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3 <title>FFTW MPI Performance Tips - FFTW 3.3.3</title>
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51 Next:&nbsp;<a rel="next" accesskey="n" href="Combining-MPI-and-Threads.html#Combining-MPI-and-Threads">Combining MPI and Threads</a>,
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56
57 <h3 class="section">6.10 FFTW MPI Performance Tips</h3>
58
59 <p>In this section, we collect a few tips on getting the best performance
60 out of FFTW's MPI transforms.
61
62 <p>First, because of the 1d block distribution, FFTW's parallelization is
63 currently limited by the size of the first dimension.
64 (Multidimensional block distributions may be supported by a future
65 version.) More generally, you should ideally arrange the dimensions so
66 that FFTW can divide them equally among the processes. See <a href="Load-balancing.html#Load-balancing">Load balancing</a>.
67 <a name="index-block-distribution-423"></a><a name="index-load-balancing-424"></a>
68
69 <p>Second, if it is not too inconvenient, you should consider working
70 with transposed output for multidimensional plans, as this saves a
71 considerable amount of communications. See <a href="Transposed-distributions.html#Transposed-distributions">Transposed distributions</a>.
72 <a name="index-transpose-425"></a>
73
74 <p>Third, the fastest choices are generally either an in-place transform
75 or an out-of-place transform with the <code>FFTW_DESTROY_INPUT</code> flag
76 (which allows the input array to be used as scratch space). In-place
77 is especially beneficial if the amount of data per process is large.
78 <a name="index-FFTW_005fDESTROY_005fINPUT-426"></a>
79
80 <p>Fourth, if you have multiple arrays to transform at once, rather than
81 calling FFTW's MPI transforms several times it usually seems to be
82 faster to interleave the data and use the advanced interface. (This
83 groups the communications together instead of requiring separate
84 messages for each transform.)
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