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author Chris Cannam
date Tue, 18 Oct 2016 13:40:26 +0100
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3 <!-- This manual is for FFTW
4 (version 3.3.5, 30 July 2016).
5
6 Copyright (C) 2003 Matteo Frigo.
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8 Copyright (C) 2003 Massachusetts Institute of Technology.
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25 <title>FFTW 3.3.5: 2d MPI example</title>
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35 <link href="index.html#SEC_Contents" rel="contents" title="Table of Contents">
36 <link href="Distributed_002dmemory-FFTW-with-MPI.html#Distributed_002dmemory-FFTW-with-MPI" rel="up" title="Distributed-memory FFTW with MPI">
37 <link href="MPI-Data-Distribution.html#MPI-Data-Distribution" rel="next" title="MPI Data Distribution">
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72 <a name="g_t2d-MPI-example"></a>
73 <div class="header">
74 <p>
75 Next: <a href="MPI-Data-Distribution.html#MPI-Data-Distribution" accesskey="n" rel="next">MPI Data Distribution</a>, Previous: <a href="Linking-and-Initializing-MPI-FFTW.html#Linking-and-Initializing-MPI-FFTW" accesskey="p" rel="prev">Linking and Initializing MPI FFTW</a>, Up: <a href="Distributed_002dmemory-FFTW-with-MPI.html#Distributed_002dmemory-FFTW-with-MPI" accesskey="u" rel="up">Distributed-memory FFTW with MPI</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>
76 </div>
77 <hr>
78 <a name="g_t2d-MPI-example-1"></a>
79 <h3 class="section">6.3 2d MPI example</h3>
80
81 <p>Before we document the FFTW MPI interface in detail, we begin with a
82 simple example outlining how one would perform a two-dimensional
83 <code>N0</code> by <code>N1</code> complex DFT.
84 </p>
85 <div class="example">
86 <pre class="example">#include &lt;fftw3-mpi.h&gt;
87
88 int main(int argc, char **argv)
89 {
90 const ptrdiff_t N0 = ..., N1 = ...;
91 fftw_plan plan;
92 fftw_complex *data;
93 ptrdiff_t alloc_local, local_n0, local_0_start, i, j;
94
95 MPI_Init(&amp;argc, &amp;argv);
96 fftw_mpi_init();
97
98 /* <span class="roman">get local data size and allocate</span> */
99 alloc_local = fftw_mpi_local_size_2d(N0, N1, MPI_COMM_WORLD,
100 &amp;local_n0, &amp;local_0_start);
101 data = fftw_alloc_complex(alloc_local);
102
103 /* <span class="roman">create plan for in-place forward DFT</span> */
104 plan = fftw_mpi_plan_dft_2d(N0, N1, data, data, MPI_COMM_WORLD,
105 FFTW_FORWARD, FFTW_ESTIMATE);
106
107 /* <span class="roman">initialize data to some function</span> my_function(x,y) */
108 for (i = 0; i &lt; local_n0; ++i) for (j = 0; j &lt; N1; ++j)
109 data[i*N1 + j] = my_function(local_0_start + i, j);
110
111 /* <span class="roman">compute transforms, in-place, as many times as desired</span> */
112 fftw_execute(plan);
113
114 fftw_destroy_plan(plan);
115
116 MPI_Finalize();
117 }
118 </pre></div>
119
120 <p>As can be seen above, the MPI interface follows the same basic style
121 of allocate/plan/execute/destroy as the serial FFTW routines. All of
122 the MPI-specific routines are prefixed with &lsquo;<samp>fftw_mpi_</samp>&rsquo; instead
123 of &lsquo;<samp>fftw_</samp>&rsquo;. There are a few important differences, however:
124 </p>
125 <p>First, we must call <code>fftw_mpi_init()</code> after calling
126 <code>MPI_Init</code> (required in all MPI programs) and before calling any
127 other &lsquo;<samp>fftw_mpi_</samp>&rsquo; routine.
