Parallel computation of the time-frequency power spectrum: analysis and comparison to the bispectrum

Experiments of large data sets are computationally expensive. Signal processing analysis on a single CPU leads to unacceptably long execution times. The paper presents initial experiments on calculating the time-frequency power spectrum using the coarse-grained parallel programming technique. Experimental speedup factors are given and discussed. The measured speedup factor of the time-frequency power spectrum parallel calculation process is sublinear which indicates that the time-frequency power spectrum is a suitable application for parallel programming. The parallel efficiency is acceptable with the lowest value of 75.1% occurring at N = 10. The maximum speedup factor of 9.1 is obtained when N = 12 at 75.3% of efficiency.