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Add FFTW 3.3.8 source, and a Linux build
author Chris Cannam
date Tue, 19 Nov 2019 14:52:55 +0000
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Chris@82 25 <title>FFTW 3.3.8: Transposed distributions</title>
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Chris@82 71 <a name="Transposed-distributions"></a>
Chris@82 72 <div class="header">
Chris@82 73 <p>
Chris@82 74 Next: <a href="One_002ddimensional-distributions.html#One_002ddimensional-distributions" accesskey="n" rel="next">One-dimensional distributions</a>, Previous: <a href="Load-balancing.html#Load-balancing" accesskey="p" rel="prev">Load balancing</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>
Chris@82 75 </div>
Chris@82 76 <hr>
Chris@82 77 <a name="Transposed-distributions-1"></a>
Chris@82 78 <h4 class="subsection">6.4.3 Transposed distributions</h4>
Chris@82 79
Chris@82 80 <p>Internally, FFTW&rsquo;s MPI transform algorithms work by first computing
Chris@82 81 transforms of the data local to each process, then by globally
Chris@82 82 <em>transposing</em> the data in some fashion to redistribute the data
Chris@82 83 among the processes, transforming the new data local to each process,
Chris@82 84 and transposing back. For example, a two-dimensional <code>n0</code> by
Chris@82 85 <code>n1</code> array, distributed across the <code>n0</code> dimension, is
Chris@82 86 transformd by: (i) transforming the <code>n1</code> dimension, which are
Chris@82 87 local to each process; (ii) transposing to an <code>n1</code> by <code>n0</code>
Chris@82 88 array, distributed across the <code>n1</code> dimension; (iii) transforming
Chris@82 89 the <code>n0</code> dimension, which is now local to each process; (iv)
Chris@82 90 transposing back.
Chris@82 91 <a name="index-transpose"></a>
Chris@82 92 </p>
Chris@82 93
Chris@82 94 <p>However, in many applications it is acceptable to compute a
Chris@82 95 multidimensional DFT whose results are produced in transposed order
Chris@82 96 (e.g., <code>n1</code> by <code>n0</code> in two dimensions). This provides a
Chris@82 97 significant performance advantage, because it means that the final
Chris@82 98 transposition step can be omitted. FFTW supports this optimization,
Chris@82 99 which you specify by passing the flag <code>FFTW_MPI_TRANSPOSED_OUT</code>
Chris@82 100 to the planner routines. To compute the inverse transform of
Chris@82 101 transposed output, you specify <code>FFTW_MPI_TRANSPOSED_IN</code> to tell
Chris@82 102 it that the input is transposed. In this section, we explain how to
Chris@82 103 interpret the output format of such a transform.
Chris@82 104 <a name="index-FFTW_005fMPI_005fTRANSPOSED_005fOUT"></a>
Chris@82 105 <a name="index-FFTW_005fMPI_005fTRANSPOSED_005fIN"></a>
Chris@82 106 </p>
Chris@82 107
Chris@82 108 <p>Suppose you have are transforming multi-dimensional data with (at
Chris@82 109 least two) dimensions n<sub>0</sub>&nbsp;&times;&nbsp;n<sub>1</sub>&nbsp;&times;&nbsp;n<sub>2</sub>&nbsp;&times;&nbsp;&hellip;&nbsp;&times;&nbsp;n<sub>d-1</sub>
Chris@82 110 . As always, it is distributed along
Chris@82 111 the first dimension n<sub>0</sub>
Chris@82 112 . Now, if we compute its DFT with the
Chris@82 113 <code>FFTW_MPI_TRANSPOSED_OUT</code> flag, the resulting output data are stored
Chris@82 114 with the first <em>two</em> dimensions transposed: n<sub>1</sub>&nbsp;&times;&nbsp;n<sub>0</sub>&nbsp;&times;&nbsp;n<sub>2</sub>&nbsp;&times;&hellip;&times;&nbsp;n<sub>d-1</sub>
Chris@82 115 ,
Chris@82 116 distributed along the n<sub>1</sub>
Chris@82 117 dimension. Conversely, if we take the
Chris@82 118 n<sub>1</sub>&nbsp;&times;&nbsp;n<sub>0</sub>&nbsp;&times;&nbsp;n<sub>2</sub>&nbsp;&times;&hellip;&times;&nbsp;n<sub>d-1</sub>
Chris@82 119 data and transform it with the
Chris@82 120 <code>FFTW_MPI_TRANSPOSED_IN</code> flag, then the format goes back to the
Chris@82 121 original n<sub>0</sub>&nbsp;&times;&nbsp;n<sub>1</sub>&nbsp;&times;&nbsp;n<sub>2</sub>&nbsp;&times;&nbsp;&hellip;&nbsp;&times;&nbsp;n<sub>d-1</sub>
Chris@82 122 array.
