Local

Choose your preferred method to install NVIDIA CUDA-X libraries for data science locally.

conda

Install CUDA-X using conda

https://docs.nvidia.com/datascience/install/#conda

Docker

Install CUDA-X using Docker

Custom Docker Guide

pip

Install CUDA-X using pip

https://docs.nvidia.com/datascience/install/#pip

WSL2

Install CUDA-X on Windows using WSL2

https://docs.nvidia.com/datascience/install/#wsl2

Examples

GPU-Accelerated Land Use Land Cover Classification

Classify land cover from Sentinel-2 imagery using Dask and Xarray composites and a cuML random forest.

Local · cuML · Training

Measuring Performance with the One Billion Row Challenge

Generate one billion rows with cuDF and CuPy, then aggregate them with Dask and cuDF about 60x faster than pandas.

EC2 +6 · cuDF · Data processing

HPO with dask-ml and cuml

Tune XGBoost and a cuML random forest on airline data with dask-ml grid and random search across local GPUs.

EC2 +4 · cuML · HPO

Getting Started with Optuna and CUDA-X libraries for HPO

Tune a cuML logistic regression on the BNP Paribas claims data with Optuna trials spread across local GPUs by Dask.

Local · cuML · HPO