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Vectorised Xcorr
author Geogaddi\David <d.m.ronan@qmul.ac.uk>
date Wed, 22 Jul 2015 15:28:00 +0100
parents 25bf17994ef1
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d@0 3 <title>One-dimensional distributions - FFTW 3.2alpha3</title>
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d@0 49 <a name="One-dimensional-distributions"></a>
d@0 50 <a name="One_002ddimensional-distributions"></a>
d@0 51 Previous:&nbsp;<a rel="previous" accesskey="p" href="Transposed-distributions.html#Transposed-distributions">Transposed distributions</a>,
d@0 52 Up:&nbsp;<a rel="up" accesskey="u" href="MPI-data-distribution.html#MPI-data-distribution">MPI data distribution</a>
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d@0 55
d@0 56 <h4 class="subsection">6.4.4 One-dimensional distributions</h4>
d@0 57
d@0 58 <p>For one-dimensional distributed DFTs using FFTW, matters are slightly
d@0 59 more complicated because the data distribution is more closely tied to
d@0 60 how the algorithm works. In particular, you can no longer pass an
d@0 61 arbitrary block size, and must accept FFTW's default, and the block
d@0 62 sizes may be different for input and output. Also, the data
d@0 63 distribution depends on the flags and transform direction, in order
d@0 64 for forward and backward transforms to work correctly.
d@0 65
d@0 66 <pre class="example"> ptrdiff_t fftw_mpi_local_size_1d(ptrdiff_t n0, MPI_Comm comm,
d@0 67 int sign, unsigned flags,
d@0 68 ptrdiff_t *local_ni, ptrdiff_t *local_i_start,
d@0 69 ptrdiff_t *local_no, ptrdiff_t *local_o_start);
d@0 70 </pre>
d@0 71 <p><a name="index-fftw_005fmpi_005flocal_005fsize_005f1d-363"></a>
d@0 72 This function computes the data distribution for a 1d transform of
d@0 73 size <code>n0</code> with the given transform <code>sign</code> and <code>flags</code>.
d@0 74 Both input and output data use block distributions. The input on the
d@0 75 current process will consist of <code>local_ni</code> numbers starting at
d@0 76 index <code>local_i_start</code>; e.g. if only a single process is used,
d@0 77 then <code>local_ni</code> will be <code>n0</code> and <code>local_i_start</code> will
d@0 78 be <code>0</code>. Similarly for the output, with <code>local_no</code> numbers
d@0 79 starting at index <code>local_o_start</code>. The return value of
d@0 80 <code>fftw_mpi_local_size_1d</code> will be the total number of elements to
d@0 81 allocate on the current process (which might be slightly larger than
d@0 82 the local size due to intermediate steps in the algorithm).
d@0 83
d@0 84 <p>As mentioned above (see <a href="Load-balancing.html#Load-balancing">Load balancing</a>), the data will be divided
d@0 85 equally among the processes if <code>n0</code> is divisible by the
d@0 86 <em>square</em> of the number of processes. In this case,
d@0 87 <code>local_ni</code> will equal <code>local_no</code>. Otherwise, they may be
d@0 88 different.
d@0 89
d@0 90 <p>For some applications, such as convolutions, the order of the output
d@0 91 data is irrelevant. In this case, performance can be improved by
d@0 92 specifying that the output data be stored in an FFTW-defined
d@0 93 &ldquo;scrambled&rdquo; format. (In particular, this is the analogue of
d@0 94 transposed output in the multidimensional case: scrambled output saves
d@0 95 a communications step.) If you pass <code>FFTW_MPI_SCRAMBLED_OUT</code> in
d@0 96 the flags, then the output is stored in this (undocumented) scrambled
d@0 97 order. Conversely, to perform the inverse transform of data in
d@0 98 scrambled order, pass the <code>FFTW_MPI_SCRAMBLED_IN</code> flag.
d@0 99 <a name="index-FFTW_005fMPI_005fSCRAMBLED_005fOUT-364"></a><a name="index-FFTW_005fMPI_005fSCRAMBLED_005fIN-365"></a>
d@0 100 In MPI FFTW, only composite sizes <code>n0</code> can be parallelized; we
d@0 101 have not yet implemented a parallel algorithm for large prime sizes.
d@0 102
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