
be accelerated by the electric field and
injected over the oxide potential barrier to
adjacent floating gates
V(L)
V(Gd)
mbist1.10
Cheng-Wen Wu, NTHU
63
Drain Erase Disturb Fault (DEDF)
Conditions:
1.Victim cell initial value is a logic ‘0’
G
2.Aggressor “10” (program)
Victim “01” (erase)
Control Gate
S
Floating Gate
Source
D
V(L)
Drain
V(H)
V(H)
Substrate
V(L)
B
V(Gd)
mbist1.10
Cheng-Wen Wu, NTHU
64
Read Disturb Fault (RDF)
Conditions:
1. Occurs on the selected cell
G
2. Cell initial value is logic ‘1’
Control Gate
S
Floating Gate
Source
Soft-Program
Drain
Substrate
B
mbist1.10
D
• During the read operation,
hot carriers can be injected
from the channel into the FG
even if at low gate voltages
Cheng-Wen Wu, NTHU
65
Over Erase Fault (OEF)
 Flash memory erase mechanism is not
self-limiting
 Threshold voltage can be low enough to
turn the cell into a depletion-mode
transistor
 Fault behavior:
 An unselected cell in the same bit-line has
excessive source-drain leakage current
 Reading that cell leads to incorrect value
(like DEDF)
 Cannot be programmed correctly (like TF)
mbist1.10
Cheng-Wen Wu, NTHU
66
Basic RAM Faults for Flash Memory
 Address-Decoder Fault (AF)
 Stuck-At Fault (SAF)
 Transition Fault (TF)
 Stuck-Open Fault (SOF)
 Bridging Fault (BF)
 Coupling faults need not be considered!
Replaced by disturb faults
mbist1.10
Cheng-Wen Wu, NTHU
67
Reliability Consideration
 Reliability characteristics of floating-gate
ICs depend on
 Circuit density, circuit design, and process
integrity
 Memory array type and cell structure
 Reliability stressing and testing must then
be oriented toward determining the relevant
failure rates for the particular array under
consideration
mbist1.10
Cheng-Wen Wu, NTHU
68
Data Retention Fault
 Retention time: the time from data storage to the
time at which a verifiable error is detected from
any cause
 Intrinsic retention times exceed millions of years in
the operating temperature range
 Months at 300°C
 1 million years at 150 °C
 120 million years at 55 °C
 Data Retention Fault (DRF)
 Static leakage
 Built-in data retention test circuit
mbist1.10
Cheng-Wen Wu, NTHU
69
Cell Endurance Fault
 Endurance: a measure of the ability to meet datasheet specifications as a function of accumulated
program/erase cycles
 Endurance limit is a result of damage to the
dielectric around the floating gate caused by
electric stresses
 In many flash devices, the end of endurance is
generally caused by hot electron trapping in the
charge transport oxide
 Cell Endurance Fault (CEF)
 Threshold window shift due to increased
program/erase cycles
 Built-in stress test circuit
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70
Composite Failure Rate Determination
 125°C dynamic life stress
 The 125°C dynamic life stress is the standard MOS
memory continuous dynamic read in a burn-in
chamber
 Endurance test
 The endurance test is the repeated data
complementing of floating-gate devices, possibly at
temperature extremes
 Extended data retention stress
 This test is constituted by a high-temperature bake
with a charge polarity that is opposite to the
equilibrium state on the floating gate
mbist1.10
Cheng-Wen Wu, NTHU
71
Typical Test Modes (Characterization)
 Stress (row/column)
 Reverse tunneling stress
 Punch through stress
 Tox stress
 DC stress






Mass program
Weak erase
Leak (thin-oxide, bit-line, etc.)
Cell current; cell Vt
Margin
Etc.
mbist1.10
Cheng-Wen Wu, NTHU
72
Test Patterns
 A RAM test pattern definition includes both the
data pattern and the address pattern
 The time to read a pattern is the same as the time
to write a pattern
 For flash memories, however, the address and
data pattern definitions must be segregated
 It has long write times relative to the read times
 Typical data patterns:
 Solid, checkerboard, random, etc.
