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Current fftw source
author Chris Cannam <cannam@all-day-breakfast.com>
date Tue, 18 Oct 2016 13:40:26 +0100
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cannam@127 25 <title>FFTW 3.3.5: One-dimensional distributions</title>
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cannam@127 71 <body lang="en" bgcolor="#FFFFFF" text="#000000" link="#0000FF" vlink="#800080" alink="#FF0000">
cannam@127 72 <a name="One_002ddimensional-distributions"></a>
cannam@127 73 <div class="header">
cannam@127 74 <p>
cannam@127 75 Previous: <a href="Transposed-distributions.html#Transposed-distributions" accesskey="p" rel="prev">Transposed distributions</a>, Up: <a href="MPI-Data-Distribution.html#MPI-Data-Distribution" accesskey="u" rel="up">MPI Data Distribution</a> &nbsp; [<a href="index.html#SEC_Contents" title="Table of contents" rel="contents">Contents</a>][<a href="Concept-Index.html#Concept-Index" title="Index" rel="index">Index</a>]</p>
cannam@127 76 </div>
cannam@127 77 <hr>
cannam@127 78 <a name="One_002ddimensional-distributions-1"></a>
cannam@127 79 <h4 class="subsection">6.4.4 One-dimensional distributions</h4>
cannam@127 80
cannam@127 81 <p>For one-dimensional distributed DFTs using FFTW, matters are slightly
cannam@127 82 more complicated because the data distribution is more closely tied to
cannam@127 83 how the algorithm works. In particular, you can no longer pass an
cannam@127 84 arbitrary block size and must accept FFTW&rsquo;s default; also, the block
cannam@127 85 sizes may be different for input and output. Also, the data
cannam@127 86 distribution depends on the flags and transform direction, in order
cannam@127 87 for forward and backward transforms to work correctly.
cannam@127 88 </p>
cannam@127 89 <div class="example">
cannam@127 90 <pre class="example">ptrdiff_t fftw_mpi_local_size_1d(ptrdiff_t n0, MPI_Comm comm,
cannam@127 91 int sign, unsigned flags,
cannam@127 92 ptrdiff_t *local_ni, ptrdiff_t *local_i_start,
cannam@127 93 ptrdiff_t *local_no, ptrdiff_t *local_o_start);
cannam@127 94 </pre></div>
cannam@127 95 <a name="index-fftw_005fmpi_005flocal_005fsize_005f1d"></a>
cannam@127 96
cannam@127 97 <p>This function computes the data distribution for a 1d transform of
cannam@127 98 size <code>n0</code> with the given transform <code>sign</code> and <code>flags</code>.
cannam@127 99 Both input and output data use block distributions. The input on the
cannam@127 100 current process will consist of <code>local_ni</code> numbers starting at
cannam@127 101 index <code>local_i_start</code>; e.g. if only a single process is used,
cannam@127 102 then <code>local_ni</code> will be <code>n0</code> and <code>local_i_start</code> will
cannam@127 103 be <code>0</code>. Similarly for the output, with <code>local_no</code> numbers
cannam@127 104 starting at index <code>local_o_start</code>. The return value of
cannam@127 105 <code>fftw_mpi_local_size_1d</code> will be the total number of elements to
cannam@127 106 allocate on the current process (which might be slightly larger than
cannam@127 107 the local size due to intermediate steps in the algorithm).
cannam@127 108 </p>
cannam@127 109 <p>As mentioned above (see <a href="Load-balancing.html#Load-balancing">Load balancing</a>), the data will be divided
cannam@127 110 equally among the processes if <code>n0</code> is divisible by the
cannam@127 111 <em>square</em> of the number of processes. In this case,
cannam@127 112 <code>local_ni</code> will equal <code>local_no</code>. Otherwise, they may be
cannam@127 113 different.
cannam@127 114 </p>
cannam@127 115 <p>For some applications, such as convolutions, the order of the output
cannam@127 116 data is irrelevant. In this case, performance can be improved by
cannam@127 117 specifying that the output data be stored in an FFTW-defined
cannam@127 118 &ldquo;scrambled&rdquo; format. (In particular, this is the analogue of
cannam@127 119 transposed output in the multidimensional case: scrambled output saves
cannam@127 120 a communications step.) If you pass <code>FFTW_MPI_SCRAMBLED_OUT</code> in
cannam@127 121 the flags, then the output is stored in this (undocumented) scrambled
cannam@127 122 order. Conversely, to perform the inverse transform of data in
cannam@127 123 scrambled order, pass the <code>FFTW_MPI_SCRAMBLED_IN</code> flag.
cannam@127 124 <a name="index-FFTW_005fMPI_005fSCRAMBLED_005fOUT"></a>
cannam@127 125 <a name="index-FFTW_005fMPI_005fSCRAMBLED_005fIN"></a>
cannam@127 126 </p>
cannam@127 127
cannam@127 128 <p>In MPI FFTW, only composite sizes <code>n0</code> can be parallelized; we
cannam@127 129 have not yet implemented a parallel algorithm for large prime sizes.
cannam@127 130 </p>
cannam@127 131 <hr>
cannam@127 132 <div class="header">
cannam@127 133 <p>
cannam@127 134 Previous: <a href="Transposed-distributions.html#Transposed-distributions" accesskey="p" rel="prev">Transposed distributions</a>, Up: <a href="MPI-Data-Distribution.html#MPI-Data-Distribution" accesskey="u" rel="up">MPI Data Distribution</a> &nbsp; [<a href="index.html#SEC_Contents" title="Table of contents" rel="contents">Contents</a>][<a href="Concept-Index.html#Concept-Index" title="Index" rel="index">Index</a>]</p>
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