Experimental playground for testing out linear solvers in OPM Flow.
We assume you have opm and dune in your prefix path. Compiling should just be
mkdir build
cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
make
Note that you probably want to specify CMAKE_PREFIX_PATH
to point to the locations of the OPM and Dune build folder, that is
# from build.
# IMPORTANT: Notice the quotation marks around the prefix path.
# This is IMPORTANT when you have multiple paths
cmake .. -DCMAKE_BUILD_TYPE=Release \
-DCMAKE_PREFIX_PATH="/path/to/opm-common/build;/path/to/opm-grid/build;MOREPATHSHERE"
To simplify this process, we've added the script build_helpers/prefix_path.sh
to generate this prefix path. If you directory structure looks like this:
#DUNE
/some/path/for/dune/dune-common/build
/some/path/for/dune/dune-grid/build
/some/path/for/dune/dune-geometry/build
/some/path/for/dune/dune-istl/build
#OPM
/some/path/other/path/for/opm/opm-common/build
/some/path/other/path/for/opm/opm-grid/build
/some/path/other/path/for/opm/opm-models/build
/some/path/other/path/for/opm/opm-simulators/build
you can run cmake as
# from build.
cmake .. -DCMAKE_BUILD_TYPE=Release \
-DCMAKE_PREFIX_PATH="$(bash ../build_helpers/prefix_path.sh /some/path/other/path/for/opm/ /some/path/for/dune/dune-common/)"
You probably need to have libfmt installed. On Ubuntu this can be accomplished by installing
sudo apt install libfmt-dev
Alternatively you can manually donwload and install libfmt. Make sure to extend your CMAKE_PREFIX_PATH
to contain the install directory of libfmt.
From the build folder, you can run eg.
./linsolverlab \
-x ../examples/matrices/spe1/rhs.mm \
-y ../examples/matrices/spe1/rhs.mm \
-m ../examples/matrices/spe1/matrix.mm \
-c ../examples/configurations/cpu/ilu0.json \
-g ../examples/configurations/gpu/cuilu0.json
Example output
{
"CPU": {
"runtime": "21541",
"failed_by_exception": "false",
"iterations": "25",
"reduction": "9.463892568041427e-13",
"converged": "true",
"conv_rate": "0.33040209473507992",
"elapsed": "0.021522673999999999",
"condition_estimate": "-1"
},
"GPU": {
"runtime": "21831",
"failed_by_exception": "false",
"iterations": "25",
"reduction": "3.532348061635463e-13",
"converged": "true",
"conv_rate": "0.31763074967064442",
"elapsed": "0.02177946",
"condition_estimate": "-1"
}
}
./linsolverlab \
-x ../examples/matrices/spe1/rhs.mm \
-y ../examples/matrices/spe1/rhs.mm \
-m ../examples/matrices/spe1/matrix.mm \
-c ../examples/configurations/cpu/ilu0_onlypreconditioner.json \
-g ../examples/configurations/gpu/cuilu0_onlypreconditioner.json
Example output
{
"CPU": {
"runtime": "6",
"failed_by_exception": "false",
"iterations": "1",
"reduction": "0",
"converged": "true",
"conv_rate": "1",
"elapsed": "0",
"condition_estimate": "-1"
},
"GPU": {
"runtime": "2396",
"failed_by_exception": "false",
"iterations": "1",
"reduction": "0",
"converged": "true",
"conv_rate": "1",
"elapsed": "0",
"condition_estimate": "-1"
}
}
Generating benchmark data
# usage: run_opm_benchmark.py <subfolder1> [<subfolder2> ...]
python benchmarking_scripts/run_opm_benchmark.py sleipner
Adjusting the experiment in the file
json_files = [
'examples/configurations/cpu/ilu0.json --block-size 2',
'examples/configurations/cpu/dilu.json --block-size 2',
'examples/configurations/gpu/cuilu0.json --block-size 2',
'examples/configurations/gpu/cudilu.json --block-size 2'
]
matrix_root = "./examples/matrices" # folder where the matrix files can be found
limit = 10 # Adjust this to change the number of matrices processed per directory
Plotting the results
python benchmarking_scripts/process_and_plot_opm.py