 Typical address patterns:
 Address increment/decrement, address
complement, column/diagonal galloping, etc.
mbist1.10
Cheng-Wen Wu, NTHU
73
Testing GPDF
 Flash
 Program the first column
 Read all cells except the first column
 Flash
 Program any column except the first
 Read the first column
*Assume reading and programming are done column-wise
Source: Saluja, et al., Int. Conf. VLSI Design, 2000
mbist1.10
Cheng-Wen Wu, NTHU
74
Testing GEDF
 Flash
 Program all cells
 Read all cells except the last column
 Program any column except the last
 Read the last column
*Assume reading and programming are done column-wise
Source: Saluja, et al., Int. Conf. VLSI Design, 2000
mbist1.10
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75
Test Coverage: Previous Results
Fault
DCP
DCE
DD
EF
GF
SAF
50%
50%
50%
100%
100%
TF
12.5%
50%
50%
87.5%
62.5%
AF
40%
0%
0%
44.5%
40%
SOF
0%
0%
0%
12.5%
6.2%
CFst
25%
25%
25%
50%
50%
GPDF
33.3%
0%
0%
100%
33.3%
GEDF
0%
100%
75%
100%
100%
DEDF
0%
75%
100%
100%
100%
DPDF
0%
0%
0%
0%
0%
Source: Saluja, et al., Int. Conf. VLSI Design, 2000
mbist1.10
Cheng-Wen Wu, NTHU
76
March-Based Flash Test: March-FT
 {(f); (r1,w0,r0); (r0); (f); (r1,w0,r0); (r0)}
This Flash memory is NOR type (Stacked gate).
Memory size (N) : 65536
Test length : 2(chip erase time) + 131072(word program time) + 393216(word read time)
Test time : 7.207173 sec
SAF : 100%
(131072 / 131072)
TF : 100%
(131072 / 131072)
Flash Type = NOR
SOF : 100%
(65536 / 65536)
Gate Type = Stack
AF : 100%
(4294901760 / 4294901760)
Row Number = 256
CFst : 100%
(17179607040 / 17179607040)
Col Number = 256
GPD : 100%
(16711680 / 16711680)
Word Length = 1
GED : 100%
(16711680 / 16711680)
Chip erase time = 3 sec
DPD : 100%
(16711680 / 16711680)
Word program time = 9u sec
DED : 100%
(16711680 / 16711680)
Word read time = 70n sec
RD : 100%
(65536 / 65536)
OE : 100%
(65536 / 65536)
mbist1.10
Cheng-Wen Wu, NTHU
P.S.
77
Test Length (Bit-Oriented)
 Notation:
DCP 2(F) + 2r(P) + rc(R)
 F : Flash time
 P : Program time
DCE (F) + (c+1)r(P) + rc(R)
 R : Read time
DD
(F) + (r+1)c(P) + rc(R)
 r : row number
EF
2(F) + (rc+2r+c-2)(P) +
(2rc+r+c-3)(R)
GF
2(F) + (rc+2r+c-1)(P) +
(2rc+c+r-2)(R)
FT
2(F) + 2rc(P) + 6rc(R)
 c : column number
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Cheng-Wen Wu, NTHU
78
Test Length (Word-Oriented)
 Word length = w:
 2(F)+2rc(P)+6rc(R)+log(w)[2(F)+rc(P)+rc(R)]
solid background
standard background
testing time
testing time
 Solid: 0000 (1111)
 Standard: 0101 (1010), 0011 (1100)
 Ex: word length w = 4
 6(F) + 4rc(P) + 8rc(R)
mbist1.10
Cheng-Wen Wu, NTHU
79
Test Algorithm Generation by Simulation (TAGS)
T(N) Test algorithms
2N
(f); (r1)
3N
(f); (w0); (r0)
4N
(f); (r1,w0); (r0)
5N
(f); (r1,w0,r0); (r0)
6N
(f); (r1,w0,r0); (r0,w0)
7N
(f); (r0); (r1,w0,r0); (r0,w0)
8N
(f); (r1,w0); (f); (r1,w0,r0); (r0)
9N
(f); (r1,w0); (r0); (f); (r1,w0,r0); (r0)
10N
(f); (r1,w0,r0); (r0); (f); (r1,w0,r0); (r0)
mbist1.10
Cheng-Wen Wu, NTHU
80
Embedded Memory Testing
 Memories are one of the most universal cores
 In Alpha 21264, cache RAMs represent 2/3
transistors and 1/3 area; in StrongArm SA110, the
