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

机译:X86 Xeon系统上用于多媒体数据处理的快速傅立叶变换基准

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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.
机译:我在X86 Xeon E5 2690 v3系统上对著名的Fast Fourier变换库进行了基准测试。傅立叶变换图像处理是一种重要的工具,可用于将图像分解为正弦和余弦分量。如果输入的图像在空间域中由等式表示,则傅立叶变换的输出表示傅立叶或频域中的图像。每个点代表傅立叶域图像中的空间域图像中包括的特定频率。傅立叶变换作为各种应用广泛用于图像分析,图像过滤,图像压缩和图像重建。傅里叶变换在信号处理,图像处理和语音识别中起着重要作用。它已被广泛应用于各个领域。例如,这通常是信号处理,用于数字信号处理应用中,例如语音识别,图像处理。离散傅立叶变换是一种特定类型的傅立叶变换。它将序列随时间映射到频率上的序列。如果实现为离散傅立叶变换,则时间复杂度为O(N2)。实际上,这不是更好的使用方法。可选地,快速傅立叶变换可以仅使用O(n log n)算法轻松地执行并行的离散傅立叶变换。快速傅立叶变换广泛用于各种科学计算程序中。如果使用正确的库,可以提高程序的性能,而无需任何额外的努力。我有一个著名的快速傅立叶变换库,它将在基于X86的英特尔至强E5 2690系统上执行基准测试。在机器当前的Intel Xeon X86 Linux系统中。我已经在基于Intel X86 Xeon E5的系统上安装了Intel IPP库,FFTW3库(西FFT),Kiss -FFT库和numutils库。基准测试在C进行,并在整个变换大小范围内测量性能。它在一维中对真实和复杂转换进行基准测试。

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