- 164 Views
- Uploaded on

Download Presentation
## PowerPoint Slideshow about 'Spectral Methods for Testing of Digital Circuits' - parmida

**An Image/Link below is provided (as is) to download presentation**

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript

### Spectral Methods for Testing of Digital Circuits

OutlineOutline

Doctoral Defense

Nitin Yogi

Dept. of ECE, Auburn University

Dissertation Committee:

Chair:Prof. Vishwani D. AgrawalProf. Victor P. Nelson Prof. Adit D. Singh Prof. Charles E. StroudOutside reader:Prof. Paul M. Swamidass

June 12, 2009

Outline

- Test challenges & primary goals of this work
- Spectral analysis fundamentals
- Contributions of this thesis
- Spectral RTL Test generation
- Minimization of N-model tests
- Spectral TPG for BIST
- Conclusion

Nitin Yogi - Doctoral Defense

Manufacturing Test Challenges

NIST

Advances in Microelectronic Fabrication

Effects

- Decreasing feature sizes
- Increasing design complexities

Microchip Corp.

- Manufacturing Test Issues
- Increase in test generation complexity
- More specific test patterns required
- Higher number and more complex defects
- Increase in test data volume
- Increase in test time

Nitin Yogi - Doctoral Defense

Primary Goals of this Work

1. Develop an efficient test generation algorithm

- High fault coverage
- Low test generation complexity
- Low number of test vectors

Issues addressed

Increase in

test generation

complexity

Increase in

test data volume

Nitin Yogi - Doctoral Defense

Primary Goals of this Work

2. Develop a minimization approach for N-Model tests (multiple fault models)

- High test minimization capability
- Ability to handle diverse and custom fault models

Issues addressed

Increase in

test data volume

Higher number & more complex

defects

Nitin Yogi - Doctoral Defense

Primary Goals of this Work

3. Develop a Built-In Self Test (BIST) synthesis scheme

- High fault coverage
- Low area overhead
- Low test application time

Issues addressed

More specific

test patterns

required

Increase in

test time

Nitin Yogi - Doctoral Defense

Outline

- Test challenges & primary goals of this work
- Spectral analysis fundamentals
- Contributions of this thesis
- Spectral RTL Test generation
- Minimization of N-model tests
- Spectral TPG for BIST
- Conclusion

Nitin Yogi - Doctoral Defense

Spectral Analysis Fundamentals

- Basic idea: Interpret information in frequency domain
- Binary bit-streams converted to spectral coefficients using transforms like Hadamard, Haar, etc.
- Motivation: Good quality test vectors exhibit certain discernible spectral characteristics
- Premise supported by findings of earlier works

Nitin Yogi - Doctoral Defense

Walsh Functions and Hadamard Matrix

- Walsh functions: a complete orthogonal set of basis functions that can represent any arbitrary bit-stream.
- Walsh functions form the rows of a Hadamard matrix.

w0

w1

w2

w3

Walsh functions (order 3)

H(3)=

w4

w5

w6

w7

Example of Hadamard matrix of order 3

time

Nitin Yogi - Doctoral Defense

Test Vectors and Bit-streams

Circuit Under Test (CUT)

Outputs

Input J

Input 3

Input 5

Input 1

Input 4

Input 2

A binary bit-stream

Vector 1 →

Vector 2 →

Vector 3 →

Vector 4 →

Vector 5 →

Time

Vector K→

Nitin Yogi - Doctoral Defense

Spectral Analysis of a Bit-stream

Input 1

Input 2

.

.

.

Test vector set

Original binary

bit-stream

Modified bit-stream

Vector 1

Vector 2

Vector 3

.

.

.

0 to -1

Bit-stream of

Input 2

Nitin Yogi - Doctoral Defense

Spectral Analysis of a Bit-stream (cont.)

Bit stream to analyze

Bit stream

Spectral coeffs.

Hadamard Matrix H(3)

=

Correlating with Walsh functions by multiplying with Hadamard matrix.