embedded RAMs occupy 90% area [Bhavsar, ITC-99]
 In average SOC, memory cores will represent more
than 90% of the chip area by 2010 [ITRS 2000]
 Embedded memory testing is increasingly difficult
 High bandwidth (speed and I/O data width)
 Heterogeneity and plurality
 Isolation (accessibility)
 AC test, diagnostics, and repair
 BIST is considered the best solution
mbist1.10
Cheng-Wen Wu, NTHU
81
Embedded RAM Test Support
Te s t ru n
P ro b e te s t
P re -B I te s t
BI
Po s t-B I te s t
F in a l te s t
mbist1.10
Is o la tio n o n ly Is o la tio n & B IS T
Te ste r
Te ste r/B IS T
Te ste r
B IS T
B I b o a rd
B IS T
Te ste r
B IS T
Te ste r
Te ste r/B IS T
Cheng-Wen Wu, NTHU
82
RAM BIST Approaches
 Methodology
 Processor-based BIST
 Programmable
 Hardwired BIST
 Fast
 Compact
 Interface
 Serial (scan, 1149.1)
 Parallel (embedded controller; hierarchical)
 Patterns (address sequence)
 March
 Pseudorandom
mbist1.10
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83
Typical RAM BIST Architecture
Controller
Pattern
RAM
Generator
Go/No-Go
Comparator
BIST Module
RAM Controller
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84
Serial March (SMarch)
{  ( r x w 0 ) ( r 0 w 0 ) ;  ( r 0 w 1) ( r 1 w1) ;  ( r 1 w 0 ) ( r 0 w 0 ) ;
c
c
c
c
c
c
 ( r 0 w1 ) ( r 1 w1 ) ;  ( r 1 w 0 ) ( r 0 w 0 ) ;  ( r 0 w 0 ) ( r 0 w 0 ) }
c
c
From March C-
•
Serial interface
•
One BIST for all
(cascaded)
•
One-bit read/write at a
time, but one pattern
per cycle
Addr
•
Slow
•
No diagnostics
SI
X Decoder
•
c
c
c
c
Memory Cell Array
Y Decoder
Transparent Serial Data-MUX
c
D
SO
c
Q
Source: Nadeau-Dostie et al., IEEE D&T, Apr. 1990
mbist1.10
Cheng-Wen Wu, NTHU
85
Syntest MBIST

Algorithms:
 March C MOVI
 March C++
 Checkerboard
CE
FSM
OE
WEB
 Shared controller
for multiple RAMs
 Synthesizable RTL
code
ADR Control
A
Data Generator
D
Analyzer
Q
Pass
BistFail
Finish
Source: Syntest
mbist1.10
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86
NTHU/GUC EDO DRAM BIST
mbist1.10
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87
DRAM Page-Mode Read-Write Cycle
mbist1.10
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88
Programmable Memory BIST (PMBIST)
mbist1.10
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89
PMBIST Architecture
mbist1.10
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90
Controller and Sequencer
 Controller
 Microprogram
 Hardwired
 Shared CPU core
 IEEE 1149.1 TAP
 Sequencer (Pattern Generator)
 Counter
 LFSR
 LUT
mbist1.10
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91
Controller
mbist1.10
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92
Sequencer
D Q
D Q
C o m b in a tio n L o gic # 0
D Q
D Q
C o m b in a tio n L o gic # 1
B IS T
C o n tr o lle r
D Q
D Q
R o w A d d r e ss C o u n te r
C o lu m n A d d r e ss
C o u n te r
C o n tr o l C ou n t e r
S ta te
D Q
eD R A M
D Q
eD R A M
c o n tr o l
sign a l
F la gs
MCK
MCK
C o m p ar a to r
mbist1.10
Cheng-Wen Wu, NTHU
93
PMBIST Test Modes
1. Scan-Test Mode
2. RAM-BIST Mode
1.Functional faults
2.Timing faults (setup/hold times, rise/fall times,
etc.)
