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Table 3 Runtime for varying sequence lengths

From: Design of high-performance parallelized gene predictors in MATLAB

    Time (s) for the following sequence sizes:
Function Loop type Processing 5,000 50,000 200,000 500,000 1,000,000 5,000,000 15,000,000
1 goertzel.m PARFOR CPU 8 T 1.06 8.29 32.91 82.16 161.89 805.44 TLTC
2 goertzelMEX FOR CPU 0.18 1.78 7.11 17.84 35.65 178.30 535.21
3 goertzelMEX PARFOR CPU 2 T 0.19 0.99 3.86 9.58 19.20 100.39 287.35
4 goertzelMEX PARFOR CPU 4 T 0.18 0.60 2.36 5.81 11.41 56.27 164.84
5 goertzelMEX PARFOR CPU 8 T 0.25 0.53 1.95 4.75 9.52 47.49 164.57
6 Custom Goertzel PARFOR CPU 8 T 0.25 0.37 1.18 2.83 5.56 27.63 87.47
7 JACKET’s FFT (full sequences) GFOR GPU 0.03 0.22 0.78 1.90 3.78 18.82 57.68
8 JACKET’s FFT (1 M blocks) GFOR GPU 0.03 0.22 0.78 1.90 3.78 18.90 56.70
9 Matlab’s FFT PARFOR CPU 8 T 0.29 0.42 1.46 3.51 6.95 34.12 109.15
10 Custom Goerztel on GPU GFOR GPU 0.22 0.79 2.82 7.15 14.09 71.01 213.31