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.
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/0.19
|Module||Version||Module Load Command|
|rapidsai||0.19||module load singularity/3.7.1 rapidsai/0.19|
|rapidsai||21.10||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
If you are using a Slurm script, add this line:
(The constraint argument requires the
" character which is not yet supported on the JupyterLab form.)