3.Data retention faults
3. RAM-Diagnosis Mode
4. RAM-BI Mode
mbist1.10
Cheng-Wen Wu, NTHU
94
PMBIST Controller Commands
Bit 4
A ddressing order
Bit 3
D ata type
Bit 2, Bit 1, Bit 0
O perations
1:  (increasing)
1: d = D B
000: EO T
0:  (decreasing)
0: d = ~D B
001: Rd
010: W d
011: RdW ~d
100:
101:
110:
111:
mbist1.10
(End of test)
(REA D C ycle)
(Early W R ITE C ycle)
(REA D -W R ITE) C ycle
ED O -PA G E-M O D E
Wd
(Early W R ITE C ycle
RdW ~d
(REA D -W R ITE) C ycle
RdW ~dR~d (REA D Early W R ITE Cycle)
Refresh
Cheng-Wen Wu, NTHU
95
PMBIST Control Sequence
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BIST Area Overhead
3%
Overhead
Mem size
0.3%
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Processor-Based RAM BIST
Processor
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On-Chip Processor-Based RAM BIST
 BIST program is stored in boot ROM during
design phase, and memory BIST is done by
executing BIST program
Address
bus
DATAI
bus
DATAO
bus
Control
bus
BOOT
ROM
Embedded
memory
CPU core
I/O port
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Testing RAM Core by On-Chip CPU
 6502 assembly program that performs March Ctest algorithm
data background
M0:
M1:
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.org
LDX
LDA
0HFF00
#$$00
#$$55
STA
INX
CPX
BNE
LDX
0000,X
(W0)
#$$FF
M0
#$$00
(R0W1)
LDA
CMP
BNE
LDA
STA
INX
CPX
BNE
LDX
. . . .
0000,X
#$$55
ERROR
#$$AA
0000,X
(R0W1)
#$$FF
M1
#$$00
.
write data background to memory
March C- algorithm
(R1W0)
(R1W0)
(R0)
read from memory
write data background to memory
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Test Speed Consideration
 Processor-BIST speed is lower than dedicated
BIST circuit
 Total clock cycles to implement MARCH C- is
O(114N)
Table 1. 6502 instruction cycles
IM M
ABX
IM P
REL
LD A
2
4
-
-
LD X
2
-
-
-
S TA
-
4
-
-
IN X
-
-
2
-
C PX
2
-
-
-
BNE
-
-
-
2~4
CM P
2
-
-
-
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NTHU Processor-Programmable BIST
ADDR_cpu
0
ADDR
A
1
DATAO_cpu
0
clock_cpu
BIST core
1
mux_sel
ctrl_bist
1
ctrl_cpu
1
DATAI_cpu
control
on-chip bus
embedded
CPU
ADDR_bist
DATAO_bist
DATAO
DATAI_bist
DATAI_sys
embedded
memory
control
0
0
DI
DATAI
DO
BIST circuitry
mux_sel = 0 in normal mode
mux_sel = 1 in BIST mode
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I/O circuitry
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Advantages and Disadvantages
 Advantages
 Reuse of on-chip CPU core
 Might need modification
 Core March elements can be implemented in
hardware, allowing different March algorithms to be
executed via assembly programming
 Disadvantages
 Some address space will be occupied by PPBIST
 Area overhead
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PPBIST Implementation
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PPBIST Data Registers
R e g is te r
F u n c tio n
R BG
Sto re b a c k g ro u n d d a ta
R AL
Sto re lo w e s t a d d re s s
R AH
Sto re h ig h e s t a d d re s s
R ME
Sto re c u rre n t M a rc h e le m e n t
R IR
In s tru c tio n re g is te r
R FLAG
Sta tu s re g is te r
R ED
E rro n e o u s re s p o n s e o f d e fe c tiv e m e m o ry c e ll
R EA
A d d re s s o f d e fe c tiv e m e m o ry c e ll
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PPBIST Test Procedure
CPU write data back ground
CPU write start/stop address
CPU write MARCH element instruction
CPU write START instruction to wrapper
BIST core
(W0)
BIST core
(R0W1)
BIST core
(R1W0)
BIST core
(R0W1)
compare error?
BIST core
(R1W0)
yes
no
complete?
yes
write complete flag
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BIST core
(R0)
write error flag
write faulty address
write faulty data
no
CPU take over
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PPBIST Example Using 6502
 6502 assembly program that performs March Ctest algorithm under the proposed BIST scheme
START: LDA
STA
LDA
STA
LDA
STA
LDA
STA
LDA
STA
M0:
LDA
STA
JSR
M1:
LDA
. . . . . .
