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ECE469 proj2_Lakshmi Yasaswi Kamireddy
- 1. Computer System Design Project-2 Lakshmi Yasaswi Kamireddy (651771619)
- 2. 0 5 10 15 20 25 30 35 Minset-Size 50 0 5 10 15 20 25 RV1 0 2 4 6 8 10 12 14 16 RV2 0 10 20 30 40 50 Minset-Size 49 0 5 10 15 20 25 30 RV1 0 5 10 15 20 25 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 28.57142857 28.57142857 42.85714286 57.14285 42.85714 21.42857143 35.71428571 42.85714286 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)
- 3. 0 10 20 30 9.375 15.625 21.875 25 31.25 37.5 40.625 43.75 46.875 50 53.125 56.25 59.375 62.5 65.625 68.75 71.875 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 0 2 4 6 8 10 Minset-Size-106 0 5 10 15 RV1 0 2 4 6 8 10 12 RV2 c2670 0 5 10 15 20 25 Minset-Size-152 0 5 10 15 20 25 RV2 0 5 10 15 20 25 RV1c3540
- 5. 57.14285714 57.14285714 85.71428571 57.14285714 57.14285714 64.285714291 2 minset1 RV1 RV2 77.55102041 59.18367347 57.14285714 85.71428571 53.06122449 48.97959184 42.85714286 100 73.46938776 59.18367347 61.2244898 48.97959184 32.65306122 46.93877551 89.79591837 85.71428571 64.28571429 55.10204082 50 32.65306122 42.85714286 1 2 3 4 5 6 7 minset1 RV11 RV21 46 52 58 52 40 52 50 42 44 58 42 48 42 50 42 52 54 38 56 44 42 36 38 46 44 50 44 50 52 42 42 48 54 60 40 50 62 60 50 58 46 50 42 64 54 48 48 50 48 52 56 42 52 42 52 38 56 48 56 38 54 60 2 52 54 53 49 39 59 47 53 44 50 48 49 51 52 50 45 56 40 57 56 60 51 45 51 55 44 47 43 53 53 56 0 43 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 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
- 6. 52.94117647 43.52941176 48.23529412 42.35294118 43.52941176 49.41176471 57.64705882 50.58823529 43.52941176 56.47058824 47.05882353 54.11764706 37.64705882 50.58823529 49.41176471 56.47058824 43.52941176 38.82352941 43.52941176 43.52941176 42.35294118 36.47058824 52.94117647 47.05882353 65.88235294 48.23529412 45.88235294 58.82352941 49.41176471 44.70588235 47.05882353 55.29411765 52.94117647 63.52941176 50.58823529 45.88235294 49.41176471 52.94117647 44.70588235 52.94117647 44.70588235 49.41176471 43.52941176 55.29411765 47.05882353 44.70588235 55.29411765 35.29411765 54.11764706 52.94117647 61.17647059 45.88235294 52.94117647 44.70588235 45.88235294 50.58823529 48.23529412 58.82352941 55.29411765 51.76470588 55.29411765 52.94117647 0 45.88235294 48.82352941 42.94117647 48.82352941 51.76470588 48.23529412 57.64705882 51.76470588 54.11764706 50.58823529 47.64705882 50 53.52941176 44.70588235 51.17647059 47.64705882 56.47058824 50 48.82352941 54.11764706 51.76470588 53.52941176 55.29411765 57.05882353 51.76470588 51.76470588 45.88235294 47.64705882 52.94117647 50.58823529 57.05882353 1.176470588 51.17647059 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 minset1 RV11 RV21 51.2605042 48.7394958 47.89915966 53.78151261 49.57983193 45.37815126 44.53781513 51.2605042 55.46218487 50.42016807 44.53781513 48.7394958 51.2605042 46.21848739 47.89915966 40.33613445 47.05882353 52.94117647 52.94117647 47.89915966 52.10084034 42.85714286 56.30252101 57.98319328 52.10084034 54.62184874 61.34453782 47.05882353 41.17647059 47.89915966 44.53781513 42.01680672 61.34453782 47.89915966 49.57983193 50.42016807 52.10084034 56.30252101 51.2605042 57.14285714 51.2605042 88.23529412 42.01680672 40.33613445 42.85714286 33.61344538 35.29411765 63.02521008 67.22689076 36.13445378 49.57983193 46.63865546 55.04201681 55.46218487 49.15966387 49.15966387 55.04201681 50.42016807 52.5210084 56.30252101 53.36134454 50.42016807 50 49.15966387 49.15966387 50 88.23529412 35.29411765 38.65546218 33.19327731 37.81512605 34.45378151 60.92436975 69.74789916 34.87394958 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 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 99 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 minset1 RV11 RV21 17.64705882 23.52941176 23.52941176 31.37254902 19.60784314 88.23529412 84.31372549 80.39215686 74.50980392 43.1372549 98.03921569 37.25490196 9.803921569 7.843137255 47.05882353 54.90196078 52.94117647 62.74509804 45.09803922 64.70588235 64.70588235 41.17647059 49.01960784 60.78431373 60.78431373 58.82352941 13.7254902 13.7254902 9.803921569 23.52941176 37.25490196 70.58823529 90.19607843 88.23529412 82.35294118 49.01960784 100 13.7254902 3.921568627 7.843137255 56.8627451 54.90196078 49.01960784 43.1372549 62.74509804 39.21568627 35.29411765 31.37254902 62.74509804 64.70588235 64.70588235 54.90196078 10.78431373 7.843137255 13.7254902 22.54901961 29.41176471 73.52941176 85.29411765 88.23529412 88.23529412 35.29411765 100 13.7254902 10.78431373 9.803921569 39.21568627 47.05882353 47.05882353 31.37254902 63.7254902 33.33333333 29.41176471 50.98039216 50.98039216 54.90196078 50 56.8627451 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 minset1 RV11 RV12 c1355 c880 c1908 c2670
