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author Chris Cannam
date Fri, 07 Feb 2020 11:51:13 +0000
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Chris@42 72 <a name="Transposed-distributions"></a>
Chris@42 73 <div class="header">
Chris@42 74 <p>
Chris@42 75 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@42 76 </div>
Chris@42 77 <hr>
Chris@42 78 <a name="Transposed-distributions-1"></a>
Chris@42 79 <h4 class="subsection">6.4.3 Transposed distributions</h4>
Chris@42 80
Chris@42 81 <p>Internally, FFTW&rsquo;s MPI transform algorithms work by first computing
Chris@42 82 transforms of the data local to each process, then by globally
Chris@42 83 <em>transposing</em> the data in some fashion to redistribute the data
Chris@42 84 among the processes, transforming the new data local to each process,
Chris@42 85 and transposing back. For example, a two-dimensional <code>n0</code> by
Chris@42 86 <code>n1</code> array, distributed across the <code>n0</code> dimension, is
Chris@42 87 transformd by: (i) transforming the <code>n1</code> dimension, which are
Chris@42 88 local to each process; (ii) transposing to an <code>n1</code> by <code>n0</code>
Chris@42 89 array, distributed across the <code>n1</code> dimension; (iii) transforming
Chris@42 90 the <code>n0</code> dimension, which is now local to each process; (iv)
Chris@42 91 transposing back.
Chris@42 92 <a name="index-transpose"></a>
Chris@42 93 </p>
Chris@42 94
Chris@42 95 <p>However, in many applications it is acceptable to compute a
Chris@42 96 multidimensional DFT whose results are produced in transposed order
Chris@42 97 (e.g., <code>n1</code> by <code>n0</code> in two dimensions). This provides a
Chris@42 98 significant performance advantage, because it means that the final
Chris@42 99 transposition step can be omitted. FFTW supports this optimization,
Chris@42 100 which you specify by passing the flag <code>FFTW_MPI_TRANSPOSED_OUT</code>
Chris@42 101 to the planner routines. To compute the inverse transform of
Chris@42 102 transposed output, you specify <code>FFTW_MPI_TRANSPOSED_IN</code> to tell
Chris@42 103 it that the input is transposed. In this section, we explain how to
Chris@42 104 interpret the output format of such a transform.
Chris@42 105 <a name="index-FFTW_005fMPI_005fTRANSPOSED_005fOUT"></a>
Chris@42 106 <a name="index-FFTW_005fMPI_005fTRANSPOSED_005fIN"></a>
Chris@42 107 </p>
Chris@42 108
Chris@42 109 <p>Suppose you have are transforming multi-dimensional data with (at
Chris@42 110 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>. As always, it is distributed along
Chris@42 111 the first dimension n<sub>0</sub>. Now, if we compute its DFT with the
Chris@42 112 <code>FFTW_MPI_TRANSPOSED_OUT</code> flag, the resulting output data are stored
Chris@42 113 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@42 114 distributed along the n<sub>1</sub> dimension. Conversely, if we take the
Chris@42 115 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> data and transform it with the
Chris@42 116 <code>FFTW_MPI_TRANSPOSED_IN</code> flag, then the format goes back to the
Chris@42 117 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> array.
Chris@42 118 </p>
Chris@42 119 <p>There are two ways to find the portion of the transposed array that
Chris@42 120 resides on the current process. First, you can simply call the
Chris@42 121 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> (the
Chris@42 122 transposed dimensions). This would mean calling the &lsquo;<samp>local_size</samp>&rsquo;
Chris@42 123 function twice, once for the transposed and once for the
Chris@42 124 non-transposed dimensions. Alternatively, you can call one of the
Chris@42 125 &lsquo;<samp>local_size_transposed</samp>&rsquo; functions, which returns both the
Chris@42 126 non-transposed and transposed data distribution from a single call.
Chris@42 127 For example, for a 3d transform with transposed output (or input), you
Chris@42 128 might call:
Chris@42 129 </p>
Chris@42 130 <div class="example">
Chris@42 131 <pre class="example">ptrdiff_t fftw_mpi_local_size_3d_transposed(
Chris@42 132 ptrdiff_t n0, ptrdiff_t n1, ptrdiff_t n2, MPI_Comm comm,
Chris@42 133 ptrdiff_t *local_n0, ptrdiff_t *local_0_start,
Chris@42 134 ptrdiff_t *local_n1, ptrdiff_t *local_1_start);
Chris@42 135 </pre></div>
Chris@42 136 <a name="index-fftw_005fmpi_005flocal_005fsize_005f3d_005ftransposed"></a>
Chris@42 137
Chris@42 138 <p>Here, <code>local_n0</code> and <code>local_0_start</code> give the size and
Chris@42 139 starting index of the <code>n0</code> dimension for the
Chris@42 140 <em>non</em>-transposed data, as in the previous sections. For
Chris@42 141 <em>transposed</em> data (e.g. the output for
Chris@42 142 <code>FFTW_MPI_TRANSPOSED_OUT</code>), <code>local_n1</code> and
Chris@42 143 <code>local_1_start</code> give the size and starting index of the <code>n1</code>
Chris@42 144 dimension, which is the first dimension of the transposed data
Chris@42 145 (<code>n1</code> by <code>n0</code> by <code>n2</code>).
Chris@42 146 </p>
Chris@42 147 <p>(Note that <code>FFTW_MPI_TRANSPOSED_IN</code> is completely equivalent to
Chris@42 148 performing <code>FFTW_MPI_TRANSPOSED_OUT</code> and passing the first two
Chris@42 149 dimensions to the planner in reverse order, or vice versa. If you
Chris@42 150 pass <em>both</em> the <code>FFTW_MPI_TRANSPOSED_IN</code> and
Chris@42 151 <code>FFTW_MPI_TRANSPOSED_OUT</code> flags, it is equivalent to swapping the
Chris@42 152 first two dimensions passed to the planner and passing <em>neither</em>
Chris@42 153 flag.)
Chris@42 154 </p>
Chris@42 155 <hr>
Chris@42 156 <div class="header">
Chris@42 157 <p>
Chris@42 158 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@42 159 </div>
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