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RAPIDS

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About

RAPIDS is a suite of open source software libraries and APIs leveraging NVIDIA GPUs to execute end-to-end data science pipelines using familiar PyData APIs. It delivers high-speed capabilities for dataframe processing (cuDF), machine learning (cuML), graph processing (cuGraph), and much more. With the integration of NVIDIA CUDA and Apache Arrow, RAPIDS allows users to transform their data science workflows, offering significant performance improvements over traditional CPU processing. The ecosystem promotes open collaboration and supports various cloud platforms for easy deployment, enhancing productivity for developers and data scientists.

Platform

Keywords

data science open source gpu nvidia apache arrow

Task

Features

• open source

• gpu acceleration

• supports various cloud platforms

• zero code change for cudf

• high-performance data processing

• seamless integration with pydata libraries

FAQs

What is RAPIDS?

RAPIDS is a collection of open source libraries aimed at accelerating data science workflows using NVIDIA GPUs.

What kind of tasks can RAPIDS assist with?

RAPIDS supports dataframe processing, machine learning, graph analytics, and spatial analytics among others.

Is RAPIDS open source?

Yes, RAPIDS is open source and encourages community involvement.

Pricing Plans

Free

• Open Source

• GPU Acceleration

• Support for PyData APIs

• Access to tutorials

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