RAPIDS

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This is not a complete article: This is a draft, a work in progress that is intended to be published into an article, which may or may not be ready for inclusion in the main wiki. It should not necessarily be considered factual or authoritative.

Overview

RAPIDS is a suite of open source software libraries from NVIDIA, mainly for executing data science and analytics pipelines on GPUs. It relies on NVIDIA CUDA primitives for low level compute optimization and provides users with friendly Python APIs, similar to those in Pandas, Scikit-learn, etc.

Since RAPIDS is available as Conda packages which require having Anaconda for the installation, however Anaconda is not advised to use on the Compute Canada clusters. Instead, a container solution of using Singularity is recommended. As RAPIDS is also available as Docker container images from NVIDIA, and a Singularity image for RAPIDS can be built based from a Docker image.

This page provides the instructions for working with RAPIDS on Compute Canada clusters based from a Singularity container.

Build a Singularity image for RAPIDS

Where to look for a Docker image for RAPIDS

There are two major sites where to look for a Docker image for RAPIDS.

• NVIDIA GPU Cloud (NGC). The RAPIDS Docker images are available on NGC in two types, i.e.
  • base - contains a RAPIDS environment ready to use. Use this image if you want to submit a job to the Slurm scheduler.
  • runtime - extends the base image by adding a Jupyter notebook server and example notebooks. Use this image if you want to interactively work with RAPIDS through notebooks and examples.

• Docker Hub