- Docker should be installed.
- nvidia-docker should be installed.
In the root path of cuDF repo, run below command to build the docker image.
docker build -f java/ci/Dockerfile.rocky --build-arg CUDA_VERSION=11.8.0 -t cudf-build:11.8.0-devel-rocky8 .
The following CUDA versions are supported w/ CUDA Enhanced Compatibility:
- CUDA 11.0+
Change the --build-arg CUDA_VERSION to what you need. You can replace the tag "cudf-build:11.8.0-devel-rocky8" with another name you like.
Run below command to start a docker container with GPU.
nvidia-docker run -it cudf-build:11.8.0-devel-rocky8 bash
You can download the cuDF repo in the docker container or you can mount it into the container. Here I choose to download again in the container.
git clone --recursive https://github.com/rapidsai/cudf.git -b branch-24.12
cd cudf
export WORKSPACE=`pwd`
scl enable gcc-toolset-11 "java/ci/build-in-docker.sh"
You can find the cuDF jar in java/target/ like cudf-24.12.0-SNAPSHOT-cuda11.jar.