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In the article the techniques efficient using of multi-core processors for the task of calculating the fast Fourier transform. The fast Fourier transform is led on the basis of calculating a time time-frequency correlation function. The time-frequency correlation function allows increasing the information content of the analysis as compared with the classic correlation function. The significant computational capabilities are required to calculate the time-frequency correlation function because of the necessity of multiple computing fast Fourier transform. For computing the fast Fourier transform is used Cooley-Tukey algorithm with fixed base two, which lends itself to efficient parallelization and is simple to implement. Immediately before the fast Fourier transform computation the procedure of bit-reversing the input data sequence is used. For algorithm of calculating the time-frequency correlation function using parallel computing the data defining the optimal number of iterations for each core of the CPU, depending on the sample size was experimentally obtained. The results of experiments allow developing the special software that enables automatic selection of an effective amount of sub parallel processing of data, also the choice of sequential or parallel computations mode, depending on the sample size and the number of frequency intervals in the calculation of time-frequency correlation function.

Аврамчук В.С., Фаерман В.А. Алгоритм вычисления нормированной частотно-временной корреляционной функции