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#$$55
0HFFE0
#$$00
0HFFE1
#$$00
0HFFE2
#$$FF
0HFFE3
#$$0F
0HFFE4
#$$00
0HFFE5
BIST
#$$01
END:
LDA
STA
JMP
#$$04
0HFFE6
FINISH
BIST:
LDA
STA
LDA
CMP
BEQ
CMP
BNE
RTS
#$$00
0HFFE6
0HFFE7
#$$01
ERROR
#$$FF
LOOP
ERROR: LDA
STA
JMP
#$$03
0HFFEA
FINISH
LOOP:
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PPBIST Example
 Addresses of the registers in the BIST experiment
R e g is te r
A d d re s s
R e g is te r
A d d re s s
R BG
FFE0
R IR
FFE6
R AL
FFE1 ~ FFE2
R FLAG
FFE7
R AH
FFE3 ~ FFE4
R ED
FFE8
R ME
FFE5
R EA
FFE9 ~ FFEA
 March elements and the corresponding RME
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M0
M1
M2
M3
M4
M5
0H
1H
2H
3H
4H
5H
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Experimental Results
 Total test time in terms of clock cycles
 The sum of all the March elements' test time plus
30 clock cycles
 10N clock cycles to perform March C-
 Test time of each March element :
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M0
M1
M2
M3
M4
M5
1N
2N
2N
2N
2N
1N
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Comparison of BIST Methodologies
B IS T sch e m e
Test tim e
H /W o ve rh e a d
R o u tin g o ve rh e a d
In te g ra te d B IS T co re
S h o rt
Low
H ig h
O n -ch ip p ro ce sso r
Ve ry lo n g
Z e ro
Z e ro
O u rs
S h o rt
Ve ry lo w
ze ro
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RAM BIST Compiler
 Use of RAM cores is increasing.
 SRAM, DRAM, flash RAM
 Multiple cores
 RAM BIST compiler is the trend.
 BRAINS (BIST for RAM in Seconds)
 Proposed BIST Architecture
 Memory Modeling
 Command Sequence Generation
 Configuration of the Proposed BIST
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BRAINS Outputs
 Synthesizable BIST design
 At-speed testing
 Programmable March algorithms
 Optional diagnosis support
 BISD
 Activation sequence
 Test bench
 Synthesis script
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BIST Synthesis Flow
GUI
Memory
Library
RTL
RAM/BIST
Description
Parser
Compile
Engine
Synthesis
BIST
Template
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Netlist
Cell
Library
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NTHU/GUC PMBIST Architecture
Programmable Memory BIST
MSO
MRD
MBO
Controller
Sequencer
TPG
Controls
Test Collar
MCK
MBS
MBC
MBR
MSI
Comparator
Address
D
Memory
Q
Normal
Access
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PMBIST with Scan
T est C o m m and /In fo rm a tio n S to rag e
M o d ule
S eria l
d ata in
S eria l
d ata ou t
M e m o ry
C o m m an d
C o m m an d
B IS T
co n tro l
sig n als
C o n tr oller
H an dsha kin g
E rro r
S eq u e n cer
A dd re ss
T est
P attern
G e n era to r
To
M e m o ry
E rro r
Source: Cheng, et al., DFT00
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Sequencer
Address Generator
Control
Module
Sequence Generator
go
Command Generator
error
info.
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address
Error Handling Module
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command
error
signature
116
State Diagram of Control Module
BIST
idle
BIST
idle
BIST
active
BIST
done
BIST
done
BIST
apply
For SRAM
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BIST
apply
For DRAM
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DRAM Page-Mode Operation
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Memory Specification Techniques
 Memory Specifications
I/O Specification
Command Specification
Task Specification
Delay Constraint Specification
AC Parameter Specification
 Support customized memories.
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I/O Specification
 Four parameters
 IO_type
 IO_width
 IO_latency
 IO_packet_length
 IO_type: input, output, or inout
 IO_width: port width (#bits), can be a constant
or specified by user
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I/O Specification
 IO_latency: port latency
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I/O Modeling
 IO_packet_length: #bits packed within a clock
cycle for the port
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Command Specification
 Specifies the memory’s instructions
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Task Specification
 Specifies a complete memory operation
 A task can be a single command or a sequence
of commands.
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Delay Constraint Specification
 Specifies the minimal time interval between any
two tasks
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AC Parameter Specification
 Specifies input and output delays
 Specified parameters will be inserted into the
synthesis script.
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Memory Specification Example
 For ZBT SRAM:
 Method A:
 @latency D = 1;
 @task write = {write};
 Method B:
 @latency D = 0;
 @task write = {pre_write, post_write};
 The BIST circuit from method A is faster than
the one from method B, but it has higher area
overhead
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Sequence Generation
 For each March element, the compiler generates
the command sequence according to the read
task, write task, and minimum delay between the
two tasks
 For example:
 task read = {A}
 task write = {B, C}
 minimum delay between read and write = 10ns
 clock period = 10 ns
 Then the (rw) element becomes {A, nop, B, C}
 One can also optimize the command sequence
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Fast Access Mode
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Diagnosis Support
 The BIST circuit scans out the error information
(element, address, signature, and polarity) during
the diagnosis mode.
