In this paper we present an automatic system able to detect the internal structure of executions of high-performance computing applications. This automatic system is able to rule out non-significant regions of executions, to detect redundancies, and, finally, to select small but significant execution regions. This automatic detection process is based on spectral analysis (wavelet transform, Fourier transform, etc.) and works detecting the most important frequencies of the application’s execution. These main frequencies are strongly related to the internal loops of the application’s source code. The automatic detection of small but significant execution regions shown in the paper reduces the load of the performance analysis process remarkably.