NVIDIA RAPIDS Description

The RAPIDS software library, which is built on CUDAX AI, allows you to run end-to-end data science pipelines and analytics entirely on GPUs. It uses NVIDIA®, CUDA®, primitives for low level compute optimization. However, it exposes GPU parallelism through Python interfaces and high-bandwidth memories speed through user-friendly Python interfaces. RAPIDS also focuses its attention on data preparation tasks that are common for data science and analytics. This includes a familiar DataFrame API, which integrates with a variety machine learning algorithms for pipeline accelerations without having to pay serialization fees. RAPIDS supports multi-node, multiple-GPU deployments. This allows for greatly accelerated processing and training with larger datasets. You can accelerate your Python data science toolchain by making minimal code changes and learning no new tools. Machine learning models can be improved by being more accurate and deploying them faster.

Integrations

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Company Details

Company:
NVIDIA
Year Founded:
1993
Headquarters:
United States
Website:
developer.nvidia.com/rapids

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Product Details

Platforms
SaaS
Type of Training
Documentation
Live Online
In Person
Customer Support
Phone Support
Online

NVIDIA RAPIDS Features and Options

Data Science Software

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