 Assume address 20h stuck-at 64h:
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Multiple RAM Cores
 Controller and sequencer can be shared.
Test pattern
generator
Ram Core A
Test pattern
generator
Ram Core B
Test pattern
generator
Ram Core C
sequencer
controller
sequencer
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Experimental Results
 The Built-In Memory List
 DRAM
 EDO DRAM
 SDRAM
 DDR SDRAM
 SRAM
 Single-Port Synchronous SRAM
 Single-Port Asynchronous SRAM
 Two-Port Synchronous Register File
 Dual-Port Synchronous SRAM
 Micron ZBT SRAM
 BRAINS can support new memory architecture
easily
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Experimental Results
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Experimental Results
 Four single-port SRAM BIST circuits share the same
controller and sequencer.
 Size of the SRAM core: 8K x 16
Original
BIST area for single-port
SRAM: 1438 (gates)
Total area = 1438 * 4 =
5752 (gates)
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Shared
gate count: 3350
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Experimental Results
 8K x 16 single-port synchronous SRAM (0.25um)
 Area:
 Die size: 1780.74 x 755.07 um2
 BIST area: 80.1 x 583.48 um2
 Area overhead : 3.4%
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Experimental Results
 2K x 32 two-port register file (0.25um)
 Die size: 1130.74 x 936.34 um2
 BIST area: 77.88 x 620 um2
 Area overhead: 4.5%
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Why RAM Diagnostics?
 Memory testing is more and more important
 Memories are key components
 Represent about 30% of the semiconductor market
 Dominate the chip area/yield
 Memory testing is more and more difficult
 Growing density, capacity, and speed
 Emerging new architectures & technologies
 Growing need for embedded memories
 Why diagnostics?
 Yield improvement
 Repair and/or design/process debugging
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Fault Model Subtypes
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NTHU-FTC BIST Architecture
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Test Mode
 In Test Mode it runs a fixed algorithm for
production test and repair
 Only a few pins need to be controlled, and BGO
reports the result (Go/No-Go)
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Fault Analysis Mode
 In Fault Analysis Mode, we can apply a longer
March algorithm for diagnosis
 FSI captures the error information of the faulty
cells
EOP format:
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Error Catch and Analysis
 Locate the faulty cells
 Identify the fault types
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How to Identify Fault Type?
RAM Circuit/Layout
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Tester/BIST Output
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143
March Dictionary
March 11N
E0
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E1 E2
E3
E4 E5
E6 E7
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E8 E9
E10
144
March Signature and Error Map
March Signature (Syndrome)
Error Map
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MECA System
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Error Analyzer
Tester/BIST data log
Data log parser
Error maps
March
Dictionary
Fault analysis
Fault maps
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Fault Analysis
 Derive analysis equations from the fault dictionary
 Convert error maps to fault maps by the
equations
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Test Algorithm Generation
 Start from a base test: generated by TAGS or
user-specified
 Generation options reduced to read-insertions
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Diagnostic Resolution
 Diagnostic resolution
Diagnostic
resolution

# of distinguis
hable faults
# of detectable
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faults
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Experimental Results
 Proposed diagnosis framework has been
applied to commercial embedded SRAMs
 Results for a 16Kx8 embedded SRAM
(FS80A020) are shown
 Tester log from Credence SC212 is examined
 Address remapping (logical to physical) is
applied
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The Total Error Bitmap
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Fault Bitmaps
Idempotent Coupling Fault
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Stuck-at 0
153
Redundancy and Repair
 Problem: We keep shrinking the feature size and
increasing the chip density and size. How do we
maintain the yield?
 Solutions:
 Fabrication
 Material, process, equipment, etc.
 Design
 Device, circuit, etc.
