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3 <title>Distributed-memory FFTW with MPI - FFTW 3.2alpha3</title>
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56
57 <h2 class="chapter">6 Distributed-memory FFTW with MPI</h2>
58
59 <p><a name="index-MPI-329"></a>
60 <a name="index-parallel-transform-330"></a>In this chapter we document the parallel FFTW routines for parallel
61 hardware supporting the MPI message-passing interface. Unlike the
62 shared-memory threads described in the previous chapter, MPI allows
63 you to use <em>distributed-memory</em> parallelism, where each CPU has
64 its own separate memory, and which can scale up to clusters of many
65 thousands of processors. This capability comes at a price, however:
66 each process only stores a <em>portion</em> of the data to be
67 transformed, which means that the data structures and
68 programming-interface are quite different from the serial or threads
69 versions of FFTW.
70 <a name="index-data-distribution-331"></a>
71 Distributed-memory parallelism is especially useful when you are
72 transforming arrays so large that they do not fit into the memory of a
73 single processor. The storage per-process required by FFTW's MPI
74 routines is proportional to the total array size divided by the number
75 of processes. Conversely, distributed-memory parallelism can easily
76 pose an unacceptably high communications overhead for small problems;
77 the threshold problem size for which parallelism becomes important
78 will depend on the precise problem you are interested in, your
79 hardware, and your MPI implementation.
80
81 <p>A note on terminology: in MPI, you divide the data among a set of
82 &ldquo;processes&rdquo; which each run in their own memory address space.
83 Generally, each process runs on a different physical processor, but
84 this is not required. A group of processes in MPI is described by an
85 opaque data structure called a &ldquo;communicator,&rdquo; the most common of
86 which is the predefined communicator <code>MPI_COMM_WORLD</code> which
87 refers to <em>all</em> processes. For more information on these and
88 other concepts common to all MPI programs, we refer the reader to the
89 documentation at <a href="http://www-unix.mcs.anl.gov/mpi/">the MPI home page</a>.
90 <a name="index-MPI-communicator-332"></a><a name="index-MPI_005fCOMM_005fWORLD-333"></a>
91 We assume in this chapter that the reader is familiar with the usage
92 of the serial (uniprocessor) FFTW, and focus only on the concepts new
93 to the MPI interface.
94
95 <ul class="menu">
96 <li><a accesskey="1" href="FFTW-MPI-Installation.html#FFTW-MPI-Installation">FFTW MPI Installation</a>
97 <li><a accesskey="2" href="Linking-and-Initializing-MPI-FFTW.html#Linking-and-Initializing-MPI-FFTW">Linking and Initializing MPI FFTW</a>
98 <li><a accesskey="3" href="Simple-MPI-example.html#Simple-MPI-example">Simple MPI example</a>
99 <li><a accesskey="4" href="MPI-data-distribution.html#MPI-data-distribution">MPI data distribution</a>
100 <li><a accesskey="5" href="Multi_002ddimensional-MPI-DFT-of-Real-Data.html#Multi_002ddimensional-MPI-DFT-of-Real-Data">Multi-dimensional MPI DFT of Real Data</a>
101 <li><a accesskey="6" href="Other-Multi_002ddimensional-Real_002ddata-MPI-Transforms.html#Other-Multi_002ddimensional-Real_002ddata-MPI-Transforms">Other Multi-dimensional Real-data MPI Transforms</a>
102 <li><a accesskey="7" href="FFTW-MPI-Transposes.html#FFTW-MPI-Transposes">FFTW MPI Transposes</a>
103 <li><a accesskey="8" href="FFTW-MPI-Wisdom.html#FFTW-MPI-Wisdom">FFTW MPI Wisdom</a>
104 <li><a accesskey="9" href="Avoiding-MPI-Deadlocks.html#Avoiding-MPI-Deadlocks">Avoiding MPI Deadlocks</a>
105 <li><a href="FFTW-MPI-Performance-Tips.html#FFTW-MPI-Performance-Tips">FFTW MPI Performance Tips</a>
106 <li><a href="Combining-MPI-and-Threads.html#Combining-MPI-and-Threads">Combining MPI and Threads</a>
107 <li><a href="FFTW-MPI-Reference.html#FFTW-MPI-Reference">FFTW MPI Reference</a>
108 </ul>
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