Chris@82 123 </p>
Chris@82 124 <p>There are two ways to find the portion of the transposed array that
Chris@82 125 resides on the current process. First, you can simply call the
Chris@82 126 appropriate &lsquo;<samp>local_size</samp>&rsquo; function, passing n<sub>1</sub>&nbsp;&times;&nbsp;n<sub>0</sub>&nbsp;&times;&nbsp;n<sub>2</sub>&nbsp;&times;&hellip;&times;&nbsp;n<sub>d-1</sub>
Chris@82 127 (the
Chris@82 128 transposed dimensions). This would mean calling the &lsquo;<samp>local_size</samp>&rsquo;
Chris@82 129 function twice, once for the transposed and once for the
Chris@82 130 non-transposed dimensions. Alternatively, you can call one of the
Chris@82 131 &lsquo;<samp>local_size_transposed</samp>&rsquo; functions, which returns both the
Chris@82 132 non-transposed and transposed data distribution from a single call.
Chris@82 133 For example, for a 3d transform with transposed output (or input), you
Chris@82 134 might call:
Chris@82 135 </p>
Chris@82 136 <div class="example">
Chris@82 137 <pre class="example">ptrdiff_t fftw_mpi_local_size_3d_transposed(
Chris@82 138 ptrdiff_t n0, ptrdiff_t n1, ptrdiff_t n2, MPI_Comm comm,
Chris@82 139 ptrdiff_t *local_n0, ptrdiff_t *local_0_start,
Chris@82 140 ptrdiff_t *local_n1, ptrdiff_t *local_1_start);
Chris@82 141 </pre></div>
Chris@82 142 <a name="index-fftw_005fmpi_005flocal_005fsize_005f3d_005ftransposed"></a>
Chris@82 143
Chris@82 144 <p>Here, <code>local_n0</code> and <code>local_0_start</code> give the size and
Chris@82 145 starting index of the <code>n0</code> dimension for the
Chris@82 146 <em>non</em>-transposed data, as in the previous sections. For
Chris@82 147 <em>transposed</em> data (e.g. the output for
Chris@82 148 <code>FFTW_MPI_TRANSPOSED_OUT</code>), <code>local_n1</code> and
Chris@82 149 <code>local_1_start</code> give the size and starting index of the <code>n1</code>
Chris@82 150 dimension, which is the first dimension of the transposed data
Chris@82 151 (<code>n1</code> by <code>n0</code> by <code>n2</code>).
Chris@82 152 </p>
Chris@82 153 <p>(Note that <code>FFTW_MPI_TRANSPOSED_IN</code> is completely equivalent to
Chris@82 154 performing <code>FFTW_MPI_TRANSPOSED_OUT</code> and passing the first two
Chris@82 155 dimensions to the planner in reverse order, or vice versa. If you
Chris@82 156 pass <em>both</em> the <code>FFTW_MPI_TRANSPOSED_IN</code> and
Chris@82 157 <code>FFTW_MPI_TRANSPOSED_OUT</code> flags, it is equivalent to swapping the
Chris@82 158 first two dimensions passed to the planner and passing <em>neither</em>
Chris@82 159 flag.)
Chris@82 160 </p>
Chris@82 161 <hr>
Chris@82 162 <div class="header">
Chris@82 163 <p>
Chris@82 164 Next: <a href="One_002ddimensional-distributions.html#One_002ddimensional-distributions" accesskey="n" rel="next">One-dimensional distributions</a>, Previous: <a href="Load-balancing.html#Load-balancing" accesskey="p" rel="prev">Load balancing</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>
Chris@82 165 </div>
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