RAPIDS: Difference between revisions
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=Overview= | =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. | RAPIDS<ref>RAPIDS Open GPU Data Science : https://rapids.ai/ </ref> 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. | ||
This page provides the instructions for working with RAPIDS on Compute Canada clusters based from a Singularity container. | This page provides the instructions for working with RAPIDS on Compute Canada clusters based from a Singularity container. | ||
Revision as of 21:33, 18 December 2020
This article is a draft
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[1] 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.
This page provides the instructions for working with RAPIDS on Compute Canada clusters based from a Singularity container.
Build a Singularity image for RAPIDS
Work on Clusters with a RAPIDS Singularity image
Work interactively on a GPU node
Submit a RAPIDS job to Slurm scheduler
Helpful Links
- ↑ RAPIDS Open GPU Data Science : https://rapids.ai/