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rapidsai_public_repos/rapids.ai/layouts
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<div class="container">
<h2 class="mt-6">Adopters and Contributors</h2>
<p> RAPIDS has a strong ecosystem of adopters and contributors in a variety of industries and communities. Click on a logo to learn more:</p>
<div class="d-flex flex-wrap justify-content-between mt-5">
<a href="https://anyscale.com/" target="_blank" class="img-w100"> <img src="/images/Anyscale-logo.png" alt="anyscale"> </a>
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<a href="https://github.com/h2oai" target="_blank" class="img-w100"> <img src="/images/gpu-ventures-h2o-ai-logo.png" alt="h20ai"> </a>
<a href="https://ibm.github.io/" target="_blank" class="img-w100"> <img src="/images/ibm-logo.png" alt="ibm"> </a>
<a href="https://www.iguazio.com/" target="_blank" class="img-w100"> <img src="/images/iguazio_logo.png" alt="iguzaio"> </a>
<a href="https://github.com/INRIA" target="_blank" class="img-w100"> <img src="/images/inria-logo.png" alt="inria"> </a>
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<a href="https://paperspace.com" target="_blank" class="img-w100"> <img src="/images/paperspace.png" alt="paperspace"> </a>
</div>
<div class="d-flex flex-wrap justify-content-between">
<a href="https://plotly.com/dash/" target="_blank" class="img-w100"> <img src="/images/Plotly_Dash_logo.png" alt="plotly dash"> </a>
<a href="https://www.preferred-networks.jp/en/" target="_blank" class="img-w100"> <img src="/images/PFN-logo.png" alt="preferred-networks"> </a>
<a href="https://pytorch.org/" target="_blank" class="img-w100"> <img src="/images/PyTorch_logo.png" alt="pytorch"> </a>
<a href="https://ray.io/" target="_blank" class="img-w100"> <img src="/images/ray-logo.png" alt="ray"> </a>
<a href="https://www.saturncloud.io" target="_blank" class="img-w100"> <img src="/images/saturn-cloud-logo.png" alt="saturn-cloud"> </a>
<a href="https://github.com/uber" target="_blank" class="img-w100"> <img src="/images/uber_logo_2018.png" alt="uber"> </a>
<a href="https://ursalabs.org/" target="_blank" class="img-w100"> <img src="/images/ursa_logo.png" alt="ursa"> </a>
</div>
<div class="d-flex flex-wrap justify-content-between">
<a href="https://www.anaconda.com/anaconda-community/" target="_blank" class="img-w100"> <img src="/images/anaconda.png"alt="anaconda"> </a>
<a href="https://github.com/capitalone" target="_blank" class="img-w100"> <img src="/images/capital_one_logo.png" alt="capitalOne"></a>
<a href="https://github.com/chainer" target="_blank" class="img-w100"> <img src="/images/Chainer-logo.png" alt="chainer"> </a>
<a href="https://cupy.chainer.org/" target="_blank" class="img-w100"> <img src="/images/cupy-logo.png" alt="cuPY"> </a>
<a href="https://github.com/deepwavedigital" target="_blank" class="img-w100"> <img src="/images/deepwave-digital.png"alt="deepwave-digital"> </a>
<a href="https://gunrock.github.io/docs/" target="_blank" class="img-w100"> <img src="/images/Gunrock_Color.png" alt="gunrock"> </a>
<a href="https://developer.nvidia.com/open-source" target="_blank" class="img-w100"> <img src="/images/nvidia-hz.png" alt="nvidia"> </a>
<a href="https://github.com/quansight-labs" target="_blank" class="img-w100"> <img src="/images/quansight.png" alt="quantsight"> </a>
<a href="https://corporate.walmart.com/tech" target="_blank" class="img-w100"> <img src="/images/Walmart-logo.png" alt="walmart"> </a>
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<!-- Posts -->
<div class="container">
<h2 class="mt-5"><i class="fa-regular fa-message-quote"></i> Latest Posts </h2>
