Fast Fourier transform benchmark on X86 Xeon system for multimedia data processing

• Published in: Multimedia tools and applications Vol. 76; no. 4; pp. 6015 - 6030
• Main Authors: Park, Young-Soo, Park, Koo-Rack, Kim, Jin-Mook, Jeong, Hwa-Young
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2017; Springer Nature B.V
• Subjects: Benchmarks; Complexity; Computer Communication Networks; Computer Science; Data processing; Data Structures and Information Theory; Digital imaging; Digital signal processing; Digital signal processors; Fast Fourier transformations; Filtration; Fourier transforms; Image analysis; Image compression; Image processing; Image reconstruction; Libraries; Multimedia; Multimedia Information Systems; Object recognition; Performance enhancement; Polypropylene; Signal processing; Special Purpose and Application-Based Systems; Speech recognition; Trigonometric functions; Voice recognition; Image processing; Numutils; Signal processing; INTEL IPP; Fourier transform; FFTW3; Kiss-fft
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-015-2843-7

I benchmarking the well-known Fast Fourier Transforms Library at X86 Xeon E5 2690 v3 system. Fourier transform image processing is an important tool that is used to decompose the image into sine and cosine components. If the input image represented by the equation in the spatial domain, output from the Fourier transform represents the image in the fourier or the frequency domain. Each point represents a particular frequency included in the spatial domain image in the Fourier domain image. Fourier transform is used widely for image analysis, image filtering, image compression and image reconstruction as a wide variety of applications. Fourier transform plays a important role in signal processing, image processing and speech recognition. It has been used in a wide range of sectors. For example, this is often a signal processing, is used in digital signal processing applications, such as voice recognition, image processing. The Discrete Fourier transform is a specific kind of Fourier transform. It maps the sequence over time to sequence over frequencies. If it implemented as a discrete Fourier transform, the time complexity is O (N2). It’s actually not a better way to use. Alternatively, the Fast Fourier Transform is possible to easily perform a Discrete Fourier Transform of parallelism with only O (n log n) algorithm. Fast Fourier Transform is widely used in a variety of scientific computing program. If you are using the correct library can improve the performance of the program, without any additional effort. I have a well-known fast Fourier transform library was going to perform a benchmarking on X86 based Intel Xeon E5 2690 systems. In the machine’s current Intel Xeon X86 Linux system. I have installed Intel IPP library, FFTW3 Library (West FFT), Kiss -FFT library and the numutils library on Intel X86 Xeon E5 based systems. The benchmark performed at C, and measuring the performance over a range of a transform size. It benchmarks both real and complex transforms in one dimension.