ece469 proj2_lakshmi yasaswi kamireddy
TRANSCRIPT
Computer System Design Project-2
Lakshmi Yasaswi Kamireddy
(651771619)
0
5
10
15
20
25
30
35
Minset-Size 50
0
5
10
15
20
25
RV1
02468
10121416
RV2
01020304050
Minset-Size 49
05
1015202530
RV1
05
10152025
RV2
C17,Minset size -7
c432
c499
0
5
10
15
20
25
Minset-Size-52
0
5
10
15
20
25
RV1
0
5
10
15
20
RV2
28
.57
14
28
57
28
.57
14
28
57
42
.85
71
42
86
57
.14
28
5
42
.85
71
4
21
.42
85
71
43
35
.71
42
85
71
42
.85
71
42
86
0 50 100
c880
X-axis –Output density of 1’s ;Y-axis-Input Instance (%);Minset is the Minimum set from Atalanta;RV1-Randam Test Vector set with size same as Minset;RV2- Random Test Vector set with size double of Minset
Part(a)
0
10
20
309
.37
5
15
.62
5
21
.87
5
25
31
.25
37
.5
40
.62
5
43
.75
46
.87
5
50
53
.12
5
56
.25
59
.37
5
62
.5
65
.62
5
68
.75
71
.87
5
Minset-Size-85
0
5
10
15
20
25
RV1
0
5
10
15
20
RV2
0
5
10
15
20
28 32 36 40 44 48 52 56 60 64 68 76
Minset-Size-119
0
5
10
15
20
24 28 32 36 40 44 48 52 56 60 64 68 72 76
RV1
0
5
10
15
20
16 20 28 32 36 40 44 48 52 56 60 64 68 72 76 84
RV2
c1355
c1908
02468
10
Minset-Size-106
0
5
10
15
RV1
02468
1012
RV2c2670
0
5
10
15
20
25
Minset-Size-152
05
10152025
RV2
0
5
10
15
20
25
RV1c3540
0
2
4
6
8
Minset-Size-109
02468
10
RV1
02468
RV2
0
5
10
15
20
Minset-Size-34
0
5
10
15
20
RV1
0
5
10
15
20
25
RV2
0
1
2
3
4
5
6
7
8
9
37
.96
…
40
.74
…
44
.44
…
46
.29
…
48
.14
…
50
51
.85
…
53
.70
…
55
.55
…
57
.40
…
59
.25
…
61
.11
…
62
.96
…
65
.74
…
67
.59
…
69
.44
…
72
.22
…
74
.07
…
78
.70
…
81
.48
…
Minset-Size-213
0
1
2
3
4
5
6
7
8
9
41
.66
66
66
67
44
.44
44
44
44
46
.29
62
96
3
48
.14
81
48
15
50
51
.85
18
51
85
53
.70
37
03
7
55
.55
55
55
56
57
.40
74
07
41
59
.25
92
59
26
61
.11
11
11
11
62
.96
29
62
96
64
.81
48
14
81
66
.66
66
66
67
69
.44
44
44
44
RV1
0
1
2
3
4
5
6
7
8
9
39
.81
48
14
81
41
.66
66
66
67
43
.51
85
18
52
45
.37
03
70
37
47
.22
22
22
22
49
.07
40
74
07
50
.92
59
25
93
52
.77
77
77
78
54
.62
96
29
63
56
.48
14
81
48
58
.33
33
33
33
60
.18
51
85
19
62
.03
70
37
04
63
.88
88
88
89
65
.74
07
40
74
69
.44
44
44
44
72
.22
22
22
22
RV2
c5315
c6288
c7552
57
.14
28
57
14
57
.14
28
57
14
85
.71
42
85
71
57
.14
28
57
14
57
.14
28
57
14
64
.28
57
14
29
1 2
minset1 RV1 RV2
77
.55
10
20
41
59
.18
36
73
47
57
.14
28
57
14
85
.71
42
85
71
53
.06
12
24
49
48
.97
95
91
84
42
.85
71
42
86
10
0
73
.46
93
87
76
59
.18
36
73
47
61
.22
44
89
8
48
.97
95
91
84
32
.65
30
61
22
46
.93
87
75
51
89
.79
59
18
37
85
.71
42
85
71
64
.28
57
14
29
55
.10
20
40
82
50
32
.65
30
61
22
42
.85
71
42
86
1 2 3 4 5 6 7
minset1 RV11 RV21
46
52
58
52
40
52
50
42 4
4
58
42
48
42
50
42
52 5
4
38
56
44
42
36 3
8
46
44
50
44
50 5
2
42
42
48
54
60
40
50
62
60
50
58
46
50
42
64
54
48
48 5
0
48
52
56
42
52
42
52
38
56
48
56
38
54
60
2
525
4
53
49
39
59
47
53
44
50
48 49 5
1 52
50
45
56
40
57
56
60
51
45
51
55
44 4
7
43
53
53 5
6
0
43
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4 2 5 2 6 2 7 2 8 2 9 3 0 3 1 3 2
minset1 RV11 RV12
