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A Novel Technique for Input Vector Compression in System-on-Chip Testing Satyendra Biswas, Sunil Das, and Altaf Hossain,” Information Technology, 2008. ICIT '08. International Conference on ”, Bhubaneswar, pp. 53 - 58, 17-20 Dec. 2008. Student: Chien Nan Lin 1/20 Outline Introduction Frame of Compression Technique Theoretical Background Proposed Technique Experimental Results 2/24 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. 3/24 Introduction 4/24 Outline Introduction Frame of Compression Technique Theoretical Background Proposed Technique Experimental Results 5/24 Frame of Compression Technique Original Test Vectors Block Matching Low Frequency Data Sets High Frequency Data Sets Lzw Coding Compressed Test Vectors + Burrows-Wheeler Transformation 6/24 Outline Introduction Frame of Compression Technique Theoretical Background Proposed Technique Experimental Results 7/24 Theoretical Background Frame Original Test Vectors Block Matching Low Frequency Data Sets High Frequency Data Sets Lzw Coding Compressed Test Vectors + Burrows-Wheeler Transformation 8/24 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. 9/24 Theoretical Background Burrows Wheeler Transform 10/24 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 11/24 (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」 12/24 Theoretical Background Burrows-Wheeler Transform Reversing the example above is done like this: 13/24 Reversing the example above is done like this: 14/24 Theoretical Background Lzw Coding 15/24 Theoretical Background Lzw Coding Example: TOBEORNOTTOBEORTO BEORNOT# The initial dictionary # = 00000 = 0 A = 00001 = 1 B = 00010 C = 00011 . . . Z = 11010 = 26 16/24 Theoretical Background Encoding 17/24 Outline Introduction Frame of Compression Technique Theoretical Background Proposed Technique Experimental Results 18/24 Frame Original Test Vectors Block Matching Low Frequency Data Sets High Frequency Data Sets Lzw Coding Compressed Test Vectors + Burrows-Wheeler Transformation 19/24 Proposed Technique BlOCK Number 1 2 3 4 5 6 1000 7 Test Vector- 0100 1100 0001 1000 0110 Test Vector- 0100 1011 0110 0111 Test Vector- 0100 1001 0110 0111 0111 All the test vectors are divided into several block of equal size. 20/24 Proposed Technique 0100 T1 0100 0100 0110 T2 0110 0110 0111 T3 0111 0111 TK,where K=1,2,3,…,n, as a matrix of M N, M > 2, N= block size of data. 21/24 Outline Introduction Frame of Compression Technique Theoretical Background Proposed Technique Experimental Results 22/24 Experimental Results (Orignal _ Bits) (Compressed _ Bits) %Compression 100 Original _ Bits 23/24 Experimental Results 24/24 Thanks 25/24