Audience

Enterprises in search of a solution to execute end-to-end data science and analytics pipelines entirely on GPUs

About NVIDIA RAPIDS

The RAPIDS suite of software libraries, built on CUDA-X AI, gives you the freedom to execute end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization, but exposes that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces. RAPIDS also focuses on common data preparation tasks for analytics and data science. This includes a familiar DataFrame API that integrates with a variety of machine learning algorithms for end-to-end pipeline accelerations without paying typical serialization costs. RAPIDS also includes support for multi-node, multi-GPU deployments, enabling vastly accelerated processing and training on much larger dataset sizes. Accelerate your Python data science toolchain with minimal code changes and no new tools to learn. Increase machine learning model accuracy by iterating on models faster and deploying them more frequently.

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Company Information

NVIDIA
Founded: 1993
United States
developer.nvidia.com/rapids

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Product Details

Platforms Supported
Cloud
Training
Documentation
Live Online
In Person
Support
Phone Support
Online

NVIDIA RAPIDS Frequently Asked Questions

Q: What kinds of users and organization types does NVIDIA RAPIDS work with?
Q: What languages does NVIDIA RAPIDS support in their product?
Q: What kind of support options does NVIDIA RAPIDS offer?
Q: What other applications or services does NVIDIA RAPIDS integrate with?
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NVIDIA RAPIDS Product Features

Data Science

Data Ingestion
Data Preparation
Data Visualization
Data Discovery
Advanced Modeling
Model Deployment
Access Control
Audit Logs
Reports