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|  | (version 3.3.10, 10 December 2020). | ||
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|  | Copyright (C) 2003 Matteo Frigo. | ||
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|  | <title>Transposed distributions (FFTW 3.3.10)</title> | ||
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|  | <span id="Transposed-distributions"></span><div class="header"> | ||
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|  | Next: <a href="One_002ddimensional-distributions.html" accesskey="n" rel="next">One-dimensional distributions</a>, Previous: <a href="Load-balancing.html" accesskey="p" rel="prev">Load balancing</a>, Up: <a href="MPI-Data-Distribution.html" accesskey="u" rel="up">MPI Data Distribution</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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|  | <span id="Transposed-distributions-1"></span><h4 class="subsection">6.4.3 Transposed distributions</h4> | ||
|  | 
 | ||
|  | <p>Internally, FFTW’s MPI transform algorithms work by first computing | ||
|  | transforms of the data local to each process, then by globally | ||
|  | <em>transposing</em> the data in some fashion to redistribute the data | ||
|  | among the processes, transforming the new data local to each process, | ||
|  | and transposing back.  For example, a two-dimensional <code>n0</code> by | ||
|  | <code>n1</code> array, distributed across the <code>n0</code> dimension, is | ||
|  | transformd by: (i) transforming the <code>n1</code> dimension, which are | ||
|  | local to each process; (ii) transposing to an <code>n1</code> by <code>n0</code> | ||
|  | array, distributed across the <code>n1</code> dimension; (iii) transforming | ||
|  | the <code>n0</code> dimension, which is now local to each process; (iv) | ||
|  | transposing back. | ||
|  | <span id="index-transpose"></span> | ||
|  | </p> | ||
|  | 
 | ||
|  | <p>However, in many applications it is acceptable to compute a | ||
|  | multidimensional DFT whose results are produced in transposed order | ||
|  | (e.g., <code>n1</code> by <code>n0</code> in two dimensions).  This provides a | ||
|  | significant performance advantage, because it means that the final | ||
|  | transposition step can be omitted.  FFTW supports this optimization, | ||
|  | which you specify by passing the flag <code>FFTW_MPI_TRANSPOSED_OUT</code> | ||
|  | to the planner routines.  To compute the inverse transform of | ||
|  | transposed output, you specify <code>FFTW_MPI_TRANSPOSED_IN</code> to tell | ||
|  | it that the input is transposed.  In this section, we explain how to | ||
|  | interpret the output format of such a transform. | ||
|  | <span id="index-FFTW_005fMPI_005fTRANSPOSED_005fOUT"></span> | ||
|  | <span id="index-FFTW_005fMPI_005fTRANSPOSED_005fIN"></span> | ||
|  | </p> | ||
|  | 
 | ||
|  | <p>Suppose you have are transforming multi-dimensional data with (at | ||
|  | least two) dimensions n<sub>0</sub> × n<sub>1</sub> × n<sub>2</sub> × … × n<sub>d-1</sub> | ||
|  | .  As always, it is distributed along | ||
|  | the first dimension n<sub>0</sub> | ||
|  | .  Now, if we compute its DFT with the | ||
|  | <code>FFTW_MPI_TRANSPOSED_OUT</code> flag, the resulting output data are stored | ||
|  | with the first <em>two</em> dimensions transposed: n<sub>1</sub> × n<sub>0</sub> × n<sub>2</sub> ×…× n<sub>d-1</sub> | ||
|  | , | ||
|  | distributed along the n<sub>1</sub> | ||
|  |  dimension.  Conversely, if we take the | ||
|  | n<sub>1</sub> × n<sub>0</sub> × n<sub>2</sub> ×…× n<sub>d-1</sub> | ||
|  |  data and transform it with the | ||
|  | <code>FFTW_MPI_TRANSPOSED_IN</code> flag, then the format goes back to the | ||
|  | original n<sub>0</sub> × n<sub>1</sub> × n<sub>2</sub> × … × n<sub>d-1</sub> | ||
|  |  array. | ||
|  | </p> | ||
|  | <p>There are two ways to find the portion of the transposed array that | ||
|  | resides on the current process.  First, you can simply call the | ||
|  | appropriate ‘<samp>local_size</samp>’ function, passing n<sub>1</sub> × n<sub>0</sub> × n<sub>2</sub> ×…× n<sub>d-1</sub> | ||
|  |  (the | ||
|  | transposed dimensions).  This would mean calling the ‘<samp>local_size</samp>’ | ||
|  | function twice, once for the transposed and once for the | ||
|  | non-transposed dimensions.  Alternatively, you can call one of the | ||
|  | ‘<samp>local_size_transposed</samp>’ functions, which returns both the | ||
|  | non-transposed and transposed data distribution from a single call. | ||
|  | For example, for a 3d transform with transposed output (or input), you | ||
|  | might call: | ||
|  | </p> | ||
|  | <div class="example"> | ||
|  | <pre class="example">ptrdiff_t fftw_mpi_local_size_3d_transposed( | ||
|  |                 ptrdiff_t n0, ptrdiff_t n1, ptrdiff_t n2, MPI_Comm comm, | ||
|  |                 ptrdiff_t *local_n0, ptrdiff_t *local_0_start, | ||
|  |                 ptrdiff_t *local_n1, ptrdiff_t *local_1_start); | ||
|  | </pre></div> | ||
|  | <span id="index-fftw_005fmpi_005flocal_005fsize_005f3d_005ftransposed"></span> | ||
|  | 
 | ||
|  | <p>Here, <code>local_n0</code> and <code>local_0_start</code> give the size and | ||
|  | starting index of the <code>n0</code> dimension for the | ||
|  | <em>non</em>-transposed data, as in the previous sections.  For | ||
|  | <em>transposed</em> data (e.g. the output for | ||
|  | <code>FFTW_MPI_TRANSPOSED_OUT</code>), <code>local_n1</code> and | ||
|  | <code>local_1_start</code> give the size and starting index of the <code>n1</code> | ||
|  | dimension, which is the first dimension of the transposed data | ||
|  | (<code>n1</code> by <code>n0</code> by <code>n2</code>). | ||
|  | </p> | ||
|  | <p>(Note that <code>FFTW_MPI_TRANSPOSED_IN</code> is completely equivalent to | ||
|  | performing <code>FFTW_MPI_TRANSPOSED_OUT</code> and passing the first two | ||
|  | dimensions to the planner in reverse order, or vice versa.  If you | ||
|  | pass <em>both</em> the <code>FFTW_MPI_TRANSPOSED_IN</code> and | ||
|  | <code>FFTW_MPI_TRANSPOSED_OUT</code> flags, it is equivalent to swapping the | ||
|  | first two dimensions passed to the planner and passing <em>neither</em> | ||
|  | flag.) | ||
|  | </p> | ||
|  | <hr> | ||
|  | <div class="header"> | ||
|  | <p> | ||
|  | Next: <a href="One_002ddimensional-distributions.html" accesskey="n" rel="next">One-dimensional distributions</a>, Previous: <a href="Load-balancing.html" accesskey="p" rel="prev">Load balancing</a>, Up: <a href="MPI-Data-Distribution.html" accesskey="u" rel="up">MPI Data Distribution</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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