{{ range $index, $post := first 6 $.Site.Data.posts.medium }}
{{ if (modBool $index 3) }}
{{ $cssModifier := "mt-5" }}
{{ if (eq $index 0) }}
{{ $cssModifier = "" }}
{{end}}
<div class='row {{ $cssModifier }}'>
{{end}}
<div class="col-md-4 py-3">
<a href="{{ .link }}" target="_blank">
<h3>
{{ .title }} <i class="fa-solid fa-arrow-up-right"></i>
</h3>
<p class="post-text">
<i class="fa-sharp fa-solid fa-quote-left has-text-rapids-purple-secondary2"></i>
{{ .text}}
<i class="fa-sharp fa-solid fa-quote-right has-text-rapids-purple-secondary2"></i>
<br>
<span class="post-action">Post by {{ .poster }}</span>
</p>
</a>
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{{ if (eq (mod $index 3) 2) }}
</div>
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<nav x-data="{isOpen: false}" class="navigation container-fluid" role="navigation" aria-label="main navigation">
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---
title: RAPIDS | GPU Accelerated Data Science
---
<!-- Hero Shortcode -->
{{< hero hero-text="GPU Accelerated Data Science" button-link="#quick-start" button-text="Quick Start" >}}
<!-- Special -->
<section class="row">
<div class="col">
<div class="hero-announce-container">
<a href="https://www.nvidia.com/en-us/events/ai-data-science-virtual-summit/" target='_blank' class="hero-announce">
<span class="announce-icon fa-stack">
<i class="fa-solid fa-circle fa-stack-2x"></i>
<i class="fa-sharp fa-regular fa-bell-on fa-bounce fa-stack-1x fa-inverse"></i>
</span>
<button class="button-rapids-purple"><strong>Watch the replay:</strong> <br/> AI and Data Science Virtual Summit Hosted by NVIDIA</button>
</a>
<a href="/cudf-pandas" target='_blank' class="hero-announce">
<span class="announce-icon fa-stack">
<i class="fa-solid fa-circle fa-stack-2x"></i>
<i class="fa-sharp fa-regular fa-bell-on fa-bounce fa-stack-1x fa-inverse"></i>
</span>
<button class="button-rapids-purple"><strong>Now in open beta:</strong> <br> cuDF pandas accelerator mode</button>
</a>
</div>
</div>
</section>
<br>
<!-- Announcements Shortcode (0-3x)-->
<!-- UPDATE HERE -->
<!-- {{< announcements
text-2="RAPIDS 23.10 Released" link-2="https://docs.rapids.ai/install#selector"
text-3="Notice: Depreciation for Pascal GPUs" link-3="https://docs.rapids.ai/notices"
>}} -->
<!-- Intro -->
<section class="row section padding-bottom-slant">
<div class="col">
<div class="container">
<h1 class="text-center mb-5">Data Science at the speed of thought</h1>
<div class="row">
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-caret-right"></i> What is RAPIDS </h2>
<p> RAPIDS provides unmatched speed with familiar APIs that match the most popular PyData libraries. Built on state-of-the-art foundations like <a href="https://developer.nvidia.com/cuda-toolkit" target="_blank">NVIDIA CUDA</a> and <a href="https://arrow.apache.org/" target="_blank">Apache Arrow</a>, it unlocks the speed of GPUs with code you already know. <a href="/learn-more/#about">Jump to About Section <i class="fa-solid fa-arrow-up-right"></i> </a></p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-bolt-lightning"></i> Why Use RAPIDS</h2>
<p> RAPIDS allows fluid, creative interaction with data for everyone from BI users to AI researchers on the
cutting edge. GPU acceleration means less time and less cost moving data and training models. <a href="/learn-more/#use-cases">Jump to RAPIDS Use Cases <i class="fa-solid fa-arrow-up-right"></i> </a></p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-chart-network"></i> Open Source Ecosystem </h2>
<p>RAPIDS is Open Source and available on <a href="https://github.com/rapidsai" target="_blank">GitHub</a>.
