wiki:AnugaParallel

Version 25 (modified by steve, 12 years ago) (diff)

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INSTALLING anuga_parallel

Install anuga

First you should install the most uptodate version of the code. Follow the instructions to install Anuga on Ubuntu. By following those instructions you should end up with a download of the anuga_core code (which contains the sequential code (in the source/anuga directory) and the anuga_parallel code (in source/anuga_parallel)).

You should end up with a directory

/home/username/anuga_core

where username is of course your username on your machine.

Make sure you have setup your PYTHONPATH to point to the anuga source directory

For instance I have the following line in my .bashrc file

export PYTHONPATH=/home/username/anuga_core/source

At this stage you should have a working version of the sequential anuga program. I.e. you should be able to run command

python test_all.py

from the anuga_core directory and have your installation pass all the unit tests (well nearly all, as this is the development version and there are sometimes a few minor unit tests that fail).

Updating anuga_core

If you had already downloaded anuga_core then it is sensible to update to the most recent version of the code using the subversion update command. Run the following command from the anuga_core directory

svn update

and then

python compile_all.py
python test_all.py

This should update an old version to the most recent version.

Install anuga_parallel

Now to get anuga_parallel to work, we need to install some other packages first, in particular MPI for the parallel message passing and pypar a simple python wrapper of MPI.

MPI

Now you need to install MPI on your system. OPENMPI and MPICH2 are supported by pypar (see below) so both should be ok. But I tend to use mpich2.

So install mpich2 on your system via apt-get

sudo apt-get install mpich2

Make sure mpi works. You should be able to run a program in parallel. Something as simple as

mpirun -np 4 pwd

should produce the output of pwd 4 times.

pypar

We use pypar as the interface between mpi and python. The most recent version of PYPAR is available from http://code.google.com/p/pypar/ Use svn to get the most recent version of the code. The tarred version is a little old.

(There is also an old version on sourceforge, do not use that)

From your home directory run the command

svn checkout http://pypar.googlecode.com/svn/ pypar

This produces a directory

/home/username/pypar

Change to the /home/username/pypar/source directory, and then run the command

sudo python setup.py install

This should install pypar.

Fire up python and see if you can import pypar

You should obtain

>>> import pypar
Pypar (version 2.1.4) initialised MPI OK with 1 processors

Also make sure the pypar examples work

By the way, it is sometimes useful to fire up a new console to see if these installations work in a clean console.

pymetis

In the anuga_parallel directory there is a subdirectory pymetis.

Follow the instructions in README to install. Essentially just run make.

From the pymetis diectory run

make

From the pymetis directory, test using test_all.py, i.e. run

python test_all.py

Running anuga_parallel

You should now be ready to run some parallel anuga code. Go back to the anuga_parallel directory and run the tests

cd /home/username/anuga_core/source/anuga_parallel
python test_all.py

Hopefully that all works.

Example program

Run run_parallel_sw_merimbula.py

First just run it as a sequential program, via

python run_parallel_sw_merimbula.py

Then try a parallel run using a command like

mpirun -np 4 python run_parallel_sw_merimbula.py

That should run on 4 processors

You should look at the code in run_parallel_sw_merimbula.py

Essentially a fairly standard example, with the extra command

domain = distribute(domain)

which sets up all the parallel stuff.

Also for efficiency reasons we only setup the original full sequential mesh on processor 0, hence the statement

if myid == 0:
     domain = create_domain_from_file(mesh_filename)
     domain.set_quantity('stage', Set_Stage(x0, x1, 2.0))
else:
     domain = None

The output will be an sww file associated to each processor.

sww_merge

There is a script anuga/utilities/sww_merge.py which provides a function to merge sww files into one sww file for viewing with the anuga viewer.

Suppose your parallel code produced 3 sww files, domain_P3_0.sww domain_P3_1.sww and domain_P3_2.sww

The base name would be "domain" and the number of processors would be 3. To stitch these 3 files together either run sww_merge.py as a script with the command

python /home/username/anuga_core/source/anuga/utilities/sww_merge.py -f domain -np 3

or you can add a command of the form

domain.sww_merge()

at the end of your simulation script, if you want to keep the individual parallel sww files or

domain.sww_merge(delete_old=True)

(check out the script run_parallel_sw_merimbula.py which demos this). if you are happy for the individual sww files to be deleted after the merge operation.