- 7. 5.921052632 65.13157895 39.47368421 53.94736842 48.02631579 9.868421053 51.31578947 56.57894737 18.42105263 43.42105263 45.39473684 25 38.81578947 47.36842105 50.65789474 45.39473684 47.36842105 44.07894737 96.05263158 55.26315789 50 49.34210526 4.605263158 62.5 58.55263158 57.89473684 55.92105263 20.39473684 58.55263158 51.31578947 3.289473684 7.236842105 3.947368421 8.552631579 7.236842105 7.894736842 7.894736842 42.10526316 42.10526316 3.947368421 99.34210526 53.94736842 56.57894737 59.86842105 6.25 62.82894737 55.59210526 53.61842105 51.31578947 16.77631579 57.89473684 41.44736842 1.644736842 7.236842105 4.934210526 13.81578947 7.236842105 6.907894737 7.236842105 48.35526316 43.42105263 5.592105263 99.67105263 47.03947368 54.27631579 58.55263158 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 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 99 101 103 105 107 109 111 113 115 117 119 121 123 minset1 RV11 RV21 41.17647059 47.05882353 55.88235294 41.17647059 47.05882353 41.17647059 55.88235294 55.88235294 29.41176471 52.94117647 44.11764706 61.76470588 47.05882353 41.17647059 50 41.17647059 58.82352941 47.05882353 50 29.41176471 44.11764706 58.82352941 61.76470588 58.82352941 32.35294118 52.94117647 58.82352941 38.23529412 50 41.17647059 17.64705882 26.47058824 20.58823529 38.23529412 47.05882353 50 50 55.88235294 35.29411765 47.05882353 38.23529412 64.70588235 55.88235294 47.05882353 52.94117647 44.11764706 61.76470588 70.58823529 35.29411765 44.11764706 47.05882353 44.11764706 41.17647059 58.82352941 52.94117647 55.88235294 55.88235294 61.76470588 44.11764706 35.29411765 35.29411765 26.47058824 17.64705882 17.64705882 22.05882353 44.11764706 42.64705882 52.94117647 61.76470588 50 45.58823529 51.47058824 50 45.58823529 55.88235294 48.52941176 54.41176471 64.70588235 63.23529412 51.47058824 47.05882353 58.82352941 50 51.47058824 42.64705882 51.47058824 51.47058824 44.11764706 42.64705882 50 39.70588235 44.11764706 25 41.17647059 10.29411765 20.58823529 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 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
- 8. 114.2857143 85.71428571 102.1978022 95.81780538 minset RV1 RV2 RV3 c17 311.7346939 284.3537415 284.0732169 276.9742498 minset RV1 RV2 RV3 c432 1603.755102 1555.265306 1547.737374 1549.625651 minset RV1 RV2 RV3 c499 1033.936652 950.2262443 933.9992532 950.1333926 minset RV1 RV2 RV3 c880 1589.859944 1547.787115 1552.794988 1550.491513 minset RV1 RV2 RV3 c1355 1251.645065 1192.422732 1187.582881 1201.120637 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 minset RV2-Random test vector set with 2x size of minset RV3-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
- 9. 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 4865.284791 4879.928197 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.
- 10. From the graphs it can be seen that enlarging the test pattern did not give a significant difference in the hamming distance diversity in most of the cases(but not all).What I understood from this is the random vectors I have chosen might be in such a way 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 they can produce noticeable change across the output. For example for C17 benchmark the Random test set with double size than the minset shows greater diversity than the Random test with size similar to that of minset .This means the increased vectors are capable of generating wide change in output values leading to increased diversity. It is similar in case of C7552 benchmark also. 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 of outputs then the diversity increases( with exceptions -what if they are covering the same part of circuit as inputs that are already 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 of combinations 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 output coverage as possible to increase the diversity. Figure a Figure b