Our mission is to empower and advance the open-source GPU data science data engineering ecosystem. <a href="https://github.com/rapidsai" target="_blank">Jump to RAPIDS GitHub <i class="fa-solid fa-arrow-up-right"></i> </a></p>
</div>
</div>
<br>
<div class="row has-background-rapids-image ">
<div class="col-md-12 py-5">
<h2 class="text-white"><i class="fa-light fa-gauge-circle-bolt"></i> NEW: Pandas Accelerator Mode for cuDF </h2>
<p class="text-white">Use cuDF's new pandas Accelerator Mode to speed up pandas workflows with zero code change.
<a href="/cudf-pandas"> Learn More on the Launch Page <i class="fa-solid fa-arrow-up-right"></i></a> </p>
</div>
</div>
<br>
<div id="benchmarks"></div>
<div class="row mt-5">
<div class="col-md-4 py-3">
<h2><i class="fa-thin fa-objects-column"></i> Faster Pandas <br> with cuDF</h2>
<p>cuDF accelerates pandas with no code change and brings greatly improved performance.</p> <br>
<a href="https://github.com/rapidsai/cudf/blob/branch-23.10/docs/cudf/source/user_guide/performance-comparisons/performance-comparisons.ipynb" target="_blank">Run this benchmark yourself <i class="fa-solid fa-arrow-up-right"></i> </a>
<canvas id="cuDFchart" width="400" height="350"></canvas>
<p class="fs-8 text-muted">* Benchmark on AMD EPYC 7642 (using 1x 2.3GHz CPU core) w/ 512GB and NVIDIA A100 80GB (1x GPU) w/ pandas v1.5 and cuDF v23.02</p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-microchip-ai"></i> Faster scikit-learn <br> with cuML</h2>
<p>cuML brings huge speedups to ML modeling with an API that matches scikit-learn.</p> <br>
<a href="https://github.com/rapidsai/cuml/tree/branch-23.10/python/cuml/benchmark" target="_blank">Run this benchmark yourself <i class="fa-solid fa-arrow-up-right"></i> </a>
<canvas id="cuMLchart" width="400" height="350"></canvas>
<p class="fs-8 text-muted">* Benchmark on AMD EPYC 7642 (using 1x 2.3GHz CPU core) w/ 512GB and NVIDIA A100 80GB (1x GPU) w/ scikit-learn v1.2 and cuML v23.02</p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-circle-nodes"></i> Faster networkX <br> with cuGraph</h2>
<p>cuGraph makes migration from networkX easy, accelerates graph analytics, and allows scaling far beyond existing tools. </p>
<a href="https://github.com/rapidsai/cugraph/blob/branch-23.10/notebooks/cugraph_benchmarks/synth_release.ipynb" target="_blank">Run this benchmark yourself <i class="fa-solid fa-arrow-up-right"></i> </a>
<canvas id="cuGraphChart" width="400" height="350"></canvas>
<p class="fs-8 text-muted">* Benchmark on AMD EPYC 7642 (using 1x 2.3GHz CPU core) w/ 512GB and NVIDIA A100 80GB (1x GPU) w/ networkX v3.0 and cuGraph v23.02</p>
</div>
</div>
</div>
</div>
</section>
<div class="top-slant-container">
<div class="top-slant-down has-background-rapids-purple-primary"></div>
</div>
<!-- Quick Start -->
<div id="quick-start"></div>
<section class="row section has-background-rapids-purple-primary text-white padding-bottom-slant">
<div class="col">
<div class="container">
<h1 class="mb-5 text-white">Quick Start</h1>
<div class="row">
<div class="col-md-6 py-3">
<h2 class="text-white"><i class="fa-light fa-download"></i> Quick Local Install </h2>
<p>RAPIDS offers several installation methods, the quickest is shown below.</p>
<br>
<p>For more detailed guides go to our <a href="https://docs.rapids.ai/install" target="_blank">advanced install page <i class="fa-solid fa-arrow-up-right"></i></a> </p>
<h3 class="mt-5 text-white">Requirements</h3>
<p><strong>A.</strong> NVIDIA Pascal™ or better GPU with a <a href="https://developer.nvidia.com/cuda-gpus" target="_blank">compute capability 6.0 and above <i class="fa-solid fa-arrow-up-right"></i></a></p>
