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Table 4 Results for datasets 2, 3, and 4 by running experiments on hicloud

From: Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment

 

Algorithm

Sequential

Sequential

Parallel

  

GA-PSO

iGA-PSO

iGA-PSO

50 genes (dataset 2)

Master / Slaves

1 / 0

1 / 0

1 / 20

1 / 30

 

Time cost (mins)

3019

2898

591

465

 

Speed-up

-

1

4.9036

6.2323

 

Fitness value per gene

0.2345

0.2115

0.2140

0.2076

100 genes (dataset 3)

Master / Slaves

1 / 0

1 / 0

1 / 20

1 / 30

 

Time cost (mins)

11342

10284

1526

1316

 

Speed-up

-

1

6.7392

7.8146

 

Fitness value per gene

0.3843

0.3520

0.3642

0.3582

125 genes (dataset 4)

Master / Slaves

1 / 0

1 / 0

1 / 20

1 / 30

 

Time cost (mins)

18019

16323

2152

1792

 

Speed-up

-

1

7.5850

9.1088

 

Fitness value per gene

0.2358

0.2056

0.2195

0.2195