+.. literalinclude:: ../../examples/platforms/cluster_fat_tree.xml
+ :language: xml
+ :lines: 1-3,10-
+
+
+Dragonfly Cluster
+.................
+
+This topology was introduced to further reduce the amount of links
+while maintaining a high bandwidth for local communications. To model
+this in SimGrid, pass a ``topology="DRAGONFLY"`` attribute to your
+cluster.
+
+.. literalinclude:: ../../examples/platforms/cluster_dragonfly.xml
+ :language: xml
+
+.. todo::
+
+ Add the image, and the documuentation of the topo_parameters.
+
+Final Word
+..........
+
+We only glanced over the abilities offered by SimGrid to describe the
+platform topology. Other networking zones model non-HPC platforms
+(such as wide area networks, ISP network comprising set-top boxes, or
+even your own routing schema). You can interconnect several networking
+zones in your platform to form a tree of zones, that is both a time-
+and memory-efficient representation of distributed platforms. Please
+head to the dedicated :ref:`documentation <platform>` for more
+information.
+
+Hands-on!
+---------
+
+It is time to start using SMPI yourself. For that, you first need to
+install it somehow, and then you will need a MPI application to play with.
+
+Using Docker
+............
+
+The easiest way to take the tutorial is to use the dedicated Docker
+image. Once you `installed Docker itself
+<https://docs.docker.com/install/>`_, simply do the following:
+
+.. code-block:: shell
+
+ docker pull simgrid/tuto-smpi
+ docker run -it --rm --name simgrid --volume ~/smpi-tutorial:/source/tutorial simgrid/tuto-smpi bash
+
+This will start a new container with all you need to take this
+tutorial, and create a ``smpi-tutorial`` directory in your home on
+your host machine that will be visible as ``/source/tutorial`` within the
+container. You can then edit the files you want with your favorite
+editor in ``~/smpi-tutorial``, and compile them within the
+container to enjoy the provided dependencies.
+
+.. warning::
+
+ Any change to the container out of ``/source/tutorial`` will be lost
+ when you log out of the container, so don't edit the other files!
+
+All needed dependencies are already installed in this container
+(SimGrid, the C/C++/Fortran compilers, make, pajeng and R). Vite being
+only optional in this tutorial, it is not installed to reduce the
+image size.
+
+The container also include the example platform files from the
+previous section as well as the source code of the NAS Parallel
+Benchmarks. These files are available under
+``/source/simgrid-template-smpi`` in the image. You should copy it to
+your working directory when you first log in:
+
+.. code-block:: shell
+
+ cp -r /source/simgrid-template-smpi/* /source/tutorial
+ cd /source/tutorial
+
+Using your Computer Natively
+............................
+
+To take the tutorial on your machine, you first need to :ref:`install
+SimGrid <install>`, the C/C++/Fortran compilers and also ``pajeng`` to
+visualize the traces. You may want to install `Vite
+<http://vite.gforge.inria.fr/>`_ to get a first glance at the
+traces. The provided code template requires make to compile. On
+Debian and Ubuntu for example, you can get them as follows:
+
+.. code-block:: shell
+
+ sudo apt install simgrid pajeng make gcc g++ gfortran vite
+
+To take this tutorial, you will also need the platform files from the
+previous section as well as the source code of the NAS Parallel
+Benchmarks. Just clone `this repository
+<https://framagit.org/simgrid/simgrid-template-smpi>`_ to get them all:
+
+.. code-block:: shell
+
+ git clone git@framagit.org:simgrid/simgrid-template-smpi.git
+ cd simgrid-template-smpi/
+
+If you struggle with the compilation, then you should double check
+your :ref:`SimGrid installation <install>`. On need, please refer to
+the :ref:`Troubleshooting your Project Setup
+<install_yours_troubleshooting>` section.
+
+Lab 0: Hello World
+------------------
+
+It is time to simulate your first MPI program. Use the simplistic
+example `roundtrip.c
+<https://framagit.org/simgrid/simgrid-template-smpi/raw/master/roundtrip.c?inline=false>`_
+that comes with the template.
+
+.. literalinclude:: /tuto_smpi/roundtrip.c
+ :language: c
+
+Compiling and Executing
+.......................
+
+Compiling the program is straightforward (double check your
+:ref:`SimGrid installation <install>` if you get an error message):
+
+
+.. code-block:: shell
+
+ $ smpicc -O3 roundtrip.c -o roundtrip
+
+
+Once compiled, you can simulate the execution of this program on 16
+nodes from the ``cluster_crossbar.xml`` platform as follows:
+
+.. code-block:: shell
+
+ $ smpirun -np 16 -platform cluster_crossbar.xml -hostfile cluster_hostfile ./roundtrip
+
+- The ``-np 16`` option, just like in regular MPI, specifies the
+ number of MPI processes to use.
+- The ``-hostfile cluster_hostfile`` option, just like in regular
+ MPI, specifies the host file. If you omit this option, ``smpirun``
+ will deploy the application on the first machines of your platform.
+- The ``-platform cluster_crossbar.xml`` option, **which doesn't exist
+ in regular MPI**, specifies the platform configuration to be
+ simulated.
+- At the end of the line, one finds the executable name and
+ command-line arguments (if any -- roundtrip does not expect any arguments).