Prominent spectral component

Nitin Yogi - Doctoral Defense

Power Spectrum: “Interrupt” Signal*

Examples of essential components

Examples of noise components

Normalized Power

Theoretical random noiselevel (1/128)

Spectral Coefficients

* A primary input signal for PARWAN processor

Nitin Yogi - Doctoral Defense

Power Spectrum: “DataIn[5]” Signal

Examples of essential components

Examples of noise components

Normalized Power

Theoretical random noiselevel (1/128)

Spectral Coefficients

* A primary input signal for PARWAN processor

Nitin Yogi - Doctoral Defense

Power Spectrum: Random Signal

Normalized Power

Theoretical random noiselevel (1/128)

Spectral Coefficients

Nitin Yogi - Doctoral Defense

Reverse Hadamard Transform

Original binary

bit-stream

Spectral coeffs.

Hadamard Matrix H(3)

Bit-stream

÷ 8 =

-1 to 0

Nitin Yogi - Doctoral Defense

Spectral Vector Generation

Perturbed spectral coeffs.

Hadamard Matrix H(3)

New binarybit-stream

Bit-stream

sign

-1 to 0

÷ 8

=

Bits changed

Nitin Yogi - Doctoral Defense

Effect of Noise

No. of faults detected by original vectors

- Noise inserted in ATPG vectors using increasing spectral threshold (ST) values (i.e. increasing noise)

More faults detected than original vectors

Nitin Yogi - Doctoral Defense

Significance of spectral properties

- Two types of test vectors generated
- Spectrally inserted noise by eliminating spectral coefficients below a threshold
- Randomly inserted noise by flipping proportion of bits randomly

Nitin Yogi - Doctoral Defense

Significance of spectral properties

Nitin Yogi - Doctoral Defense

Significance of spectral properties

Tests generated with ST=1 & ST=13 (3 sets for each)

- T-test results
- h = 1(hypothesis that the two data sets have equal means is rejected)
- p = 8.85 x 10-18(probability with which both data sets will have equal values is low)

Nitin Yogi - Doctoral Defense

Significance of spectral properties

Tests generated with ST=1, ST=13 & ST=25 (3 sets for each)

- T-test results
- h = 1(hypothesis that the two data sets have equal means is rejected)
- p = 1.54 x 10-78(probability with which both data sets will have equal values is low)

Nitin Yogi - Doctoral Defense

Outline

- Test challenges & primary goals of this work
- Spectral analysis fundamentals
- Contributions of this thesis
- Spectral RTL Test generation
- Minimization of N-model tests
- Spectral TPG for BIST
- Conclusion

Nitin Yogi - Doctoral Defense

Spectral RTL Test Generation

- We propose a novel test generation algorithm using:
- Register Transfer Level (RTL) information
- Spectral techniques
- Primary goals:
- Low test generation complexity
- High fault coverage
- Low test vector length

Nitin Yogi - Doctoral Defense

Faults Modeled for an RTL Module

CombinationalLogic

Inputs

Outputs

RTL stuck-at fault sites

FF

FF

A circuit is an interconnect of several RTL modules.

Nitin Yogi - Doctoral Defense

Proposed Test Generation Algorithm

RTL

circuit

Spectral properties

Step 2

Step 1

Generate test vectors for RTL faults

Generate new test vectors by spectral coeff. perturbation

Determine

prominent spectral components by spectral analysis

010010100100101110111000100110111101011101010011111000010111000100010101101011011000001011010101

Fault simulate test vectors and compact

Test vector set

Nitin Yogi - Doctoral Defense

Results for ITC’99 and ISCAS’89 Circuits

* Reset input added.

N. Yogi and V. D. Agrawal, “Spectral RTL Test Generation for Gate-Level Stuck-at Faults,” in Proc. 15th IEEE Asian Test Symp., 2006, pp. 83–88.

Nitin Yogi - Doctoral Defense

Results for PARWAN Processor

*Sun Ultra 5, 256MB RAM

N. Yogi and V. D. Agrawal, “Spectral RTL Test Generation for Microprocessors,” in Proc. 20th International Conf. VLSI Design, Jan. 2007, pp. 473–478.

Nitin Yogi - Doctoral Defense

Test Coverage Distribution

Nitin Yogi - Doctoral Defense

Test Coverage Distribution

Nitin Yogi - Doctoral Defense

- Test challenges & primary goals of this work
- Spectral analysis fundamentals
- Contributions of this thesis
- Spectral RTL Test generation
- Minimization of N-model tests
- Spectral TPG for BIST
- Conclusion

Nitin Yogi - Doctoral Defense

Multiple Fault Models

- N-Model tests: For a set of N given fault models, N ≥ 1, the N-model tests target detection of all faults in the superset of faults for all N fault models.
- Importance
- Each fault model targets specific defects
- Sematech study (Nigh et. al. VTS’97) concluded …To detect most defects, tests for all fault models need to included.
- Minimization problem
- Obtain minimized test set for considered fault models
- Take advantage of vectors detecting faults in multiple fault models
- Fault simulator/ATPG handles only one fault model at a time
- Need for a new minimization approach

Nitin Yogi - Doctoral Defense

Multiple Fault Model Test Minimization

- Obtain fault dictionary by fault simulations
- Determine faults detected by each vector
- ‘F’ faults : for all considered fault models
- ‘N’ vectors : generated to cover all faults ‘F’
- Test minimization by Integer Linear Program (ILP) considering the test application cost
- ILP formulation
- Set of integer variables
- Set of constraints
- Objective function
- Solving the ILP assigns values to variables such that:
- Constraints are met
- Objective function is optimum

Nitin Yogi - Doctoral Defense

Combined ILP

- Define two [0, 1] integer variables:
- { tj , ij } – for each vector ; j = 1 to N
- tj = 0 : drop vector j
- tj = 1 : select vector j
- ij = 0 : no IDDQ measurement for vector j
- ij = 1 : measure IDDQ for vector j

Nitin Yogi - Doctoral Defense

Combined ILP (cont.)

- Constraints {ck} for kth fault, k = 1 to F
- For kth fault detected by vectors u, v and wck : tu + tv + tw≥ 1

iu + iv + iw≥ 1tu ≥ iutv ≥ ivtw ≥ iw

Only if kthfault is an IDDQ fault

Nitin Yogi - Doctoral Defense

Combined ILP (cont.)

- Objective function
- Minimize {∑ tj + W × ∑ ij}
- N : total number of vectors
- tj : variables to select vectors
- ij : variables to select IDDQ measurements
- W : weighting factor, W ≥ 0
- How strongly to minimize IDDQ vectors(May depend on the relative cost of current measurement)

N

N

j = 1

j = 1

Nitin Yogi - Doctoral Defense

Hybrid LP – ILP

- Approximate solution to ILP
- Algorithm:
- All variables redefined as real [0,1] variables (LP model)
- Loop :
- Solve LP
- Round variables {tj} , {ij} as follows:
- Round to 0 if ( 0.0 <variables≤ 0.1)
- Round to 1 if ( 0.9 ≤variables< 1.0)
- Exit loop if no variables are rounded
- Reconvert variables to [0,1] integers & solve ILP

Nitin Yogi - Doctoral Defense

Conventional Test Vector Minimization

Nitin Yogi - Doctoral Defense

Results: N-Model Test Minimization

Conventional test minimization results:

N-Model test minimization results:

* CPU time limit of 5000 s exceeded

$ SUN Sparc Ultra 10, four CPU machine with 4.0 GB RAM shared among 4 CPUs

Order of magnitude reduction in CPU time

N. Yogi and V. D. Agrawal, “N-Model Tests for VLSI Circuits,” in Proc. 40th IEEE South-eastern Symp. System Theory, Mar. 2008, pp. 242–246.

Nitin Yogi - Doctoral Defense

- Test challenges & primary goals of this work
- Spectral analysis fundamentals
- Contributions of this thesis
- Spectral RTL Test generation
- Minimization of N-model tests
- Spectral TPG for BIST
- Conclusion

Nitin Yogi - Doctoral Defense

Spectral TPG for BIST

- We propose a novel design methodology for a Test Pattern Generator (TPG) for Built-In Self Test (BIST) environments
- Primary goals:
- Given pre-generated test vectors, replicate their effects in hardware
- Support at-speed testing for non-scan circuits
- Low area overhead
- Low test application times

Nitin Yogi - Doctoral Defense

Proposed Design Methodology

Pre-generated test vectors

Spectral properties

Step 2

Step 1

Preprocess test vectors

(for combinational circuits)