<p><strong>B.</strong> Ubuntu 20.04 or 22.04, CentOS 7, Rocky Linux 8, or WSL2 on Windows 11</p>
<p><strong>C.</strong> Recent <a href="https://docs.nvidia.com/deploy/cuda-compatibility/index.html" target="_blank"> CUDA version <em>and</em> NVIDIA driver pairs</a>. Check yours with:
<code>nvidia-smi</code>
<h3 class="mt-6 text-white">Install with Conda</h3>
<p><strong>1.</strong> If not installed, download and run the install script. <br>
This will install the latest miniconda:
</p>
<pre class="highlight use-white-copy"><code>wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh</code></pre>
<br>
<p><strong>2.</strong> Then quick install RAPIDS with:</p>
<pre class="highlight use-white-copy"><code>conda create --solver=libmamba -n rapids-23.10 -c rapidsai -c conda-forge -c nvidia rapids=23.10 python=3.10 cudatoolkit=11.8</code></pre>
<h3 class="mt-6 text-white">Install with pip</h3>
<p><strong>1.</strong> Install via pip channels:</p>
<pre class="highlight use-white-copy"><code>pip install cudf-cu11 dask-cudf-cu11 --extra-index-url=https://pypi.nvidia.com
pip install cuml-cu11 --extra-index-url=https://pypi.nvidia.com
pip install cugraph-cu11 --extra-index-url=https://pypi.nvidia.com</code></pre>
<h3 class="mt-6 text-white">Install with Docker</h3>
<p>Check that you have the <a href="https://docs.rapids.ai/install#docker" target="_blank">required environment</a> and then use the <a href="https://docs.rapids.ai/install#selector" target="_blank">install selector <i class="fa-solid fa-arrow-up-right"></i> </a></p>
<h3 class="mt-6 text-white">Install on Windows</h3>
<p>Use the Windows <a href="https://docs.rapids.ai/install#wsl2" target="_blank">WSL2 installation instructions <i class="fa-solid fa-arrow-up-right"></i> </a></p>
<h2 class="mt-9 text-white"><i class="fa-light fa-gears"></i> Do I need an Advanced Install?</h2>
<p> If you want to use Docker, WSL2, have an uncommon OS, hardware configuration, environment, or
need specific versions such as <code> CUDA 11.8 </code> or <code> Python 3.8 </code> then you should use the
installation selector in our
<a href="https://docs.rapids.ai/install" target="_blank">Advanced Installations Page <i class="fa-solid fa-arrow-up-right"></i> </a>
</p>
</div>
<div class="col-md-6 py-3">
<h2 class="text-white"><i class="fa-light fa-gauge-circle-bolt"></i> Test Drive the new cuDF</h2>
<p>Try out cuDF's new pandas Accelerator Mode, with a free required account, right now by <a href="https://nvda.ws/rapids-cudf" target="_blank">Launching Google CoLab <i class="fa-solid fa-arrow-up-right"></i> </a> </p>
<br><br>
<h2 class="text-white"><i class="fa-light fa-cloud-arrow-down"></i> Try RAPIDS Online </h2>
<p>Don't have access to a GPU system right now? Try out RAPIDS with cloud based hardware from one of these featured channels: </p>
<br>
<div class="row">
<div class="col-md-6 py-3">
<img src="/images/OpenGoogleColab.png" class="img-w200">
<h3> <a href="https://colab.research.google.com/drive/13sspqiEZwso4NYTbsflpPyNFaVAAxUgr" target="_blank">Google CoLab <i class="fa-solid fa-arrow-up-right"></i> </a></h3>
<p>Jump right into a GPU enabled RAPIDS notebook environment with a free required account. Installed with pip, it is also available via <a href="https://colab.research.google.com/drive/1TAAi_szMfWqRfHVfjGSqnGVLr_ztzUM9" target="_blank">Conda</a>. </p>
</div>
<div class="col-md-6 py-3">
<img src="/images/OpenAmazonStudioLab.png" class="img-w200">
