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Table 3 Results for datasets 2, 3, and 4 by running the experiments in the computer center

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 / 25
  Time cost (mins) 923 908 218 176
  Speed-up - 1 4.1651 5.1591
  Fitness value per gene 0.2876 0.2494 0.2593 0.2562
100 genes (dataset 3) Master / Slaves 1 / 0 1 / 0 1 / 20 1 / 25
  Time cost (mins) 3,687 3,137 496 411
  Speed-up - 1 6.3246 7.6326
  Fitness value per gene 0.4567 0.4225 0.4165 0.4114
125 genes (dataset 4) Master / Slaves 1 / 0 1 / 0 1 / 20 1 / 25
  Time cost (mins) 5,788 4,927 702 595
  Speed-up - 1 7.0185 8.2807
  Fitness value per gene 0.2822 0.2651 0.2670 0.2667
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BMC Systems Biology

ISSN: 1752-0509

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