128 <a name="index-MPI_005fInit"></a>
129 <a name="index-fftw_005fmpi_005finit-1"></a>
130 </p>
131
132 <p>Second, when we create the plan with <code>fftw_mpi_plan_dft_2d</code>,
133 analogous to <code>fftw_plan_dft_2d</code>, we pass an additional argument:
134 the communicator, indicating which processes will participate in the
135 transform (here <code>MPI_COMM_WORLD</code>, indicating all processes).
136 Whenever you create, execute, or destroy a plan for an MPI transform,
137 you must call the corresponding FFTW routine on <em>all</em> processes
138 in the communicator for that transform. (That is, these are
139 <em>collective</em> calls.) Note that the plan for the MPI transform
140 uses the standard <code>fftw_execute</code> and <code>fftw_destroy</code> routines
141 (on the other hand, there are MPI-specific new-array execute functions
142 documented below).
143 <a name="index-collective-function"></a>
144 <a name="index-fftw_005fmpi_005fplan_005fdft_005f2d"></a>
145 <a name="index-MPI_005fCOMM_005fWORLD-1"></a>
146 </p>
147
148 <p>Third, all of the FFTW MPI routines take <code>ptrdiff_t</code> arguments
149 instead of <code>int</code> as for the serial FFTW. <code>ptrdiff_t</code> is a
150 standard C integer type which is (at least) 32 bits wide on a 32-bit
151 machine and 64 bits wide on a 64-bit machine. This is to make it easy
152 to specify very large parallel transforms on a 64-bit machine. (You
153 can specify 64-bit transform sizes in the serial FFTW, too, but only
154 by using the &lsquo;<samp>guru64</samp>&rsquo; planner interface. See <a href="64_002dbit-Guru-Interface.html#g_t64_002dbit-Guru-Interface">64-bit Guru Interface</a>.)
155 <a name="index-ptrdiff_005ft-1"></a>
156 <a name="index-64_002dbit-architecture-1"></a>
157 </p>
158
159 <p>Fourth, and most importantly, you don&rsquo;t allocate the entire
160 two-dimensional array on each process. Instead, you call
161 <code>fftw_mpi_local_size_2d</code> to find out what <em>portion</em> of the
162 array resides on each processor, and how much space to allocate.
163 Here, the portion of the array on each process is a <code>local_n0</code> by
164 <code>N1</code> slice of the total array, starting at index
165 <code>local_0_start</code>. The total number of <code>fftw_complex</code> numbers
166 to allocate is given by the <code>alloc_local</code> return value, which
167 <em>may</em> be greater than <code>local_n0 * N1</code> (in case some
168 intermediate calculations require additional storage). The data
169 distribution in FFTW&rsquo;s MPI interface is described in more detail by
170 the next section.
171 <a name="index-fftw_005fmpi_005flocal_005fsize_005f2d"></a>
172 <a name="index-data-distribution-1"></a>
173 </p>
174
175 <p>Given the portion of the array that resides on the local process, it
176 is straightforward to initialize the data (here to a function
177 <code>myfunction</code>) and otherwise manipulate it. Of course, at the end
178 of the program you may want to output the data somehow, but
179 synchronizing this output is up to you and is beyond the scope of this
180 manual. (One good way to output a large multi-dimensional distributed
181 array in MPI to a portable binary file is to use the free HDF5
182 library; see the <a href="http://www.hdfgroup.org/">HDF home page</a>.)
183 <a name="index-HDF5"></a>
184 <a name="index-MPI-I_002fO"></a>
185 </p>
186 <hr>
187 <div class="header">
188 <p>
189 Next: <a href="MPI-Data-Distribution.html#MPI-Data-Distribution" accesskey="n" rel="next">MPI Data Distribution</a>, Previous: <a href="Linking-and-Initializing-MPI-FFTW.html#Linking-and-Initializing-MPI-FFTW" accesskey="p" rel="prev">Linking and Initializing MPI FFTW</a>, Up: <a href="Distributed_002dmemory-FFTW-with-MPI.html#Distributed_002dmemory-FFTW-with-MPI" accesskey="u" rel="up">Distributed-memory FFTW with MPI</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>
190 </div>
191
192
193
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195 </html>