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|  | (version 3.3.10, 10 December 2020). | ||
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|  | Copyright (C) 2003 Matteo Frigo. | ||
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|  | <span id="Introduction"></span><div class="header"> | ||
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|  | Next: <a href="Tutorial.html" accesskey="n" rel="next">Tutorial</a>, Previous: <a href="index.html" accesskey="p" rel="prev">Top</a>, Up: <a href="index.html" accesskey="u" rel="up">Top</a>   [<a href="index.html#SEC_Contents" title="Table of contents" rel="contents">Contents</a>][<a href="Concept-Index.html" title="Index" rel="index">Index</a>]</p> | ||
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|  | <hr> | ||
|  | <span id="Introduction-1"></span><h2 class="chapter">1 Introduction</h2> | ||
|  | <p>This manual documents version 3.3.10 of FFTW, the | ||
|  | <em>Fastest Fourier Transform in the West</em>.  FFTW is a comprehensive | ||
|  | collection of fast C routines for computing the discrete Fourier | ||
|  | transform (DFT) and various special cases thereof. | ||
|  | <span id="index-discrete-Fourier-transform"></span> | ||
|  | <span id="index-DFT"></span> | ||
|  | </p><ul> | ||
|  | <li> FFTW computes the DFT of complex data, real data, even- | ||
|  |   or odd-symmetric real data (these symmetric transforms are usually | ||
|  |   known as the discrete cosine or sine transform, respectively), and the | ||
|  |   discrete Hartley transform (DHT) of real data. | ||
|  | 
 | ||
|  | </li><li> The input data can have arbitrary length.   | ||
|  |        FFTW employs <i>O</i>(<i>n</i> log <i>n</i>) | ||
|  |  algorithms for all lengths, including | ||
|  |        prime numbers. | ||
|  | 
 | ||
|  | </li><li> FFTW supports arbitrary multi-dimensional data. | ||
|  | 
 | ||
|  | </li><li> FFTW supports the SSE, SSE2, AVX, AVX2, AVX512, KCVI, Altivec, VSX, and | ||
|  |        NEON vector instruction sets. | ||
|  | 
 | ||
|  | </li><li> FFTW includes parallel (multi-threaded) transforms | ||
|  |        for shared-memory systems. | ||
|  | </li><li> Starting with version 3.3, FFTW includes distributed-memory parallel | ||
|  |        transforms using MPI. | ||
|  | </li></ul> | ||
|  | 
 | ||
|  | <p>We assume herein that you are familiar with the properties and uses of | ||
|  | the DFT that are relevant to your application.  Otherwise, see | ||
|  | e.g. <cite>The Fast Fourier Transform and Its Applications</cite> by E. O. Brigham | ||
|  | (Prentice-Hall, Englewood Cliffs, NJ, 1988). | ||
|  | <a href="http://www.fftw.org">Our web page</a> also has links to FFT-related | ||
|  | information online. | ||
|  | <span id="index-FFTW"></span> | ||
|  | </p> | ||
|  | 
 | ||
|  | <p>In order to use FFTW effectively, you need to learn one basic concept | ||
|  | of FFTW’s internal structure: FFTW does not use a fixed algorithm for | ||
|  | computing the transform, but instead it adapts the DFT algorithm to | ||
|  | details of the underlying hardware in order to maximize performance. | ||
|  | Hence, the computation of the transform is split into two phases. | ||
|  | First, FFTW’s <em>planner</em> “learns” the fastest way to compute the | ||
|  | transform on your machine.  The planner | ||
|  | <span id="index-planner"></span> | ||
|  | produces a data structure called a <em>plan</em> that contains this | ||
|  | <span id="index-plan"></span> | ||
|  | information.  Subsequently, the plan is <em>executed</em> | ||
|  | <span id="index-execute"></span> | ||
|  | to transform the array of input data as dictated by the plan.  The | ||
|  | plan can be reused as many times as needed.  In typical | ||
|  | high-performance applications, many transforms of the same size are | ||
|  | computed and, consequently, a relatively expensive initialization of | ||
|  | this sort is acceptable.  On the other hand, if you need a single | ||
|  | transform of a given size, the one-time cost of the planner becomes | ||
|  | significant.  For this case, FFTW provides fast planners based on | ||
|  | heuristics or on previously computed plans. | ||
|  | </p> | ||
|  | <p>FFTW supports transforms of data with arbitrary length, rank, | ||
|  | multiplicity, and a general memory layout.  In simple cases, however, | ||
|  | this generality may be unnecessary and confusing.  Consequently, we | ||
|  | organized the interface to FFTW into three levels of increasing | ||
|  | generality. | ||
|  | </p><ul> | ||
|  | <li> The <em>basic interface</em> computes a single  | ||
|  |       transform of contiguous data. | ||
|  | </li><li> The <em>advanced interface</em> computes transforms  | ||
|  |       of multiple or strided arrays. | ||
|  | </li><li> The <em>guru interface</em> supports the most general data  | ||
|  |       layouts, multiplicities, and strides. | ||
|  | </li></ul> | ||
|  | <p>We expect that most users will be best served by the basic interface, | ||
|  | whereas the guru interface requires careful attention to the | ||
