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			151 lines
		
	
	
		
			8.2 KiB
		
	
	
	
		
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<!-- This manual is for FFTW
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(version 3.3.10, 10 December 2020).
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Copyright (C) 2003 Matteo Frigo.
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Copyright (C) 2003 Massachusetts Institute of Technology.
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Permission is granted to make and distribute verbatim copies of this
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Permission is granted to copy and distribute modified versions of this
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<title>Distributed-memory FFTW with MPI (FFTW 3.3.10)</title>
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<link href="FFTW-MPI-Installation.html" rel="next" title="FFTW MPI Installation">
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<span id="Distributed_002dmemory-FFTW-with-MPI"></span><div class="header">
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<p>
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Next: <a href="Calling-FFTW-from-Modern-Fortran.html" accesskey="n" rel="next">Calling FFTW from Modern Fortran</a>, Previous: <a href="Multi_002dthreaded-FFTW.html" accesskey="p" rel="prev">Multi-threaded FFTW</a>, Up: <a href="index.html" accesskey="u" rel="up">Top</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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<hr>
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<span id="Distributed_002dmemory-FFTW-with-MPI-1"></span><h2 class="chapter">6 Distributed-memory FFTW with MPI</h2>
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<span id="index-MPI"></span>
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<span id="index-parallel-transform-1"></span>
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<p>In this chapter we document the parallel FFTW routines for parallel
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systems supporting the MPI message-passing interface.  Unlike the
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shared-memory threads described in the previous chapter, MPI allows
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you to use <em>distributed-memory</em> parallelism, where each CPU has
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its own separate memory, and which can scale up to clusters of many
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thousands of processors.  This capability comes at a price, however:
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each process only stores a <em>portion</em> of the data to be
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transformed, which means that the data structures and
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programming-interface are quite different from the serial or threads
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versions of FFTW.
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<span id="index-data-distribution"></span>
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</p>
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<p>Distributed-memory parallelism is especially useful when you are
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transforming arrays so large that they do not fit into the memory of a
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single processor.  The storage per-process required by FFTW’s MPI
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routines is proportional to the total array size divided by the number
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of processes.  Conversely, distributed-memory parallelism can easily
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pose an unacceptably high communications overhead for small problems;
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the threshold problem size for which parallelism becomes advantageous
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will depend on the precise problem you are interested in, your
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hardware, and your MPI implementation.
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</p>
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<p>A note on terminology: in MPI, you divide the data among a set of
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“processes” which each run in their own memory address space.
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Generally, each process runs on a different physical processor, but
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this is not required.  A set of processes in MPI is described by an
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opaque data structure called a “communicator,” the most common of
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which is the predefined communicator <code>MPI_COMM_WORLD</code> which
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refers to <em>all</em> processes.  For more information on these and
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other concepts common to all MPI programs, we refer the reader to the
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documentation at <a href="http://www.mcs.anl.gov/research/projects/mpi/">the MPI home
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page</a>.
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<span id="index-MPI-communicator"></span>
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<span id="index-MPI_005fCOMM_005fWORLD"></span>
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</p>
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<p>We assume in this chapter that the reader is familiar with the usage
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of the serial (uniprocessor) FFTW, and focus only on the concepts new
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to the MPI interface.
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</p>
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<table class="menu" border="0" cellspacing="0">
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<tr><td align="left" valign="top">• <a href="FFTW-MPI-Installation.html" accesskey="1">FFTW MPI Installation</a></td><td>  </td><td align="left" valign="top">
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</td></tr>
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<tr><td align="left" valign="top">• <a href="Linking-and-Initializing-MPI-FFTW.html" accesskey="2">Linking and Initializing MPI FFTW</a></td><td>  </td><td align="left" valign="top">
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</td></tr>
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<tr><td align="left" valign="top">• <a href="2d-MPI-example.html" accesskey="3">2d MPI example</a></td><td>  </td><td align="left" valign="top">
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</td></tr>
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<tr><td align="left" valign="top">• <a href="MPI-Data-Distribution.html" accesskey="4">MPI Data Distribution</a></td><td>  </td><td align="left" valign="top">
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</td></tr>
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<tr><td align="left" valign="top">• <a href="Multi_002ddimensional-MPI-DFTs-of-Real-Data.html" accesskey="5">Multi-dimensional MPI DFTs of Real Data</a></td><td>  </td><td align="left" valign="top">
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</td></tr>
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<tr><td align="left" valign="top">• <a href="Other-Multi_002ddimensional-Real_002ddata-MPI-Transforms.html" accesskey="6">Other Multi-dimensional Real-data MPI Transforms</a></td><td>  </td><td align="left" valign="top">
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</td></tr>
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<tr><td align="left" valign="top">• <a href="FFTW-MPI-Transposes.html" accesskey="7">FFTW MPI Transposes</a></td><td>  </td><td align="left" valign="top">
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</td></tr>
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<tr><td align="left" valign="top">• <a href="FFTW-MPI-Wisdom.html" accesskey="8">FFTW MPI Wisdom</a></td><td>  </td><td align="left" valign="top">
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</td></tr>
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<tr><td align="left" valign="top">• <a href="Avoiding-MPI-Deadlocks.html" accesskey="9">Avoiding MPI Deadlocks</a></td><td>  </td><td align="left" valign="top">
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</td></tr>
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<tr><td align="left" valign="top">• <a href="FFTW-MPI-Performance-Tips.html">FFTW MPI Performance Tips</a></td><td>  </td><td align="left" valign="top">
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</td></tr>
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<tr><td align="left" valign="top">• <a href="Combining-MPI-and-Threads.html">Combining MPI and Threads</a></td><td>  </td><td align="left" valign="top">
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</td></tr>
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<tr><td align="left" valign="top">• <a href="FFTW-MPI-Reference.html">FFTW MPI Reference</a></td><td>  </td><td align="left" valign="top">
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</td></tr>
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<tr><td align="left" valign="top">• <a href="FFTW-MPI-Fortran-Interface.html">FFTW MPI Fortran Interface</a></td><td>  </td><td align="left" valign="top">
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</td></tr>
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</table>
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<hr>
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<div class="header">
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<p>
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Next: <a href="Calling-FFTW-from-Modern-Fortran.html" accesskey="n" rel="next">Calling FFTW from Modern Fortran</a>, Previous: <a href="Multi_002dthreaded-FFTW.html" accesskey="p" rel="prev">Multi-threaded FFTW</a>, Up: <a href="index.html" accesskey="u" rel="up">Top</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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