c17 c432
c499
X-axis –Outputs;Y-axis- density of 1’s (%);Minset is the Minimum set from Atalanta(Size same as mentioned in part a);RV1-Randam Test Vector set with size same as Minset;RV2- Random Test Vector set with size double of Minset
Part-b
52
.94
11
76
47
43
.52
94
11
76
48
.23
52
94
12
42
.35
29
41
18
43
.52
94
11
76
49
.41
17
64
71
57
.64
70
58
82
50
.58
82
35
29
43
.52
94
11
76
56
.47
05
88
24
47
.05
88
23
53
54
.11
76
47
06
37
.64
70
58
82
50
.58
82
35
29
49
.41
17
64
71
56
.47
05
88
24
43
.52
94
11
76
38
.82
35
29
41
43
.52
94
11
76
43
.52
94
11
76
42
.35
29
41
18
36
.47
05
88
24
52
.94
11
76
47
47
.05
88
23
53
65
.88
23
52
94
48
.23
52
94
12
45
.88
23
52
94
58
.82
35
29
41
49
.41
17
64
71
44
.70
58
82
35
47
.05
88
23
53
55
.29
41
17
65
52
.94
11
76
47
63
.52
94
11
76
50
.58
82
35
29
45
.88
23
52
94
49
.41
17
64
71
52
.94
11
76
47
44
.70
58
82
35
52
.94
11
76
47
44
.70
58
82
35
49
.41
17
64
71
43
.52
94
11
76
55
.29
41
17
65
47
.05
88
23
53
44
.70
58
82
35
55
.29
41
17
65
35
.29
41
17
65
54
.11
76
47
06
52
.94
11
76
47
61
.17
64
70
59
45
.88
23
52
94
52
.94
11
76
47
44
.70
58
82
35
45
.88
23
52
94
50
.58
82
35
29
48
.23
52
94
12
58
.82
35
29
41
55
.29
41
17
65
51
.76
47
05
88
55
.29
41
17
65
52
.94
11
76
47
0
45
.88
23
52
94
48
.82
35
29
41
42
.94
11
76
47
48
.82
35
29
41
51
.76
47
05
88
48
.23
52
94
12
57
.64
70
58
82
51
.76
47
05
88
54
.11
76
47
06
50
.58
82
35
29
47
.64
70
58
82
50 5
3.5
29
41
17
6
44
.70
58
82
35
51
.17
64
70
59
47
.64
70
58
82
56
.47
05
88
24
50
48
.82
35
29
41
54
.11
76
47
06
51
.76
47
05
88
53
.52
94
11
76
55
.29
41
17
65
57
.05
88
23
53
51
.76
47
05
88
51
.76
47
05
88
45
.88
23
52
94
47
.64
70
58
82
52
.94
11
76
47
50
.58
82
35
29
57
.05
88
23
53
1.1
76
47
05
88
51
.17
64
70
59
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4 2 5 2 6 2 7 2 8 2 9 3 0 3 1 3 2
minset1 RV11 RV21
51
.26
05
04
2
48
.73
94
95
8
47
.89
91
59
66
53
.78
15
12
61
49
.57
98
31
93
45
.37
81
51
26
44
.53
78
15
13
51
.26
05
04
2
55
.46
21
84
87
50
.42
01
68
07
44
.53
78
15
13
48
.73
94
95
8
51
.26
05
04
2
46
.21
84
87
39
47
.89
91
59
66
40
.33
61
34
45
47
.05
88
23
53
52
.94
11
76
47
52
.94
11
76
47
47
.89
91
59
66
52
.10
08
40
34
42
.85
71
42
86
56
.30
25
21
01
57
.98
31
93
28
52
.10
08
40
34
54
.62
18
48
74
61
.34
45
37
82
47
.05
88
23
53
41
.17
64
70
59
47
.89
91
59
66
44
.53
78
15
13
42
.01
68
06
72
61
.34
45
37
82
47
.89
91
59
66
49
.57
98
31
93
50
.42
01
68
07
52
.10
08
40
34
56
.30
25
21
01
51
.26
05
04
2
57
.14
28
57
14
51
.26
05
04
2
88
.23
52
94
12
42
.01
68
06
72
40
.33
61
34
45
42
.85
71
42
86
33
.61
34
45
38
35
.29
41
17
65
63
.02
52
10
08
67
.22
68
90
76
36
.13
44
53
78
49
.57
98
31
93
46
.63
86
55
46
55
.04
20
16
81
55
.46
21
84
87
49
.15
96
63
87
49
.15
96
63
87
55
.04
20
16
81
50
.42
01
68
07
52
.52
10
08
4
56
.30
25
21
01
53
.36
13
44
54
50
.42
01
68
07
50
49
.15
96
63
87
49
.15
96
63
87
50
88
.23
52
94
12
35
.29
41
17
65
38
.65
54
62
18
33
.19
32
77
31
37
.81
51
26
05
34
.45
37
81
