Editing Parallel Computing (section)

==OpenMP and MPI==

===OpenMP (internal)===
[https://secure.wikimedia.org/wikipedia/en/wiki/OpenMP OpenMP] is a standard framework for parallel applications on '''shared-memory''' systems. It is supported by the latest versions of [http://gcc.gnu.org/ GCC] and by some other compilers.

To use OpenMP in your program, you do not need to add anything to your SConstruct. Just make sure the OMP libraries are installed on your system before you configure Madagascar, (or -- reinstall them and rerun the configuration command). Of course, you need to use the appropriate pragmas in your code. To find Madagascar programs that use OpenMP and that you can take as a model, run the following command:

<syntaxhighlight lang="bash">
grep "pragma omp" $RSFSRC/*/*/M*.c |\
awk -F ':' '{ print $1 }' |\
uniq |\
awk -F '/' '{ print $NF }' 
</syntaxhighlight>
On the last check (2014-02-09), 139 standalone programs (approximately 11% of Madagascar programs) were using OMP. Running a similar command in the directory <tt>$RSFSRC/api/c</tt> will yield a few library functions parallelized with OMP.

===OpenMP (external)===

To run on a multi-core shared-memory machine a data-parallel process that does not contain OpenMP calls, use <tt>sfomp</tt>. Thus, a call like
<syntaxhighlight lang="bash">
sfradon np=100 p0=0 dp=0.01 < inp.rsf > out.rsf
</syntaxhighlight>
becomes
<syntaxhighlight lang="bash">
sfomp sfradon np=100 p0=0 dp=0.01 < inp.rsf > out.rsf
</syntaxhighlight>
<tt>sfomp</tt> splits the input along the slowest axis (presumed to be data-parallel) and runs it through parallel threads. The number of threads is set by the <tt>OMP_NUM_THREADS</tt> environmental variable or (by default) by the number of available CPUs. For example,
<syntaxhighlight lang="bash">
export OMP_NUM_THREADS=number of threads
</syntaxhighlight>

===MPI (internal)===
[http://www.mcs.anl.gov/research/projects/mpi/ MPI] (Message-Passing Interface) is the dominant standard framework for parallel processing on different computer architectures including '''distributed-memory''' systems. Several MPI implementations (such as [http://www.open-mpi.org/ Open MPI] and [http://www.mcs.anl.gov/research/projects/mpich2/ MPICH2]) are available.

An example of compiling a program with <tt>mpicc</tt> and running it under <tt>mpirun</tt> can be found in [http://www.ahay.org/RSF/book/rsf/bash/mpi.html $RSFSRC/book/rsf/bash/mpi/SConstruct].  Note that Madagascar has a requirement that all internally-executing MPI programs must contain string 'mpi' in the program name as it is needed for SCons to switch to a mpi compiler such as mpicc.

===MPI (external)===
To parallelize a data-parallel task using MPI but without including MPI calls in your source code, try <tt>sfmpi</tt>, as follows:
<syntaxhighlight lang="bash">
mpirun -np 8 sfmpi sfradon np=100 p0=0 dp=0.01 input=inp.rsf output=out.rsf split=2
</syntaxhighlight>
where the argument after <tt>-np</tt> specifies the number of processors involved. sfmpi will use this number to split the input along the slowest axis (presumed to be data-parallel) and to run it through parallel threads. Notice that the keywords <tt>input</tt>, <tt>output</tt>, and <tt>split</tt> are specific to <tt>sfmpi</tt>. They are used to specify the standard input and output streams of your program and the input axis to split.

Some older MPI implementations do not support system calls implemented in <tt>sfmpi</tt> and therefore may not support this feature.

===MPI + OpenMP (both external)===

It is possible to combine the advantages of shared-memory and distributed-memory architectures by using OpenMP and MPI together.
<syntaxhighlight lang="bash">
mpirun -np 32 sfmpi sfomp sfradon np=100 p0=0 dp=0.01 input=inp.rsf output=out.rsf
</syntaxhighlight>
will distribute the job on 32 nodes and split it again on each node using shared-memory threads.