FFT Archives - CenterSpace

FFT Performance Benchmarks in .NET

Posted on January 5, 2011March 1, 2016 by Paul Shirkey

We've had a number of inquires about the CenterSpace FFT benchmarks, so I thought I would code up a few tests and run them on my machine. I've included our FFT performance numbers and the code that generated those numbers so you can try them on your machine. (If you don't have NMath, you'll need to download the eval version). I also did a comparison of 1 dimensional real DFTs, with FFTW, one of...
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Convolution, Correlation, and the FFT

Posted on November 3, 2009March 1, 2016 by Paul Shirkey

Most scientists and programmers understand the basic implementation details of their chosen math library. However, when algorithms are ported from one library to another, problems are hard to avoid. This seems to be particularly so when dealing with convolutions, correlations and the FFT - fundamental building blocks in many areas of computation. Frequently the theoretical concepts are clear, b...
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Convolution in CenterSpace’s NMATH 4.0

Posted on October 19, 2009December 7, 2009 by Paul Shirkey

Convolution is a fundamental operation in data smoothing and filtering, and is used in many other applications ranging from discrete wavelet transform's to LTI system theory. NMath supports a high performance, forward scaling set of convolution classes that support both complex and real data. These classes will scale in performance in proportion to the number of processing cores - eliminating co...
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Modern Fast Fourier Transform

Posted on September 28, 2009February 7, 2023 by Paul Shirkey

All variants of the original Cooley-Tukey O(n log n) fast Fourier transform fundamentally exploit different ways to factor the discrete Fourier summation of length N. For example, the split-radix FFT algorithm divides the Fourier summation of length N into three new Fourier summations: one of length N/2 and two of length N/4. The prime factor FFT, divides the Fourier summation of length N, i...
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High Performance FFT in NMath 4.0

Posted on September 2, 2009February 15, 2010 by Paul Shirkey

The next release of Center Space's NMATH .NET libraries will contain high performance, multi-core aware, fast fourier transform classes. This set of classes will elegantly support all common 1D and 2D FFT computations in a robust easy to use object-oriented interface. The following FFT classes will be available. DoubleComplexForward1DFFT DoubleComplexBackward1DFFT DoubleComplexForw...
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