Fast Fourier Transform Algorithm in Parallel Processing

Title: Fast Fourier Transform Algorithm in Parallel Processing

Abstract: This research aimed to design, build, and execute a code for the Fast Fourier Transform (FFT) using parallel processing on a cluster of computers. The code was executed on a MacOS operating system and used the MacMPI routines for message passing interface. The main goal was to improve the computational efficiency of the FFT by utilizing parallel processing.

Research Question: Can the Fast Fourier Transform be efficiently implemented using parallel processing on a cluster of computers?

Methodology: The study used a cluster of 2n computers to perform parallel processing. The computers were arranged in a network, and the code was designed to distribute the data and operations across the network. The MacMPI routines were used to facilitate communication between the computers.

Results: The research found that the code was successfully executed on the cluster of computers. The FFT was performed more efficiently using parallel processing, as it required fewer computations and time. The results showed that the code could be used to perform other applications, such as filtering and image processing.

Implications: The research demonstrated that the Fast Fourier Transform can be efficiently implemented using parallel processing. This could have significant implications for fields that rely on the FFT, such as signal processing, image processing, and astronomy. The research also highlighted the potential of parallel processing for other computational tasks.

Link to Article: https://arxiv.org/abs/0103001v1 Authors: arXiv ID: 0103001v1