environment. In fact, almost all proxy apps provided by the `ExaScale
Project <https://proxyapps.exascaleproject.org/>`_ only require minor
modifications to `run on top of SMPI
-<https://github.com/simgrid/SMPI-proxy-apps/>`_.
+<https://framagit.org/simgrid/SMPI-proxy-apps>`_.
This setting permits to debug your MPI applications in a perfectly
reproducible setup, with no Heisenbugs. Enjoy the full Clairevoyance
This can be done with the following platform file, that considers the
simulated platform as a graph of hosts and network links.
-
+
.. literalinclude:: /tuto_smpi/3hosts.xml
:language: xml
The elements basic elements (with :ref:`pf_tag_host` and
:ref:`pf_tag_link`) are described first, and then the routes between
-any pair of hosts are explicitely given with :ref:`pf_tag_route`. Any
-host must be given a computational speed (in flops) while links must
-be given a latency (in seconds) and a bandwidth (in bytes per
-second). Note that you can write 1Gflops instead of 1000000000flops,
-and similar. Last point: :ref:`pf_tag_route`s are symmetrical by
-default (but this can be changed).
+any pair of hosts are explicitely given with :ref:`pf_tag_route`.
+
+Any host must be given a computational speed in flops while links must
+be given a latency and a bandwidth. You can write 1Gf for
+1,000,000,000 flops (full list of units in the reference guide of
+:ref:`pf_tag_host` and :ref:`pf_tag_link`).
+
+Routes defined with :ref:`pf_tag_route` are symmetrical by default,
+meaning that the list of traversed links from A to B is the same as
+from B to A. Explicitely define non-symmetrical routes if you prefer.
Cluster with a Crossbar
.......................
sudo apt install simgrid pajeng make gcc g++ gfortran vite
-For R analysis of the produced traces, you may want to install R,
-and the `pajengr<https://github.com/schnorr/pajengr#installation/>`_ package.
+For R analysis of the produced traces, you may want to install R,
+and the `pajengr <https://github.com/schnorr/pajengr#installation/>`_ package.
.. code-block:: shell
the documentation is up-to-date.
Lab 3: Execution Sampling on Matrix Multiplication example
--------------------------------
+----------------------------------------------------------
The second method to speed up simulations is to sample the computation
parts in the code. This means that the person doing the simulation
.. literalinclude:: /tuto_smpi/gemm_mpi.cpp
:language: c
:lines: 4-19
-
.. code-block:: shell
$ smpicc -O3 gemm_mpi.cpp -o gemm
$ time smpirun -np 16 -platform cluster_crossbar.xml -hostfile cluster_hostfile --cfg=smpi/display-timing:yes --cfg=smpi/running-power:1000000000 ./gemm
-
+
This should end quite quickly, as the size of each matrix is only 1000x1000.
But what happens if we want to simulate larger runs ?
Replace the size by 2000, 3000, and try again.
Lab 4: Memory folding on large allocations
--------------------------------
+------------------------------------------
Another issue that can be encountered when simulation with SMPI is lack of memory.
Indeed we are executing all MPI processes on a single node, which can lead to crashes.
You may also be interested in the `SMPI reference article
<https://hal.inria.fr/hal-01415484>`_ or these `introductory slides
-<http://simgrid.org/tutorials/simgrid-smpi-101.pdf>`_. The `SMPI
-reference documentation <SMPI_doc>`_ covers much more content than
+<http://simgrid.org/tutorials/simgrid-smpi-101.pdf>`_. The :ref:`SMPI
+reference documentation <SMPI_doc>` covers much more content than
this short tutorial.
Finally, we regularly use SimGrid in our teachings on MPI. This way,