The RAPIDS suite of open source software libraries and APIs gives you the ability to execute end-to-end data science and analytics pipelines entirely on GPUs. Licensed under Apache 2.0, RAPIDS is incubated by NVIDIA based on extensive hardware and data science science experience. RAPIDS utilizes NVIDIA CUDA primitives for low-level compute optimization, and exposes GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces.

**Software Category:** data

For detailed information, visit the RAPIDS website.

Available Versions

To find the available versions and learn how to load them, run:

module spider rapidsai

The output of the command shows the available RAPIDS module versions.

For detailed information about a particular RAPIDS module, including how to load the module, run the module spider command with the module’s full version label. For example:

module spider rapidsai/21.10
ModuleVersion Module Load Command
rapidsai21.10 module load singularity/3.7.1 rapidsai/21.10

Exclude K80 GPU nodes

RAPIDS requires compute capability 6.0+, which means it cannot work on K80 nodes. To exclude them from JupyterLab, fill out the form as you normally would and under

Optional: Slurm Option


-x udc-ba25-2[3,7,8],udc-ba26-2[3-6],udc-ba27-2[3-4]

If you are using a Slurm script, add this line:

#SBATCH -C "p100|v100|rtx2080"

(The constraint argument requires the " character which is not yet supported on the JupyterLab form.)