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VLSI Circuit Test Vector
Compression Technique
Satyendra Biswas, Sunil Das, and Altaf Hossain,
Instrumentation and Measurement Technology Conference,
Warsaw, Poland, May 2007, pp. 1-6.
Student: Chien Nan Lin
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Outline
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Introduction
Frame of Compression Technique
Theoretical Background
Proposed Technique
Experimental Results
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Introduction
In this paper, a new test vector compression method for
VLSI circuit testing is presented.
To reduce the on-chip:


Storage area
Testing time
Simulation experiments on ISCAS 85 benchmark.
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Outline
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


Introduction
Frame of Compression Technique
Theoretical Background
Proposed Technique
Experimental Results
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Frame of Compression Technique
Original Test
Vectors
Block
Matching
Low Frequency
Data Sets
High Frequency
Data Sets
Golomb
Coding
Compressed
Test Vectors
+
Burrows-Wheeler
Transformation
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Outline





Introduction
Frame of Compression Technique
Theoretical Background
Proposed Technique
Experimental Results
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Theoretical Background
Frame
Original Test
Vectors
Block
Matching
Low Frequency
Data Sets
High Frequency
Data Sets
Golomb
Coding
Compressed
Test Vectors
+
Burrows-Wheeler
Transformation
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Theoretical Background
 Burrows-Wheeler Transform
The Burrows-Wheeler transformation algorithm is
described in the following:
Step 1:Create a list of possible rotation of string.
Step 2:Let each rotation be one row in a large, sequare table.
Step 3:Sort the rows of the alphabetically, treating each row
as a string.
Step 4:Return the last column of the table.
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Theoretical Background
 Burrows-Wheeler Transform
For example:
Input
^BANANA@
All
Rotations
^BANANA@
@^BANANA
A@^BANAN
NA@^BANA
ANA@^BAN
NANA@^BA
ANANA@^B
BANANA@^
Sort the
Rows
ANANA@^B
ANA@^BAN
A@^BANAN
BANANA@^
NANA@^BA
NA@^BANA
^ BANANA@
@ ^ BANANA
Output
BNN^AA@A
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(the red @ character indicates the 'EOF' pointer)
Theoretical Background
 Burrows-Wheeler Transform
Compressing test data using run-length coding and
Burrows-Wheeler transformation.
For example:
BNN^AA@A ─> 1B2N1^2A1@1A
AAABBBBBBBBBAA ─> 3A9B2A
3 is「Length」
A is「Run」
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Theoretical Background
 Golomb Coding
The Golomb coding algorithm is described as follows:
step 1:Fix the parameter M to integer value.
step 2:For the number to be encoded,say N,find
out (a) Quotient=int [N/M]
(b) Remainder=N%M
step 3:Generate codeword
(a) The code format: <Quotient code>
<Remainder code>
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Outline





Introduction
Frame of Compression Technique
Theoretical Background
Proposed Technique
Experimental Results
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Frame
Original Test
Vectors
Block
Matching
Low Frequency
Data Sets
High Frequency
Data Sets
Golomb
Coding
Compressed
Test Vectors
+
Burrows-Wheeler
Transformation
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Proposed Technique
BlOCK
Number
1
2
3
4
5
6
1000
7
Test Vector-
0100 1100 0001
1000
0110
Test Vector-
0110
1011
0011
0101
Test Vector-
0100 1001
0010
0111
0111
All the test vectors are divided into several block of
equal size.
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Proposed Technique
BlOCK
Number
1
2
3
4
5
6
1000
7
Test Vector-
0100 1100 0001
1000
0110
Test Vector-
0110
1011
0011
0101
Test Vector-
0100 1001
0010
0111
0111
High frequency data sets generated from the test vector, as follows:
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Proposed Technique
0100 
T1  0110 
0100 
0110 
T2  0011 
0010 
0111
T3  0101
0111
TK,where K=1,2,3,…,n, as a matrix of M  N, M > 2, N= block
size of data.
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Outline
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
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
Introduction
Frame of Compression Technique
Theoretical Background
Proposed Technique
Experimental Results
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Experimental Results
(Orignal _ Bits)  (Compressed _ Bits)
%Compression 
 100
Original _ Bits
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Experimental Results
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Thanks
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