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RAPIDS

RAPIDS, built on NVIDIA AI, is an open-source suite of GPU-accelerated Python libraries designed to improve your data science and analytics pipelines. With APIs similar to popular open-source data science tools, RAPIDS uses NVIDIA® CUDA® primitives for low-level compute optimization. This provides access to GPU parallelism and high-bandwidth memory speed through Python interfaces, leading to a faster performance at scale across data pipelines.


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Ways to Get Started With RAPIDS


Get started with RAPIDS suite of software libraries

Learn How RAPIDS Is Being Deployed Today

AT&T applies the NVIDIA RAPIDS Accelerator in their data-to-AI pipeline

AT&T

AT&T applied the NVIDIA RAPIDS Accelerator for Apache Spark on GPU clusters for extract, transform, and load (ETL) and feature engineering stages in their data-to-AI pipeline, improving performance, reducing costs, and increasing simplicity compared to CPU-based Spark clusters and Databricks' Photon engine.


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NVIDIA and NASA have been using RAPIDS to monitor air quality during the COVID-19 pandemic

NASA

NVIDIA and NASA have been using RAPIDS to monitor air quality during the COVID-19 pandemic by combining surface monitoring data and near-real-time model data produced by the NASA GEOS-CF model. They use XGBoost to detect and quantify air pollution anomalies and build a bias-correction model that relates the model’s nitrogen dioxide predictions to observations.


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TCS Optumera uses Spark+Rapids to generate accurate predictions for demand forecasting

TCS Optumera

TCS Optumera accelerated their demand forecasting pipeline using Spark+Rapids to generate accurate predictions at a granular level, resulting in a 6X acceleration of data pipelines and a 170X performance boost in model training.


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 Walmart leverages Dask-RAPIDS to solve scalability issues

Walmart

Walmart leveraged Dask-RAPIDS to solve scalability issues with their product substitution algorithm, resulting in substantial hardware and cost reductions, improved runtime, and better insights for their business and customers.


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Financial service companies use NVIDIA's GPU-powered AI to improve customer service, prevent fraud, and more

Financial Services

Ping An, CAPE Analytics, Applica, Bank of Montreal, Capital One, Square, and Intuit are using NVIDIA's GPU-powered AI to improve customer service, prevent fraud, streamline processes, and accelerate growth, resulting in faster claims handling, more accurate underwriting decisions, elimination of manual errors, improved runtime, and better product design and selection.


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IRS team uses  Cloudera Data Platform with Spark 3.0 accelerated by NVIDIA

IRS and Cloudera

The IRS team used Cloudera Data Platform with Spark 3.0 accelerated by NVIDIA to achieve 20X performance gains on a large dataset for uncovering fraud, allowing them to run previously impossible jobs and accelerate their current work. They plan to apply this to their next step of accelerating full-blown AI inference jobs.


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Free Hands-On RAPIDS Labs on NVIDIA LaunchPad

Experience RAPIDS through one of the following free hands-on AI labs on hosted infrastructure:

  • Predict Prices With Accelerated Data Processing
  • Data Processing, Tokenization, and Sentiment Analysis
  • Accelerating Apache Spark With Zero Code Changes
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Free hands-On RAPIDS labs on NVIDIA LaunchPad

RAPIDS libraries are open source, written in Python, and built on Apache Arrow. The software is being developed in partnership with enterprises globally. Download NVIDIA RAPIDS to dramatically accelerate machine learning and data science.


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