 Redundancy and repair
 On-line
 EDAC (extended Hamming code; product code)
 Off-line
 Spare rows and/or columns
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From BIST to BISR
BIST
BISD
BIRA
BISR
•BIST: built-in self-test
•BIECA: built-in error catch & analysis
-BISD: built-in self diagnosis
-BIRA: built-in redundancy analysis
•BISR: built-in self-repair
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RAM Built-In Self-Repair (BISR)
Reconfiguration Mechanism
Analyzer
RAM
Spare Elements
Redundancy
BIST
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RAM Redundancy
 1-D: spare rows (or columns) only
 SRAM
 Algorithm: Must-Repair
 2-D: spare rows and columns
 Local and/or global spares
 NP-complete problem
 Conventional algorithm:
 Must-Repair phase
 Final-Repair phase
 Repair-Most (greedy) [Tarr et al., 1984]
 Fault-Driven (exhaustive, slow) [Day, 1985]
 Fault-Line Covering (b&b) [Huang et al., 1990]
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Redundancy Architectures
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An SRAM with BISR
[Kim et al., ITC 98]
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A DRAM Redundancy Example
4 local spare rows per block
2x4=8 global spare columns
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Definitions
 Faulty line: row or column with at least one faulty
cell.
 A faulty line is covered if all faulty cells in the line
are repaired by spare rows and/or columns.
 A faulty cell not sharing any row or column with
any other faulty cell is an orthogonal faulty cell.
 r: number of (available) spare rows
 c: number of (available) spare columns
 F: number of faulty cells in a block
 F’:number of orthogonal faulty cells in a block
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Example Block with Faulty Cells
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Repair-Most (RM)
• Run BIST and construct
bitmap.
• Construct row and column
error counters.
• Run Must-Repair algorithm.
• Run greedy Final-Repair
algorithm.
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Worst-Case Bitmap (After MustRepair)
•Max F=2rc.
•Max F’=r+c.
•Bitmap size: (rc+c)(cr+r).
r=2; c=4
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Local Repair-Most (LRM)
 RM is not good enough for embedded RAM.
 Large storage requirement: bitmap and counters
 Slow
 LRM improves the performance.





Repair-Most based
Improved heuristics
Early termination rules
Concurrent BIST and BIRA
No separate Must-Repair phase
 LRM reduces the storage required.
 Smaller local bitmap
 From (rc+c)x(cr+r) to mxn
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LRM Algorithm
 Activated by BIST whenever a faulty cell is
detected.
 Fault Collection (FC)
 Collects faulty-cell addresses.
 Constructs local bitmap.
 Counts row and column errors.
 Spare Allocation (SA)
 Allocate spare rows or columns when bitmap is full.
 Allocate spare rows or columns at end.
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LRM: FC and SA
(1,0), (1,6), (2,4), (3,4), (5,1), (5,2)
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LRM Example
(5,2)
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(5,4),(5,6),(5,7)
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(7,3)
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Local Optimization (LO)
 LMR has drawbacks:
 Selecting line with largest fault count may be slow.
 Multiple lines may need to be selected for repair.
 Area overhead is still high.
 Repair rate depends on bitmap size.
 LO has a better repair rate based on same
hardware overhead, i.e., a higher repair efficiency.
 Fault Collection (FC)
 Records faulty cells in bitmap until it is full.
 Spare Allocation (SA)
 Exhaustive search performed for repairing all faults.
 Bitmap cleared; process repeated until done.
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LO: Column*/Row Selection for SA
A 1 means that the corresponding
col is selected for repair, unless empty.
Col selection vector
Row selection vector
1. Col 5 selected for repair.
2. Row 5 is selected for repair.
* Assume column selection has a lower cost than row selection.
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LO Example
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Essential Spare Pivoting (ESP)
 Maintain high repair rate without using a bitmap.
 Small area overhead.
 Fault Collection (FC)
 Collect and store faulty-cell address using row-
pivot and column-pivot registers.
 If there is a match for row (col) pivot, the pivot is an
essential pivot.
 If there is no match, store the row/col addresses in
the pivot registers.
 If F > r+c, the RAM is unrepairable.
 Spare Allocation (SA)
 Use row and column pivots for spare allocation.
 Spare rows (cols) for essential row (col) pivots.
 SA for orthogonal faults.
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ESP Example
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Cell Fault Size Distribution
Mixed Poisson-exponential distribution.
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Repair Rate Comparison
•1,552 RAM blocks.
•1,024x64 bits per block.
•r from 6 to 10.
•c from 2 to 6.
•LRM bitmap: rxc.
•LO bitmap: 8x4.
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Normalized Repair Rate
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Repair Rate (r=10)
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Normalized Repair Rate (r=6)
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Area Overhead
Overhead is about 5-12% for 16Mb DRAM, r=8, and c=4.
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Computation Time (Simulated)
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180