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RAPIDS: Difference between revisions
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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. | 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. | ||
Since RAPIDS is available as Conda packages which requires to have Anaconda for the installation, however [[Anaconda/en|Anaconda]] is not advised to use on the Compute Canada clusters. Instead, a container solution of using [[Singularity|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. | This page provides the instructions for working with RAPIDS on Compute Canada clusters based from a Singularity container. | ||
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=Build a Singularity image for RAPIDS= | =Build a Singularity image for RAPIDS= | ||
==Where to look for a Docker image for RAPIDS== | |||
==Build a RAPIDS Singularity image== | |||
=Work on Clusters with a RAPIDS Singularity image= | =Work on Clusters with a RAPIDS Singularity image= | ||