+
+Feel free to tweak the content of the XML platform file and the
+program to see the effect on the simulated execution time. It may be
+easier to compare the executions with the extra option
+``--cfg=smpi/display_timing:yes``. Note that the simulation accounts
+for realistic network protocol effects and MPI implementation
+effects. As a result, you may see "unexpected behavior" like in the
+real world (e.g., sending a message 1 byte larger may lead to
+significant higher execution time).
+
+Lab 1: Visualizing LU
+---------------------
+
+We will now simulate a larger application: the LU benchmark of the NAS
+suite. The version provided in the code template was modified to
+compile with SMPI instead of the regular MPI. Compare the difference
+between the original ``config/make.def.template`` and the
+``config/make.def`` that was adapted to SMPI. We use ``smpiff`` and
+``smpicc`` as compilers, and don't pass any additional library.
+
+Now compile and execute the LU benchmark, class S (i.e., for `small
+data size
+<https://www.nas.nasa.gov/publications/npb_problem_sizes.html>`_) with
+4 nodes.
+
+.. code-block:: shell
+
+ $ make lu NPROCS=4 CLASS=S
+ (compilation logs)
+ $ smpirun -np 4 -platform ../cluster_backbone.xml bin/lu.S.4
+ (execution logs)
+
+To get a better understanding of what is going on, activate the
+vizualization tracing, and convert the produced trace for later
+use:
+
+.. code-block:: shell
+
+ smpirun -np 4 -platform ../cluster_backbone.xml -trace --cfg=tracing/filename:lu.S.4.trace bin/lu.S.4
+ pj_dump --ignore-incomplete-links lu.S.4.trace | grep State > lu.S.4.state.csv
+
+You can then produce a Gantt Chart with the following R chunk. You can
+either copy/paste it in a R session, or `turn it into a Rscript executable
+<https://swcarpentry.github.io/r-novice-inflammation/05-cmdline/>`_ to
+run it again and again.
+
+.. code-block:: R
+
+ library(ggplot2)
+
+ # Read the data
+ df_state = read.csv("lu.S.4.state.csv", header=F, strip.white=T)
+ names(df_state) = c("Type", "Rank", "Container", "Start", "End", "Duration", "Level", "State");
+ df_state = df_state[!(names(df_state) %in% c("Type","Container","Level"))]
+ df_state$Rank = as.numeric(gsub("rank-","",df_state$Rank))
+
+ # Draw the Gantt Chart
+ gc = ggplot(data=df_state) + geom_rect(aes(xmin=Start, xmax=End, ymin=Rank, ymax=Rank+1,fill=State))
+
+ # Produce the output
+ plot(gc)
+ dev.off()
+
+This produces a file called ``Rplots.pdf`` with the following
+content. You can find more visualization examples `online
+<http://simgrid.gforge.inria.fr/contrib/R_visualization.html>`_.
+
+.. image:: /tuto_smpi/img/lu.S.4.png
+ :align: center
+
+Lab 2: Tracing and Replay of LU
+-------------------------------
+
+Now compile and execute the LU benchmark, class A, with 32 nodes.
+
+.. code-block:: shell
+
+ $ make lu NPROCS=32 CLASS=A
+
+This takes several minutes to to simulate, because all code from all
+processes has to be really executed, and everything is serialized.
+
+SMPI provides several methods to speed things up. One of them is to
+capture a time independent trace of the running application, and
+replay it on a different platform with the same amount of nodes. The
+replay is much faster than live simulation, as the computations are
+skipped (the application must be network-dependent for this to work).
+
+You can even generate the trace during as live simulation, as follows:
+
+.. code-block:: shell
+
+ $ smpirun -trace-ti --cfg=tracing/filename:LU.A.32 -np 32 -platform ../cluster_backbone.xml bin/lu.A.32
+
+The produced trace is composed of a file ``LU.A.32`` and a folder
+``LU.A.32_files``. To replay this with SMPI, you need to first compile
+the provided ``smpi_replay.cpp`` file, that comes from
+`simgrid/examples/smpi/replay
+<https://framagit.org/simgrid/simgrid/tree/master/examples/smpi/replay>`_.
+
+.. code-block:: shell
+
+ $ smpicxx ../replay.cpp -O3 -o ../smpi_replay
+
+Afterward, you can replay your trace in SMPI as follows:
+
+ $ smpirun -np 32 -platform ../cluster_torus.xml -ext smpi_replay ../smpi_replay LU.A.32
+
+All the outputs are gone, as the application is not really simulated
+here. Its trace is simply replayed. But if you visualize the live
+simulation and the replay, you will see that the behavior is
+unchanged. The simulation does not run much faster on this very
+example, but this becomes very interesting when your application
+is computationally hungry.
+
+.. todo:: smpi_replay should be installed by SimGrid, and smpirun interface could be simplified here.
+
+Lab 3: Execution Sampling on EP
+-------------------------------
+
+The second method to speed up simulations is to sample the computation
+parts in the code. This means that the person doing the simulation
+needs to know the application and identify parts that are compute
+intensive and take time, while being regular enough not to ruin
+simulation accuracy. Furthermore there should not be any MPI calls
+inside such parts of the code.
+
+Use the EP benchmark, class B, 16 processes.
+
+.. todo:: write this section, and the following ones.
+
+Further Readings
+----------------
+
+We regularly use SimGrid in our teachings on MPI. This way, our
+student can experiment with platforms that they do not have access to,
+and the associated visualisation tools helps them to understand their
+work. The whole material is available online, in a separate project:
+the `SMPI CourseWare <https://simgrid.github.io/SMPI_CourseWare/>`_.
+