51
60
.92
43
69
75
69
.74
78
99
16
34
.87
39
49
58
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4 2 5
minset1 RV11 RV21
0
20
40
60
80
100
120
1 3 5 7 9
11
13
15
17
19
21
23
25
27
29
31
33
35
37
39
41
43
45
47
49
51
53
55
57
59
61
63
65
67
69
71
73
75
77
79
81
83
85
87
89
91
93
95
97
99
10
1
10
3
10
5
10
7
10
9
11
1
11
3
11
5
11
7
11
9
12
1
12
3
12
5
12
7
12
9
13
1
13
3
13
5
13
7
13
9
minset1 RV11 RV21
17
.64
70
58
82
23
.52
94
11
76
23
.52
94
11
76
31
.37
25
49
02
19
.60
78
43
14
88
.23
52
94
12
84
.31
37
25
49
80
.39
21
56
86
74
.50
98
03
92
43
.13
72
54
9
98
.03
92
15
69
37
.25
49
01
96
9.8
03
92
15
69
7.8
43
13
72
55
47
.05
88
23
53
54
.90
19
60
78
52
.94
11
76
47
62
.74
50
98
04
45
.09
80
39
22
64
.70
58
82
35
64
.70
58
82
35
41
.17
64
70
59
49
.01
96
07
84
60
.78
43
13
73
60
.78
43
13
73
58
.82
35
29
41
13
.72
54
90
2
13
.72
54
90
2
9.8
03
92
15
69
23
.52
94
11
76
37
.25
49
01
96
70
.58
82
35
29
90
.19
60
78
43
88
.23
52
94
12
82
.35
29
41
18
49
.01
96
07
84 1
00
13
.72
54
90
2
3.9
21
56
86
27
7.8
43
13
72
55 56
.86
27
45
1
54
.90
19
60
78
49
.01
96
07
84
43
.13
72
54
9
62
.74
50
98
04
39
.21
56
86
27
35
.29
41
17
65
31
.37
25
49
02
62
.74
50
98
04
64
.70
58
82
35
64
.70
58
82
35
54
.90
19
60
78
10
.78
43
13
73
7.8
43
13
72
55
13
.72
54
90
2
22
.54
90
19
61
29
.41
17
64
71
73
.52
94
11
76
85
.29
41
17
65
88
.23
52
94
12
88
.23
52
94
12
35
.29
41
17
65
10
0
13
.72
54
90
2
10
.78
43
13
73
9.8
03
92
15
69
39
.21
56
86
27
47
.05
88
23
53
47
.05
88
23
53
31
.37
25
49
02
63
.72
54
90
2
33
.33
33
33
33
29
.41
17
64
71
50
.98
03
92
16
50
.98
03
92
16
54
.90
19
60
78
50 5
6.8
62
74
51
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4 2 5 2 6
minset1 RV11 RV12
c1355
c880
c1908
c2670
5.9
21
05
26
32
65
.13
15
78
95
39
.47
36
84
21
53
.94
73
68
42
48
.02
63
15
79
9.8
68
42
10
53
51
.31
57
89
47
56
.57
89
47
37
18
.42
10
52
63
43
.42
10
52
63
45
.39
47
36
84
25 3
8.8
15
78
94
7
47
.36
84
21
05
50
.65
78
94
74
45
.39
47
36
84
47
.36
84
21
05
44
.07
89
47
37
96
.05
26
31
58
55
.26
31
57
89
50
49
.34
21
05
26
4.6
05
26
31
58
62
.5
58
.55
26
31
58
57
.89
47
36
84
55
.92
10
52
63
20
.39
47
36
84
58
.55
26
31
58
51
.31
57
89
47
3.2
89
47
36
84
7.2
36
84
21
05
3.9
47
36
84
21
8.5
52
63
15
79
7.2
36
84
21
05
7.8
94
73
68
42
7.8
94
73
68
42
42
.10
52
63
16
42
.10
52
63
16
3.9
47
36
84
21
99
.34
21
05
26
53
.94
73
68
42
56
.57
89
47
37
59
.86
84
21
05
6.2
5
62
.82
89
47
37
55
.59
21
05
26
53
.61
84
21
05
51
.31
57
89
47
16
.77
63
15
79
57
.89
47
36
84
41
.44
73
68
42
1.6
44
73
68
42
7.2
36
84
21
05
4.9
34
21
05
26
13
.81
57
89
47
7.2
36
84
21
05
6.9
07
89
47
37
7.2
36
84
21
05
48
.35
52
63
16
43
.42
10
52
63
5.5
92
10
52
63
99
.67
10
52
63
47
.03
94
73
68
54
.27
63
15
79
58
.55
26
31
58
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2
minset1 RV11 RV21
0
50
100
150
1 3 5 7 9
11
13
15
17
19
21
23
25
27
29
31
33
35
37
39
41
43
45
47
49
51
53
55
57
59
61
63
65
67
69
71
73
75
77
79
81
83
85
87
89
91
93
95
97
99
10
1
