Note: Static Jupyter artefact is available here
This artefact uses binder -- automatic cloud hosting of Jupyter workbooks with support for docker. So if you want to avoid all the steps mentioned below, simply click the binder badge.
This project uses Docker to facilitate reproducibility. As such, it has the following dependencies:
- nvidia-docker2 -- available here
To generate a docker image named artefact, run:
docker build -t artefact .
To start the docker image run:
docker run --runtime=nvidia -it --mount src=pwd,target=/workspace,type=bind -p 8888:8888 --net=host artefact
And run the codes with:
cd /codes
make
make test
This generates a sample of the runtimes with libscibench and the AIWC metrics
For reproducibility, BeakerX has also been added for replicating results and for the transparency of analysis. It is lauched by running:
cd /codes
beakerx --allow-root
from within the container and following the prompts to access it from the website front-end.
Note that if this node is accessed from an ssh session local ssh port forwarding is required and is achieved with the following:
ssh -N -f -L localhost:8888:localhost:8888 <node-name>