BIST

implementation

Determine prominent spectral components by spectral analysis

BIST TPG gate-level netlist

Nitin Yogi - Doctoral Defense

Pre-processing of Test Vectors

- Pre-processing of test vectors convenient for combinational circuits
- Order of application of test vectors is immaterial
- Method employed
- Reshuffling of test vectors to enhance the spectral properties

Nitin Yogi - Doctoral Defense

Reshuffling Algorithm

Input Data and Parameters:

NI: No of inputs

NV: No. of vectors

V(1:NV,1:NI): Test vector Set of dimensions NV x NI

hd: Dimension of Hadamard matrix

H: Hadamard transform matrix of dimension 2hdx 2hd

Procedure:

Vector set V appended with redundant vectors to make weighting of bit-streams of all inputs = 0.5

for i=1 to NI

Perform spectral analysis on bit-stream of input i: S = V(:,i) x H;

Pick the prominent spectral component Sp(i) from S

Rearrange vector set V such that maximum bits in the bit- streams of inputs 1 to i match with the picked prominent spectral components Sp(1 to i) respectively.

end

Nitin Yogi - Doctoral Defense

System clock

To CUT

Clock divider and holding circuit(for sequential CUTs)

BIST

clock

Hadamard wave generator

Weighted pseudo-random pattern generator

2

Spectral component synthesizer

Input 1

System clock

3

BIST clock

1

To CUT

Input 2

Randomizer

1

Hadamard Components

Input 3

1

Weighted pseudo-random bit-streams

Nitin Yogi - Doctoral Defense

Reseeding

- Reseeding: Setting memory elements (flip-flops) of TPG to values such that fault detection capability of generated test vectors improves.
- Reseeding effectively used in earlier works for LFSRs, CARs, etc.

Nitin Yogi - Doctoral Defense

Reseeding of Spectral TPG

Spectral BIST / Decompressor

BIST / Decompressor Logic

Flip-flops

Data from external tester

To CUT

Parallel interface

Serial scan interface

Nitin Yogi - Doctoral Defense

Outline

- Test challenges & primary goals of this work
- Spectral analysis fundamentals
- Contributions of this thesis
- Spectral RTL Test generation
- Minimization of N-model tests
- Spectral TPG for BIST
- Results without reseeding
- Results for combinational circuits
- Results for sequential circuits
- Results with reseeding
- Results for combinational circuits
- Conclusion

Nitin Yogi - Doctoral Defense

Spectral BIST Results and Area Overhead

Test coverage comparison (64000 vectors)

Area overhead comparison

N. Yogi and V. D. Agrawal, “BIST/Test-Decompressor Design using Combinational Test Spectrum,” in Proc. 13th VLSI Design and Test Symp., Aug. 2009.

Nitin Yogi - Doctoral Defense

Test Coverage vs Number of Vectors

Nitin Yogi - Doctoral Defense

Test Coverage vs Number of Vectors

Nitin Yogi - Doctoral Defense

Outline

- Test challenges & primary goals of this work
- Spectral analysis fundamentals
- Contributions of this thesis
- Spectral RTL Test generation
- Minimization of N-model tests
- Spectral TPG for BIST
- Results without reseeding
- Results for combinational circuits
- Results for sequential circuits
- Results with reseeding
- Results for combinational circuits
- Conclusion

Nitin Yogi - Doctoral Defense

Hadamard BIST Results

Equal or more faults detected than ATPG in5 / 8 circuits

Equal or more faults detected than ATPG in5 / 8 circuits

1. S. K. Devanathan and M. L. Bushnell, “Test Pattern Generation Using Modulation by Haar Wavelets and Correlation for Sequential BIST,” in Proc. 20th International Conf. VLSI Design, 2007, pp. 485–491.

N. Yogi and V. D. Agrawal (2008), “Sequential Circuit BIST Synthesis Using Spectrum and Noise from ATPG Patterns,” Proc. 27th IEEE Asian Test Symp., pp. 69-74.

Nitin Yogi - Doctoral Defense

Hadamard BIST Results

Maximum faults detected in 6 / 8 circuits

1. S. K. Devanathan and M. L. Bushnell, “Test Pattern Generation Using Modulation by Haar Wavelets and Correlation for Sequential BIST,” in Proc. 20th International Conf. VLSI Design, 2007, pp. 485–491.

