The purpose of this programming assignment is to gain experience in using performance analysis tools for parallel programs. For this assignment, you will run an existing parallel code, LULESH and analyze its performance using HPCToolkit and Hatchet.
You can get LULESH by cloning its git repository as follows:
You can use CMake to build LULESH on zaratan by following these steps:
git clone https://github.com/LLNL/LULESH.git
This should produce an executable
cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_CXX_COMPILER=mpicxx -DCMAKE_CXX_FLAGS="-g -O3" -DMPI_CXX_COMPILER=`which mpicxx` -DWITH_OPENMP=Off -DWITH_SILO=Off ..
lulesh2.0 in the build directory.
Lets say you want to run LULESH on 8 processes for 10 iterations/timesteps. This would be the mpirun line:
mpirun -np 8 ./lulesh2.0 -i 10 -p
HPCToolkit is available on zaratan via the
hpctoolkit/gcc module. You can use HPCtoolkit to collect profiling data for a parallel program in three steps.
mpirun -np <num_ranks> hpcrun ./exe <args>
hpcprof using its
You can use the installed Hatchet on zaratan using:
module load python
-s 45 and compare the performance of these executions with those in the default mode. Identify the functions/code regions where the code spends disproportionately more time compared to the default mode in task 1.
-s 22, and
-s 15 respectively), and compare the performance of various executions. Identify the functions/code regions that scale poorly as you run on more processes in this strong scaling mpde. Compare the results with the functions you identified in task 1.
You must submit the following files and no other files:
LastName-FirstName-assign2), compress it to .tar.gz (
LastName-FirstName-assign2.tar.gz) and upload that to gradescope.
Do not include irrelevant files in the tarball.
FirstName with your last and first name, respectively.
The project will be graded as follows: