command-line arguments (if any -- roundtrip does not expect any arguments).
Feel free to tweak the content of the XML platform file and the
-prorgam to see the effect on the simulated execution time. 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).
+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
---------------------
``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 A (i.e., for small
-data size) with 4 nodes.
+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=A
+ $ make lu NPROCS=4 CLASS=S
(compilation logs)
- $ smpirun -np 4 -platform ../cluster_backbone.xml bin/lu.A.4
+ $ 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
.. code-block:: shell
- smpirun -np 4 -platform ../cluster_backbone.xml -trace --cfg=tracing/filename:lu.A.4.trace bin/lu.A.4
- pj_dump --ignore-incomplete-links lu.A.4.trace | grep State > lu.A.4.state.csv
+ 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
library(ggplot2)
# Read the data
- df_state = read.csv("lu.A.4.state.csv", header=F, strip.white=T)
+ 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))
dev.off()
This produces a file called ``Rplots.pdf`` with the following
-content. You can find more examples of visualization in the `SimGrid
-documentation <http://simgrid.gforge.inria.fr/contrib/R_visualization.html>`_.
+content. You can find more visualization examples `online
+<http://simgrid.gforge.inria.fr/contrib/R_visualization.html>`_.
-.. image:: /tuto_smpi/img/lu.A.4.png
+.. image:: /tuto_smpi/img/lu.S.4.png
:align: center
Lab 2: Tracing and Replay of LU
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.
+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/>`_.
+
.. LocalWords: SimGrid