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A Novel Technique for Input Vector Compression in System-on-Chip Testing
Student: Chien Nan Lin
Satyendra Biswas, Sunil Das, and Altaf Hossain,” Information Technology, 2008. ICIT '08. International Conference on ”, Bhubaneswa
r, pp. 53 - 58, 17-20 Dec. 2008.
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Outline
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
Introduction Frame of Compression Technique Theoretical Background Proposed Technique Experimental Results
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Frame of Compression Technique
Original Test Vectors
Block Matching
LzwCoding
CompressedTest Vectors
Low Frequency Data Sets
High Frequency Data Sets
Burrows-Wheeler Transformation
+
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Output
Outline
Introduction Frame of Compression Technique Theoretical Background Proposed Technique Experimental Results
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Theoretical Background
Original Test Vectors
Block Matching
LzwCoding
CompressedTest Vectors
Low Frequency Data Sets
High Frequency Data Sets
Burrows-Wheeler Transformation
+
Frame
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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 AllRotations
Sort the Rows
Output
^BANANA@
^BANANA@ @^BANANA A@^BANAN NA@^BANA ANA@^BAN NANA@^BA ANANA@^B BANANA@^
ANANA@^B ANA@^BAN A@^BANAN BANANA@^ NANA@^BA NA@^BANA ^ BANANA@ @ ^ BANANA
BNN^AA@A
(the red @ character indicates the 'EOF' pointer)
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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
A is「 Run」
3 is「 Length」
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Theoretical BackgroundBurrows-Wheeler Transform
Reversing the example above is done like this:
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Theoretical Background
The initial dictionary
# = 00000 = 0
A = 00001 = 1
B = 00010
C = 00011
.
.
.
Z = 11010 = 26
Example:
TOBEORNOTTOBEORTOBEORNOT#
Lzw Coding
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Output
Outline
Introduction Frame of Compression Technique Theoretical Background Proposed Technique Experimental Results
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Frame
Original Test Vectors
Block Matching
LzwCoding
CompressedTest Vectors
Low Frequency Data Sets
High Frequency Data Sets
Burrows-Wheeler Transformation
+
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All the test vectors are divided into several block of
equal size.
Proposed Technique
BlOCK
Number 1 2 3 4 5 6 7
Test Vector- 0100 1100 0001 1000 0110 1000 0111
Test Vector- 0100 1011 0110 0111
Test Vector- 0100 1001 0110 0111
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1
0100
0100
0100
T
2
0110
0110
0110
T
3
0111
0111
0111
T
Proposed Technique
TK,where K=1,2,3,…,n, as a matrix of M N, M > 2, N= block size of data.
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Output
Outline
Introduction Frame of Compression Technique Theoretical Background Proposed Technique Experimental Results