<h3> <a href="https://studiolab.sagemaker.aws/" target="_blank">Studio Lab <i class="fa-solid fa-arrow-up-right"></i> </a></h3>
<p>Enables Amazon Sagemaker notebook based environments in a free trial with required account.</p>
</div>
</div>
<div class="row">
<div class="col-md-6 py-3">
<img src="/images/paperspace.png" class="img-w150">
<h3> <a href="https://www.paperspace.com/gpu-cloud" target="_blank">PaperSpace <i class="fa-solid fa-arrow-up-right"></i> </a></h3>
<p>Use Quick Start Instances through a limited free account.</p>
</div>
<div class="col-md-6 py-3">
<img src="/images/nv-launchpad.png" class="img-w150">
<h3> <a href="https://www.nvidia.com/en-us/launchpad/" target="_blank">NVIDIA LaunchPad <i class="fa-solid fa-arrow-up-right"></i> </a></h3>
<p>Free short term use to try and learn with hands-on lab environment.</p>
</div>
</div>
<div class="row">
<div class="col-md-6 py-3">
<img src="/images/Microsoft-Azure-Logo.png" class="img-w150">
<h3> <a href="https://azure.microsoft.com/en-us/free/" target="_blank">Microsoft Azure <i class="fa-solid fa-arrow-up-right"></i> </a></h3>
<p>Microsoft Azure Cloud infrastructure and services are available with RAPIDS.</p>
</div>
<div class="col-md-6 py-3">
<img src="/images/Oracle-logo.png" class="img-w150">
<h3> <a href="https://www.oracle.com/cloud/" target="_blank">Oracle Cloud <i class="fa-solid fa-arrow-up-right"></i> </a></h3>
<p>Oracle Cloud infrastructure and services are available with RAPIDS. </p>
</div>
</div>
<div class="row">
<div class="col-md-6 py-3">
<img src="/images/IBM-logoblk.png" class="img-w150">
<h3> <a href="https://www.ibm.com/cloud" target="_blank">IBM Cloud <i class="fa-solid fa-arrow-up-right"></i> </a></h3>
<p>IBM Cloud infrastructure and services are available with RAPIDS.</p>
</div>
</div>
<h2 class="mt-9 text-white"><i class="fa-regular fa-chalkboard-user"></i> User Guides and Tutorials
</h2>
<p>After installing, the best place to start is by looking through our more detailed tutorials and guides on the <a href="https://docs.rapids.ai/user-guide" target="_blank">User Guides Page <i class="fa-solid fa-arrow-up-right"></i> </a> </p>
</p>
</div>
</div>
</div>
</div>
</section>
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<div class="bottom-slant-up has-background-rapids-purple-primary"></div>
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<section class="row section padding-top-slant">
<div class="col">
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<h1>Ecosystem</h1>
<div class="row">
<div class="col-md-4 py-3">
<h2><i class="fa-regular fa-microchip"></i> Hardware </h2>
<p> NVIDIA's industry leading hardware provides the platform for RAPIDS high performance. Get details on the
newest GPUs, server architectures, and cloud offerings in our <a href="/ecosystem"> Ecosystem Hardware Section <i class="fa-solid fa-arrow-up-right"></i></a>
</p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-regular fa-code"></i> Software </h2>
<p>Find out details on featured RAPIDS projects like cuDF, cuML, cuGraph, and more. Also learn about
those using our integrated with RAPIDS in our <a href="/ecosystem#featured-software"> Ecosystem Software Section <i class="fa-solid fa-arrow-up-right"></i></a>
</p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-regular fa-laptop-code"></i> Developers </h2>
<p> Get involved with RAPIDS projects, reach out to its developers, find maintainer and contribution guides
in our <a href="/ecosystem#developers"> Ecosystem Developers Section <i class="fa-solid fa-arrow-up-right"></i></a>
</p>
</div>
</div>
</div>
</div>
