NVIDIA Accelerated Data Science

GPU-Accelerate your Data Analytics Workflows

Data science gives enterprises around the world the power to analyze and optimize business processes, supply chains, scientific research, products, and digital experiences. GPU computing is revolutionizing data science with RAPIDS, an open-source data analytics and machine learning acceleration platform.

RAPIDS, a GPU-accelerated data science platform, is a next-generation computational ecosystem powered by Apache Arrow. NVIDIA's collaboration with Ursa Labs will accelerate the pace of innovation in the core Arrow libraries and help bring about major performance boosts in analytics and feature engineering workloads.

- Wes McKinney, Head of Ursa Labs and Creator of Apache Arrow and Pandas

At Databricks, we are excited about RAPIDS’ potential to accelerate Apache Spark workloads. We have multiple ongoing projects to integrate Spark better with native accelerators, including Apache Arrow support and GPU scheduling with Project Hydrogen. We believe that RAPIDS is an exciting new opportunity to scale our customers' data science and AI workloads.

- Matei Zaharia, co-founder and CTO of Databricks, and the original creator of Apache Spark

RAPIDS, a GPU-accelerated data science platform, is a next-generation computational ecosystem powered by Apache Arrow. NVIDIA's collaboration with Ursa Labs will accelerate the pace of innovation in the core Arrow libraries and help bring about major performance boosts in analytics and feature engineering workloads.

- Wes McKinney, Head of Ursa Labs and Creator of Apache Arrow and Pandas

At Databricks, we are excited about RAPIDS’ potential to accelerate Apache Spark workloads. We have multiple ongoing projects to integrate Spark better with native accelerators, including Apache Arrow support and GPU scheduling with Project Hydrogen. We believe that RAPIDS is an exciting new opportunity to scale our customers' data science and AI workloads.

- Matei Zaharia, co-founder and CTO of Databricks, and the original creator of Apache Spark

RAPIDS, a GPU-accelerated data science platform, is a next-generation computational ecosystem powered by Apache Arrow. NVIDIA's collaboration with Ursa Labs will accelerate the pace of innovation in the core Arrow libraries and help bring about major performance boosts in analytics and feature engineering workloads.

- Wes McKinney, Head of Ursa Labs and Creator of Apache Arrow and Pandas

At Databricks, we are excited about RAPIDS’ potential to accelerate Apache Spark workloads. We have multiple ongoing projects to integrate Spark better with native accelerators, including Apache Arrow support and GPU scheduling with Project Hydrogen. We believe that RAPIDS is an exciting new opportunity to scale our customers' data science and AI workloads.

- Matei Zaharia, co-founder and CTO of Databricks, and founder of Apache Spark

Features and Benefits

Ease of Use

Ease of Use

Accelerate your entire Python toolchain with open-source, hassle-free software integration and minimal code changes.

Accomplish More

Accomplish More

Accelerate machine learning training up to 50X with more iterations for better model accuracy.

Cost-Efficiency

Cost-Efficiency

Reduce data science compute infrastructure costs and increase data center efficiency.

Rapids: New software libraries for data science

RAPIDS is built on more than 15 years of NVIDIA® CUDA® development and machine learning expertise. It’s powerful new software for executing end-to-end data science training pipelines completely in the GPU, reducing training time from days to minutes.

NVIDIA RAPIDS Flow
End-to-End Faster Speeds on RAPIDS

Get started with Rapids today

RAPIDS libraries are open-source, written in Python, and built on Apache Arrow. The software is being developed in partnership with open-source communities globally. Download RAPIDS to experience acceleration of your machine learning and data science workflows.

Optimized for NVIDIA GPU acceleration

Run RAPIDS anywhere, cloud or on-prem. Easily scale from workstation to multi-GPU servers to multi-node clusters.

GPU Data Science in the Cloud

Accelerate machine learning and analytics workloads in the cloud with RAPIDS and NVIDIA GPUs.

Cloud Platforms

Cutting-Edge Tesla Partner Solutions

Start using RAPIDS today for enterprise-scale data science with GPU servers from leading OEMs powered by NVIDIA Tesla® V100 Tensor Core GPUs and NVIDIA NVLink.

The Ultimate Data Science Supercomputer

Deliver breakthrough performance for data science and machine learning workflows with RAPIDS and NVIDIA DGX-2. Optimized for accelerated data loading, data manipulation, and training of algorithms, get faster insights leveraging the performance and large GPU memory footprint of NVIDIA DGX-2.

Data Science Supercomputer

Partner Ecosystem

RAPIDS is open to all and being adopted by the top enterprise leaders in data science and analytics.

Big Data, Analytics, Visualization

Anaconda
BlazingDB
DataBricks
FastData
Graphistry
H20.ai
Kinetica
MAPR
Omni Sci
Sqream
Uber

Enterprise Data Science Platform

IBM
Oracle
SAP
Sas

Storage

DellEMC
HPE
IBM
NetApp
Pure Storage

Deep Learning

Chainer
PyTorch

Explore RAPIDS accelerated hardware solutions