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author Chris Cannam <cannam@all-day-breakfast.com>
date Mon, 02 Mar 2020 14:03:47 +0000
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cannam@167 3 <!-- This manual is for FFTW
cannam@167 4 (version 3.3.8, 24 May 2018).
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cannam@167 6 Copyright (C) 2003 Matteo Frigo.
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cannam@167 8 Copyright (C) 2003 Massachusetts Institute of Technology.
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cannam@167 24 <head>
cannam@167 25 <title>FFTW 3.3.8: MPI Data Distribution</title>
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cannam@167 68 </head>
cannam@167 69
cannam@167 70 <body lang="en">
cannam@167 71 <a name="MPI-Data-Distribution"></a>
cannam@167 72 <div class="header">
cannam@167 73 <p>
cannam@167 74 Next: <a href="Multi_002ddimensional-MPI-DFTs-of-Real-Data.html#Multi_002ddimensional-MPI-DFTs-of-Real-Data" accesskey="n" rel="next">Multi-dimensional MPI DFTs of Real Data</a>, Previous: <a href="2d-MPI-example.html#g_t2d-MPI-example" accesskey="p" rel="prev">2d MPI example</a>, Up: <a href="Distributed_002dmemory-FFTW-with-MPI.html#Distributed_002dmemory-FFTW-with-MPI" accesskey="u" rel="up">Distributed-memory FFTW with MPI</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@167 75 </div>
cannam@167 76 <hr>
cannam@167 77 <a name="MPI-Data-Distribution-1"></a>
cannam@167 78 <h3 class="section">6.4 MPI Data Distribution</h3>
cannam@167 79 <a name="index-data-distribution-2"></a>
cannam@167 80
cannam@167 81 <p>The most important concept to understand in using FFTW&rsquo;s MPI interface
cannam@167 82 is the data distribution. With a serial or multithreaded FFT, all of
cannam@167 83 the inputs and outputs are stored as a single contiguous chunk of
cannam@167 84 memory. With a distributed-memory FFT, the inputs and outputs are
cannam@167 85 broken into disjoint blocks, one per process.
cannam@167 86 </p>
cannam@167 87 <p>In particular, FFTW uses a <em>1d block distribution</em> of the data,
cannam@167 88 distributed along the <em>first dimension</em>. For example, if you
cannam@167 89 want to perform a 100&nbsp;&times;&nbsp;200
cannam@167 90 complex DFT, distributed over 4
cannam@167 91 processes, each process will get a 25&nbsp;&times;&nbsp;200
cannam@167 92 slice of the data.
cannam@167 93 That is, process 0 will get rows 0 through 24, process 1 will get rows
cannam@167 94 25 through 49, process 2 will get rows 50 through 74, and process 3
cannam@167 95 will get rows 75 through 99. If you take the same array but
cannam@167 96 distribute it over 3 processes, then it is not evenly divisible so the
cannam@167 97 different processes will have unequal chunks. FFTW&rsquo;s default choice
cannam@167 98 in this case is to assign 34 rows to processes 0 and 1, and 32 rows to
cannam@167 99 process 2.
cannam@167 100 <a name="index-block-distribution"></a>
cannam@167 101 </p>
cannam@167 102
cannam@167 103 <p>FFTW provides several &lsquo;<samp>fftw_mpi_local_size</samp>&rsquo; routines that you can
cannam@167 104 call to find out what portion of an array is stored on the current
cannam@167 105 process. In most cases, you should use the default block sizes picked
cannam@167 106 by FFTW, but it is also possible to specify your own block size. For
cannam@167 107 example, with a 100&nbsp;&times;&nbsp;200
cannam@167 108 array on three processes, you can
cannam@167 109 tell FFTW to use a block size of 40, which would assign 40 rows to
cannam@167 110 processes 0 and 1, and 20 rows to process 2. FFTW&rsquo;s default is to
cannam@167 111 divide the data equally among the processes if possible, and as best
cannam@167 112 it can otherwise. The rows are always assigned in &ldquo;rank order,&rdquo;
cannam@167 113 i.e. process 0 gets the first block of rows, then process 1, and so
cannam@167 114 on. (You can change this by using <code>MPI_Comm_split</code> to create a
cannam@167 115 new communicator with re-ordered processes.) However, you should
cannam@167 116 always call the &lsquo;<samp>fftw_mpi_local_size</samp>&rsquo; routines, if possible,
cannam@167 117 rather than trying to predict FFTW&rsquo;s distribution choices.
cannam@167 118 </p>
cannam@167 119 <p>In particular, it is critical that you allocate the storage size that
cannam@167 120 is returned by &lsquo;<samp>fftw_mpi_local_size</samp>&rsquo;, which is <em>not</em>
cannam@167 121 necessarily the size of the local slice of the array. The reason is
cannam@167 122 that intermediate steps of FFTW&rsquo;s algorithms involve transposing the
cannam@167 123 array and redistributing the data, so at these intermediate steps FFTW
cannam@167 124 may require more local storage space (albeit always proportional to
cannam@167 125 the total size divided by the number of processes). The
cannam@167 126 &lsquo;<samp>fftw_mpi_local_size</samp>&rsquo; functions know how much storage is required
cannam@167 127 for these intermediate steps and tell you the correct amount to
cannam@167 128 allocate.
cannam@167 129 </p>
cannam@167 130 <table class="menu" border="0" cellspacing="0">
cannam@167 131 <tr><td align="left" valign="top">&bull; <a href="Basic-and-advanced-distribution-interfaces.html#Basic-and-advanced-distribution-interfaces" accesskey="1">Basic and advanced distribution interfaces</a>:</td><td>&nbsp;&nbsp;</td><td align="left" valign="top">
cannam@167 132 </td></tr>
cannam@167 133 <tr><td align="left" valign="top">&bull; <a href="Load-balancing.html#Load-balancing" accesskey="2">Load balancing</a>:</td><td>&nbsp;&nbsp;</td><td align="left" valign="top">
cannam@167 134 </td></tr>
cannam@167 135 <tr><td align="left" valign="top">&bull; <a href="Transposed-distributions.html#Transposed-distributions" accesskey="3">Transposed distributions</a>:</td><td>&nbsp;&nbsp;</td><td align="left" valign="top">
cannam@167 136 </td></tr>
cannam@167 137 <tr><td align="left" valign="top">&bull; <a href="One_002ddimensional-distributions.html#One_002ddimensional-distributions" accesskey="4">One-dimensional distributions</a>:</td><td>&nbsp;&nbsp;</td><td align="left" valign="top">
cannam@167 138 </td></tr>
cannam@167 139 </table>
cannam@167 140
cannam@167 141 <hr>
cannam@167 142 <div class="header">
cannam@167 143 <p>
cannam@167 144 Next: <a href="Multi_002ddimensional-MPI-DFTs-of-Real-Data.html#Multi_002ddimensional-MPI-DFTs-of-Real-Data" accesskey="n" rel="next">Multi-dimensional MPI DFTs of Real Data</a>, Previous: <a href="2d-MPI-example.html#g_t2d-MPI-example" accesskey="p" rel="prev">2d MPI example</a>, Up: <a href="Distributed_002dmemory-FFTW-with-MPI.html#Distributed_002dmemory-FFTW-with-MPI" accesskey="u" rel="up">Distributed-memory FFTW with MPI</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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