10
3
10
5
10
7
10
9
11
1
11
3
11
5
11
7
11
9
12
1
12
3
minset1 RV11 RV21
41
.17
64
70
59
47
.05
88
23
53
55
.88
23
52
94
41
.17
64
70
59
47
.05
88
23
53
41
.17
64
70
59
55
.88
23
52
94
55
.88
23
52
94
29
.41
17
64
71
52
.94
11
76
47
44
.11
76
47
06
61
.76
47
05
88
47
.05
88
23
53
41
.17
64
70
59
50
41
.17
64
70
59
58
.82
35
29
41
47
.05
88
23
53
50
29
.41
17
64
71
44
.11
76
47
06
58
.82
35
29
41
61
.76
47
05
88
58
.82
35
29
41
32
.35
29
41
18
52
.94
11
76
47
58
.82
35
29
41
38
.23
52
94
12
50
41
.17
64
70
59
17
.64
70
58
82
26
.47
05
88
24
20
.58
82
35
29
38
.23
52
94
12
47
.05
88
23
53
50
50 5
5.8
82
35
29
4
35
.29
41
17
65
47
.05
88
23
53
38
.23
52
94
12
64
.70
58
82
35
55
.88
23
52
94
47
.05
88
23
53
52
.94
11
76
47
44
.11
76
47
06
61
.76
47
05
88
70
.58
82
35
29
35
.29
41
17
65
44
.11
76
47
06
47
.05
88
23
53
44
.11
76
47
06
41
.17
64
70
59
58
.82
35
29
41
52
.94
11
76
47
55
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23
52
94
55
.88
23
52
94
61
.76
47
05
88
44
.11
76
47
06
35
.29
41
17
65
35
.29
41
17
65
26
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05
88
24
17
.64
70
58
82
17
.64
70
58
82
22
.05
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23
53
44
.11
76
47
06
42
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70
58
82
52
.94
11
76
47
61
.76
47
05
88
50
45
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82
35
29
51
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05
88
24
50
45
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35
29
55
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23
52
94
48
.52
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11
76
54
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17
64
71
64
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58
82
35
63
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12
51
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24
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23
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50 51
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51
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76
47
06
42
.64
70
58
82
50
39
.70
58
82
35
44
.11
76
47
06
25
41
.17
64
70
59
10
.29
41
17
65
20
.58
82
35
29
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4 2 5 2 6 2 7 2 8 2 9 3 0 3 1 3 2
minset1 RV11 RV21
0
50
100
150
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 97 99 101103105107
minset1 RV11 RV21
c3540
c5315
c6288
c7552
114.2857143
85.71428571102.1978022 95.81780538
minset RV1 RV2 RV3
c17
311.7346939
284.3537415 284.0732169276.9742498
minset RV1 RV2 RV3
c432
1603.755102
1555.2653061547.737374 1549.625651
minset RV1 RV2 RV3
c499
1033.936652
950.2262443933.9992532
950.1333926
minset RV1 RV2 RV3
c880
1589.859944
1547.7871151552.794988 1550.491513
minset RV1 RV2 RV3
c1355
1251.645065
1192.422732 1187.5828811201.120637
minset RV1 RV2 RV3
c1908