N. Yogi and V. D. Agrawal (2008), “Sequential Circuit BIST Synthesis Using Spectrum and Noise from ATPG Patterns,” Proc. 27th IEEE Asian Test Symp., pp. 69-74.

Nitin Yogi - Doctoral Defense

Longer BIST Sequences

ATPG fault coverage achieved in 6 / 8 circuits

N. Yogi and V. D. Agrawal (2008), “Sequential Circuit BIST Synthesis Using Spectrum and Noise from ATPG Patterns,” Proc. 27th IEEE Asian Test Symp., pp. 69-74.

Nitin Yogi - Doctoral Defense

Area OverheadN. Yogi and V. D. Agrawal (2008), “Sequential Circuit BIST Synthesis Using Spectrum and Noise from ATPG Patterns,” Proc. 27th IEEE Asian Test Symp., pp. 69-74.

Approximately similar area overheads

1. S. K. Devanathan and M. L. Bushnell, “Test Pattern Generation Using Modulation by Haar Wavelets and Correlation for Sequential BIST,” in Proc. 20th International Conf. VLSI Design, 2007, pp. 485–491.

Nitin Yogi - Doctoral Defense

Outline

- Test challenges & primary goals of this work
- Spectral analysis fundamentals
- Contributions of this thesis
- Spectral RTL Test generation
- Minimization of N-model tests
- Spectral TPG for BIST
- Results without reseeding
- Results for combinational circuits
- Results for sequential circuits
- Results with reseeding
- Results for combinational circuits
- Conclusion

Nitin Yogi - Doctoral Defense

Spectral TPG Results with Reseeding

Comparison of test data volume and test time for c7552

† assuming tester clock period Ttester=10ns and on-chip system clock period Tclk=1ns

N. Yogi and V. D. Agrawal, “BIST/Test-Decompressor Design using Combinational Test Spectrum,” in Proc. 13th VLSI Design and Test Symp., Aug. 2009.

Nitin Yogi - Doctoral Defense

Spectral TPG Results with Reseeding

Comparison of test data volume and test time for s15850 (combinational)

† assuming tester clock period Ttester=10ns and on-chip system clock period Tclk=1ns

N. Yogi and V. D. Agrawal, “BIST/Test-Decompressor Design using Combinational Test Spectrum,” in Proc. 13th VLSI Design and Test Symp., Aug. 2009.

Nitin Yogi - Doctoral Defense

Conclusion

- Proposed methods using spectral techniques for
- Test generation using RTL information
- Designing a TPG for BIST
- Proposed Spectral RTL test generation
- Generated test vectors exhibited:
- High fault coverage for most circuits
- Low test generation complexity
- Moderate number of test vectors
- N-model test defined
- Proposed an ILP-based minimization approach with high compression ratio
- Proposed design methodology for TPG in BIST
- Generated test vectors in hardware exhibited:
- Equal or higher fault coverage that ATPG vectors in most circuits
- Higher fault coverage then existing TPGs in most circuits
- Moderate area overhead compared to existing TPGs
- High test compression capabilities

Nitin Yogi - Doctoral Defense

List of Publications

- N. Yogi and V. D. Agrawal, “Sequential Circuit BIST Synthesis using Spectrum and Noise from ATPG Patterns,” 17th Asian Test Symposium, Nov. 2008
- N. Yogi and V. D. Agrawal, “N-Model tests for VLSI circuits,” 40th Southeastern Symposium on System Theory, March 2008
- N. Yogi and V. D. Agrawal, “Transition Delay Fault Testing of Microprocessors by Spectral Method,” in Proc. 39th IEEE Southeastern Symp. System Theory, Mar. 2007, pp. 283–287.
- N. Yogi and V. D. Agrawal, “Spectral RTL Test Generation for Microprocessors,” 20th Int’l Conf. on VLSI Design, Jan. 2007
- N. Yogi and V. D. Agrawal, “Spectral RTL Test Generation for Gate-Level Stuck-at Faults,” 15th Asian Test Symp., Nov. 2006
- N. Yogi and V. D. Agrawal, “Spectral Characterization of Functional Vectors for Gate-Level Fault Coverage Tests," in Proc. 9th VLSI Design and Test Symp., Aug. 2006

Nitin Yogi - Doctoral Defense

Download Presentation

Connecting to Server..