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Advances, Systems and Applications

Table 2 Comparison of running time

From: Efficient parallel spectral clustering algorithm design for large data sets under cloud computing environment

Data volume

Machines

Similar matrix (sec)

Eigenvector (sec)

K-means (sec)

Total time (sec)

DS1 (10000)

1

0.386

0.481

0.156

1.023

2

0.532

1.099

3.436

5.067

4

0.186

0.364

1.137

1.687

6

0.096

0.175

0.582

0.853

8

0.038

0.065

0.231

0.334

10

0.025

0.050

0.204

0.279

DS2 (50000)

1

7.251

9.315

2.947

19.513

2

9.814

12.879

4.139

26.832

4

3.162

3.963

1.376

8.501

6

2.299

2.829

1.239

6.367

8

1.477

1.881

0.910

4.268

10

1.218

1.555

0.887

3.660

DS3 (100000)

1

19.228

23.982

8.572

51.782

2

11.234

14.409

4.414

30.057

4

5.736

6.538

2.246

14.520

6

4.007

5.587

1.432

11.026

8

2.965

4.056

0.901

7.922

10

2.359

3.453

0.654

6.466

DS4 (1000000)

1

7671.580

9603.573

3422.564

20697.717

2

37.590

46.058

16.678

100.326

4

19.629

23.755

8.719

53.103

6

10.126

18.473

6.475

35.074

8

8.797

13.532

4.865

27.194

10

6.894

11.415

3.852

22.161

DS5 (5000000)

1

31602.604

39909.984

16630.820

88143.408

2

150.853

191.559

80.850

423.262

4

75.164

98.906

39.213

213.283

6

50.273

70.427

22.087

142.787

8

40.032

53.142

18.521

111.695

 

10

30.841

42.112

13.940

86.893