Part(c)Data and Conclusions Min set –Minimum set generated by Atlanta.(size same as mentioned in part a)RV1-Random test vector set with size same as the minsetRV2-Random test vector set with 2x size of minsetRV3-Random test vector set with 10x size of minset.Y-axis-Average hamming distance percentage.
Average hamming distance =Sum of gamming distance of all pairs/total no.of pairs.
Average hamming distance percentage=Average hamming distance*100
6432.650494
6171.015274 6182.044174 6193.045059
minset RV1 RV2 RV3
c2670
946.4447543
676.4726386 682.8274275 678.2226881
minset RV1 RV2 RV3
c3540
5189.772341
5018.722392
4967.276878 4977.886454
1 2 3 4
c5315
1562.388592
1523.707665 1521.817384 1519.835155
minset RV1 RV2 RV3
c6288
4970.456503
4865.2847914879.928197
4900.259947
minset RV1 RV2 RV3
c7552 When compared to the Atalanta generated test vectors the random vectors have a lower hamming diversity in case of all benchmarks. This means the random vectors considered produced are such that the outputs have smaller difference between each other than the outputs produced by Atalanta.As Atalanta covers all the possible faults it might cover the entire range of outputs in order to see the difference and hence has more diversity.
From the graphs it can be seen that enlarging the test pattern did not give a significant difference in the hamming distancediversity in most of the cases(but not all).What I understood from this is the random vectors I have chosen might be in such away that they are leading a change in the output of only a specific part of the circuit .So in order to increase the HD diversity the test vectors used to increase the random set should be in such a way that theycan produce noticeable change across the output. For example for C17 benchmark the Random test set with double size thanthe minset shows greater diversity than the Random test with size similar to that of minset .This means the increased vectorsare capable of generating wide change in output values leading to increased diversity. It is similar in case of C7552 benchmarkalso.So from this we can conclude that the HD diversity depends on the variation that the input test set can make at the output .If Inputs in the random set are increased as shown in Figure a i.e. addition of these inputs can change large number ofoutputs then the diversity increases( with exceptions -what if they are covering the same part of circuit as inputs that arealready existing?? In such a case the diversity does not change much.)If inputs are as shown Figure b i.e. addition of inputs cover a smaller part of output then the diversity decreases.One more observation is the diversity depends not only the type but also depends on size because as the number ofcombinations increase the denominator for average hamming distance( which we are considering as a measure for diversity )increases and hence the diversity decreases .So the set size should be increased as less as possible with as much outputcoverage as possible to increase the diversity.
Figure a Figure b