GPU-Enabled Data Science & Machine Learning

Use GPUs to speed up your data science by up to 2000x

Dask on GPUs

Dask integrates with RAPIDS cuDF, XGBoost, and RAPIDS cuML for GPU-accelerated data analytics and machine learning.

Python Integration

Speed up Python with minimal code changes.

Scale Out on GPUs

Get support for multi-node, multi-GPU deployments.

Accelerate Model Runtime by 2000x with RAPIDS

Native Integration

Out-of-the-box support and easy setup

Greater Model Accuracy

Increase machine learning model accuracy by iterating on models faster

Reducing Training Time

Improve your productivity with the fastest data science capabilities on market

Open Source

Customizable, extensible, interoperable – the open-source software is supported by NVIDIA and built on Apache Arrow.

A forest at sunset

Random Forest on GPUs: 2000x Faster than Apache Spark

We trained a random forest model using 300 million instances: Spark took 37 minutes on a 20-node CPU cluster, whereas RAPIDS took 1 second on a 20-node GPU cluster. That’s over 2000x faster with GPUs.

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