|  | documentation to avoid problems. | ||
|  | <span id="index-basic-interface"></span> | ||
|  | <span id="index-advanced-interface"></span> | ||
|  | <span id="index-guru-interface"></span> | ||
|  | </p> | ||
|  | 
 | ||
|  | <p>Besides the automatic performance adaptation performed by the planner, | ||
|  | it is also possible for advanced users to customize FFTW manually.  For | ||
|  | example, if code space is a concern, we provide a tool that links only | ||
|  | the subset of FFTW needed by your application.  Conversely, you may need | ||
|  | to extend FFTW because the standard distribution is not sufficient for | ||
|  | your needs.  For example, the standard FFTW distribution works most | ||
|  | efficiently for arrays whose size can be factored into small primes | ||
|  | (<em>2</em>, <em>3</em>, <em>5</em>, and <em>7</em>), and otherwise it uses a | ||
|  | slower general-purpose routine.  If you need efficient transforms of | ||
|  | other sizes, you can use FFTW’s code generator, which produces fast C | ||
|  | programs (“codelets”) for any particular array size you may care | ||
|  | about. | ||
|  | <span id="index-code-generator"></span> | ||
|  | <span id="index-codelet"></span> | ||
|  | For example, if you need transforms of size | ||
|  | 513 = 19*3<sup>3</sup>, | ||
|  | you can customize FFTW to support the factor <em>19</em> efficiently. | ||
|  | </p> | ||
|  | <p>For more information regarding FFTW, see the paper, “The Design and | ||
|  | Implementation of FFTW3,” by M. Frigo and S. G. Johnson, which was an | ||
|  | invited paper in <cite>Proc. IEEE</cite> <b>93</b> (2), p. 216 (2005).  The | ||
|  | code generator is described in the paper “A fast Fourier transform | ||
|  | compiler”, | ||
|  | <span id="index-compiler"></span> | ||
|  | by M. Frigo, in the <cite>Proceedings of the 1999 ACM SIGPLAN Conference | ||
|  | on Programming Language Design and Implementation (PLDI), Atlanta, | ||
|  | Georgia, May 1999</cite>.  These papers, along with the latest version of | ||
|  | FFTW, the FAQ, benchmarks, and other links, are available at | ||
|  | <a href="http://www.fftw.org">the FFTW home page</a>.   | ||
|  | </p> | ||
|  | <p>The current version of FFTW incorporates many good ideas from the past | ||
|  | thirty years of FFT literature.  In one way or another, FFTW uses the | ||
|  | Cooley-Tukey algorithm, the prime factor algorithm, Rader’s algorithm | ||
|  | for prime sizes, and a split-radix algorithm (with a | ||
|  | “conjugate-pair” variation pointed out to us by Dan Bernstein). | ||
|  | FFTW’s code generator also produces new algorithms that we do not | ||
|  | completely understand. | ||
|  | <span id="index-algorithm"></span> | ||
|  | The reader is referred to the cited papers for the appropriate | ||
|  | references. | ||
|  | </p> | ||
|  | <p>The rest of this manual is organized as follows.  We first discuss the | ||
|  | sequential (single-processor) implementation.  We start by describing | ||
|  | the basic interface/features of FFTW in <a href="Tutorial.html">Tutorial</a>.   | ||
|  | Next, <a href="Other-Important-Topics.html">Other Important Topics</a> discusses data alignment | ||
|  | (see <a href="SIMD-alignment-and-fftw_005fmalloc.html">SIMD alignment and fftw_malloc</a>), | ||
|  | the storage scheme of multi-dimensional arrays | ||
|  | (see <a href="Multi_002ddimensional-Array-Format.html">Multi-dimensional Array Format</a>), and FFTW’s mechanism for | ||
|  | storing plans on disk (see <a href="Words-of-Wisdom_002dSaving-Plans.html">Words of Wisdom-Saving Plans</a>).  Next, | ||
|  | <a href="FFTW-Reference.html">FFTW Reference</a> provides comprehensive documentation of all | ||
|  | FFTW’s features.  Parallel transforms are discussed in their own | ||
|  | chapters: <a href="Multi_002dthreaded-FFTW.html">Multi-threaded FFTW</a> and <a href="Distributed_002dmemory-FFTW-with-MPI.html">Distributed-memory FFTW with MPI</a>.  Fortran programmers can also use FFTW, as described in | ||
|  | <a href="Calling-FFTW-from-Legacy-Fortran.html">Calling FFTW from Legacy Fortran</a> and <a href="Calling-FFTW-from-Modern-Fortran.html">Calling FFTW from Modern Fortran</a>.  <a href="Installation-and-Customization.html">Installation and Customization</a> explains how to | ||
|  | install FFTW in your computer system and how to adapt FFTW to your | ||
|  | needs.  License and copyright information is given in <a href="License-and-Copyright.html">License and Copyright</a>.  Finally, we thank all the people who helped us in | ||
|  | <a href="Acknowledgments.html">Acknowledgments</a>. | ||
|  | </p> | ||
|  | <hr> | ||
|  | <div class="header"> | ||
|  | <p> | ||
|  | Next: <a href="Tutorial.html" accesskey="n" rel="next">Tutorial</a>, Previous: <a href="index.html" accesskey="p" rel="prev">Top</a>, Up: <a href="index.html" accesskey="u" rel="up">Top</a>   [<a href="index.html#SEC_Contents" title="Table of contents" rel="contents">Contents</a>][<a href="Concept-Index.html" title="Index" rel="index">Index</a>]</p> | ||
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