Single Node#

There are multiple ways you can deploy RAPIDS on a single instance, but the easiest is to use the RAPIDS docker image:

Launch a VM instance#

Launch an instance supported by RAPIDS. See the introduction section for a list of supported instance types.

Configure networking#

Create a Floating IP and associate that with the created instance to access the instance on the web.

Login#

Using the credentials supplied by IBM, log into the instance via SSH. For a short guide on launching your instance and accessing it, read the Getting Started with IBM Virtual Server Documentation.

Install pre-requisites#

Install the NVIDIA drivers and Docker and the NVIDIA Docker runtime in the IBM virtual server instance.

Install RAPIDS#

Install RAPIDS docker image. The docker container can be customized by using the options provided in the Getting Started page of RAPIDS. Example of an image that can be used is provided below:

$ docker pull rapidsai/rapidsai:22.10-cuda11.5-runtime-ubuntu20.04-py3.9
$ docker run --gpus all --rm -it --shm-size=1g --ulimit memlock=-1 -p 8888:8888 -p 8787:8787 -p 8786:8786 \
    rapidsai/rapidsai:22.10-cuda11.5-runtime-ubuntu20.04-py3.9

Test RAPIDS#

Test it! The RAPIDS docker image will start a Jupyter notebook instance automatically. You can log into it by going to the Floating IP address associated with the instance on port 8888.