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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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Introduction

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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

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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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Reversing the example above is done like this:

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Theoretical Background Lzw Coding

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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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Theoretical Background Encoding

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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

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Experimental Results

( _ ) ( _ )% 100

_

Orignal Bits Compressed BitsCompression

Original Bits

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Experimental Results

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Thanks