Here is how to build and run the benchmarks:
docker build -t symengine/ubuntu_base ./ubuntu_base
docker build -t symengine/conda_base ./conda_base
docker build -t symengine/symengine --build-arg COMMIT=master ./symengine
docker run -it -p 8888:8888 symengine/symengine jupyter notebook --ip='*' --no-browser
Then open the Plots.ipynb
notebook and execute it. It will produce graphs of
the benchmarks.
We can compare two commits as follows. The commit 398a3f39 should be faster than fdf132fc.
COMMIT=398a3f39
docker build -t symengine/symengine:$COMMIT --build-arg COMMIT=$COMMIT ./symengine
docker run -t -v `pwd`:/opt/ symengine/symengine:$COMMIT bash run_copy.sh
cp data.json data-$COMMIT.json
COMMIT=fdf132fc
docker build -t symengine/symengine:$COMMIT --build-arg COMMIT=$COMMIT ./symengine
docker run -t -v `pwd`:/opt/ symengine/symengine:$COMMIT bash run_copy.sh
cp data.json data-$COMMIT.json
And locally execute the Plot-two.ipynb
notebook:
jupyter notebook Plot-two.ipynb
Which will plot the two data-*.json
files.