bandwidth and a relatively low diameter. To model this in SimGrid,
pass a ``topology="FAT_TREE"`` attribute to your cluster. The
``topo_parameters=#levels;#downlinks;#uplinks;link count`` follows the
-semantic introduced in `Figure 1B of this article
-<http://webee.eedev.technion.ac.il/wp-content/uploads/2014/08/publication_574.pdf>`_.
+semantic introduced in `Figure 1(b) of this article
+<https://ece.technion.ac.il/wp-content/uploads/2021/01/publication_776.pdf>`_.
Here is the meaning of this example: ``2 ; 4,4 ; 1,2 ; 1,2``
.. code-block:: console
$ docker pull simgrid/tuto-smpi
- $ docker run -it --rm --name simgrid --volume ~/smpi-tutorial:/source/tutorial simgrid/tuto-smpi bash
+ $ docker run --user $UID:$GID -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
.. code-block:: console
$ smpicxx -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
+ $ time smpirun -np 16 -platform cluster_crossbar.xml -hostfile cluster_hostfile --cfg=smpi/display-timing:yes --cfg=smpi/host-speed: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?