RAPIDS
RAPIDS™, part of NVIDIA CUDA-X, is an open-source suite of GPU-accelerated data science and AI libraries with APIs that match the most popular open-source data tools. It accelerates performance by orders of magnitude, at scale, across data pipelines.
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RAPIDS Benefits
Massive Speedups
Faster pipelines enable more experimentation, improving outcomes.
Run Benchmarks Yourself
Easy to Adopt
Zero-code-change accelerators and familiar Python APIs quickly accelerate existing workloads.
Explore Modular Libraries
Flexible Open-Source Platform
With 100+ software integrations, RAPIDS promotes collaboration.
Explore the Ecosystem
Runs Everywhere
RAPIDS runs on all major clouds, on your local machine, or on premises.
See Deployment Options
Accelerating Data Science
With libraries that speed up widely adopted operations and algorithms, RAPIDS helps reduce time to insight as questions evolve.
150x
Faster Pandas With cuDF
* Benchmark on Groupy advanced operation (5GB) DuckDB Data Benchmark
HW: Intel Xeon Platinum 8480CL CPU and NVIDIA Grace Hopper GPU
SW: pandas v1.5 and cudf.pandas v23.10
500x
Faster NetworkX With cuGraph
* Benchmark on PageRank with 1.1M nodes, 57.5M edges
HW: CPU: Intel Xeon w9-3495X, GPU: NVIDIA A100 80GB (1x GPU)
SW: NetworkX 3.4.1, cuGraph/nx-cugraph 24.10
50x
Faster Scikit-Learn With cuML
* Benchmark on UMAP-Unsupervised on 100,000 samples and 256 features
HW: Intel Xeon Platinum 8480CL CPU and NVIDIA H100 80GB (1x GPU)
SW: scikit-learn v1.3 and cuML v23.10
See benchmarks at rapids.ai
Flexible Across Data Workloads
With a distinctive, modular, interoperable selection of libraries that smoothly plug and play into pipelines and applications, RAPIDS simplifies the development process.
RAPIDS keeps data science pipelines running smoothly at any scale.
Data Preparation
Seamlessly accelerate data analytics for tabular datasets, graph databases, or the Spark framework with your existing tools.
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Accelerated Data Analytics
Machine Learning
Boost model training speed with an API that closely follows scikit-learn.
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Machine Learning
Deep Learning
Support efficient graph neural networks training with DGL and PyG.
Learn More About Deep Learning
MLOps
Deploy high-performance machine learning inference with cuML and NVIDIA Triton™.
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Inference and Deployment
Inspired by the most popular open-source data tools, RAPIDS libraries adapt to your workflow.
Data Preprocessing: cuDF
Accelerate dataframes for efficiently processing hundreds of millions of records.
Explore Pandas Accelerator Mode Polars GPU Engine
Big Data Processing: RAPIDS Accelerator for Apache Spark
Accelerate your existing Apache Spark applications with minimal code changes.
Learn More About
GPU-Accelerated Spark Go to GitHub
Machine Learning: cuML
Execute machine learning algorithms on CPUs and GPUs with an API that closely follows the scikit-learn API.
Explore Docs
Graph Analytics: cuGraph
Quickly navigate graph analytics libraries with a python API that follows NetworkX.
Explore Docs
Vector Search: cuVS
Apply cuVS algorithms to accelerate vector search, including world-class performance from CAGRA.
Explore Docs
Scale RAPIDS: Dask-RAPIDS
Expand data science pipelines to multiple nodes with RAPIDS on Dask.
Go to GitHub
Visualization: cu-x-filter
Create interactive data visuals with multidimensional filtering of over 100-million-row tabular datasets.
Explore Docs
Image: cuCIM
Accelerate input/output (IO), computer vision, and image processing of n-dimensional, especially biomedical, images.
Explore Docs
Leverage purpose-built NVIDIA frameworks and guides to build accelerated applications for common and high-impact use cases.
Data Engineering
Revolutionize data management and preprocessing with the RAPIDS Accelerator for Spark.
Learn More About Scaled Data Processing
Time-Series Forecasting
Accelerate time-series modeling from feature engineering to forecasting.
Learn More About Time-Series Forecasting
Recommendation Systems
Build high-performing recommender systems at scale with NVIDIA Merlin™.
Learn More About Recommenders
AI Cybersecurity
Filter, process, and classify real-time data in optimized AI pipelines to quickly detect cyberthreats.
Learn More About AI Cybersecurity
Accelerated Optimization
cuOpt’s world-record-holding accelerated solver optimizes routes for last-mile delivery, technician dispatch, or intra-factory logistics.
Learn More About Route Optimization
Trillion Edge Graph
RAPIDS cuGraph makes it possible for enterprises to train trillion edge graph neural networks.
Learn More About Trillion Edge Graphs
RAPIDS excels at accelerating business-critical applications, reducing years of planning and development across industries.
Retail
Accelerated data science drives improved retail forecasting, data analytics, and more for retail.
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Finance
Real-time data enhances fraud detection and forecasting in an industry where time is of the essence.
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Thriving Ecosystem
With more than 100 open-source and commercial software integrations, RAPIDS provides a foundation for a collaborative high-performance data science ecosystem.
We're committed to simplifying, unifying, and accelerating data science for the open-source community.
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RAPIDS partners with the most popular data science and machine learning platforms to democratize access to accelerated data science.
Enterprise Data Science
Accelerated data science with NVIDIA AI Enterprise, an end-to-end, secure, cloud-native AI software platform optimized to take enterprises to the leading edge of AI. NVIDIA AI Enterprise delivers validation and integration for NVIDIA AI open-source software, including RAPIDS, access to AI solution workflows to speed time to production, certifications to deploy AI everywhere, and enterprise-grade support, security, manageability, and API stability to mitigate the potential risks of open-source software.
Learn More About AI Enterprise
Enterprise Adoption
Our customers use RAPIDS’ fully functional stack to scale their enterprise use cases.
PayPal reduced cloud costs by up to 70% with the RAPIDS accelerator for Apache Spark.
Watch On-Demand Session
Taboola, an advertising platform, processes terabytes of hourly data with the RAPIDS accelerator for Apache Spark.
Watch On-Demand Session
CapitalOne accelerated their financial and credit analysis pipelines, improving model training by 100X.
Watch On-Demand Session
Uber developed Horovod with support for Spark 3.x with GPU scheduling.
Watch On-Demand Session
Walmart solved scalability issues with their product-substitution algorithm.
Watch On-Demand Session
LinkedIn developed DARWIN to enable faster data analysis on RAPIDS cuDF.
Watch On-Demand Session
AT&T applied the RAPIDS Accelerator for Apache Spark on GPU clusters in their data-to-AI pipeline.
Read Blog
NASA used RAPIDS to detect and quantify air pollution anomalies and build a bias-correction model.
Read Blog: Part 1 Read Blog: Part 2
TCS Optumera accelerated their demand forecasting pipeline with the RAPIDS Accelerator for Apache Spark.
Watch On-Demand Session
The IRS team uncovered fraud with the RAPIDS Accelerator for Apache Spark on the Cloudera Data Platform.
Read BlogCheck out more RAPIDS resources, including developer kits, NVIDIA LaunchPad labs, and guidance on deployment options.