Table 3

Runtime Performance of svmPRAT on the Disorder Dataset (in seconds).

w = f = 11

w = f = 13

w = f = 15


#KER

NO

YES

SP

#KER

NO

YES

SP

#KER

NO

YES

SP

1.93e+10

83993

45025

1.86

1.92e+10

95098

53377

1.78

1.91e+10

106565

54994

1.93

1.91e+10

79623

36933

2.15

1.88e+10

90715

39237

2.31

1.87e+10

91809

39368

2.33

2.01e+10

99501

56894

1.75

2.05e+10

112863

65035

1.73

2.04e+10

125563

69919

1.75


The runtime performance of svmPRAT was benchmarked for learning a classification model on a 64-bit Intel Xeon CPU 2.33 GHz processor. #KER denotes the number of kernel evaluations for training the SVM model. NO denotes runtime in seconds when the CBLAS library was not used, YES denotes the runtime in seconds when the CBLAS library was used, and SP denotes the speedup achieved using the CBLAS library.

Rangwala et al. BMC Bioinformatics 2009 10:439   doi:10.1186/1471-2105-10-439

Open Data