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<h1 class="mb-5">Learn More</h1>
<div class="row">
<div class="col-md-4 py-3">
<h2><i class="fa-regular fa-circle-info"></i> About RAPIDS</h2>
<p> Learn more about RAPIDS' start with Apache Arrow and GoAi. Also find an overview of the capabilities of RAPIDS, as well as featured projects in our
<a href="/learn-more"> About Section <i class="fa-solid fa-arrow-up-right"></i></a>
</p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-regular fa-chart-user"></i> Use Cases </h2>
<p> Hear about success stories, resources for integrating RAPIDs workflows in your business, and deployment strategies in our
<a href="/learn-more#use-cases"> Use Cases Section <i class="fa-solid fa-arrow-up-right"></i></a>
</p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-regular fa-message-exclamation"></i> Get Involved </h2>
<p> Use RAPIDS directly or through <a href="https://www.nvidia.com/en-us/data-center/products/ai-enterprise/" target="_blank">NVIDIA AI Enterprise</a>, which provides extensive optimization, certified hardware profiles, and direct IT support. Find additional business resources, community resources, and guides for RAPIDS evangelism in our
<a href="/learn-more/#get-involved"> Get Involved Section <i class="fa-solid fa-arrow-up-right"></i></a>
</p>
</div>
</div>
</div>
</div>
</section>
<div class="bottom-slant-container">
<div class="bottom-slant-down bg-white"></div>
</div>
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<section class="row section padding-top-slant padding-bottom-slant has-background-rapids-gray">
<div class="col">
<div class="container mb-9">
<h1 class="mb-5">Latest News</h1>
<div class="row">
<div class="col-md-4 py-3">
<h2><i class="fa-brands fa-twitter"></i> RAPIDS X/Twitter </h2>
<p> Follow the latest from the RAPIDS X/Twitter community with <a href="https://twitter.com/RAPIDSai" target="_blank">@RAPIDSai <i class="fa-solid fa-arrow-up-right"></i></a> </p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-regular fa-triangle-exclamation"></i> RAPIDS Support Notices </h2>
<p> Get the full list of developer updates and notices (RSN) that may affect your projects on the <a
href="https://docs.rapids.ai/notices" target="_blank"> RSN Docs Page <i class="fa-solid fa-arrow-up-right"></i></a> </p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-regular fa-books"></i> RAPIDS News </h2>
<p> Find our highlighted content, including talks, posts, guides and more on the <a href="https://developer.nvidia.com/blog/" target="_blank"> NVIDIA Dev Blog</a> and <a href="https://medium.com/rapids-ai" target="_blank">RAPIDS Blog <i class="fa-solid fa-arrow-up-right"></i></a> </p>
</div>
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rapidsai_public_repos/rapids.ai/content/user-guides/library-guides.md
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---
layout: default
title: User Guides
nav_order: 3
permalink: user-guide
description: |
Guide to Getting Started Using RAPIDS
---
# RAPIDS User Guides
{: .fs-8 }
The RAPIDS data science framework is a collection of libraries for running end-to-end data science pipelines completely on the GPU. The interaction is designed to have a familiar look and feel to working in Python, but utilizes optimized NVIDIA® CUDA® primitives and high-bandwidth GPU memory under the hood. Below are some links to help getting started with each of the individual RAPIDS libraries.
{: .fs-6 .fw-300 .mb-8 }
### <i class="fa-light fa-notebook"></i> Full Collection of each RAPIDS Library Example Notebooks with [RAPIDS Notebooks](https://github.com/rapidsai/notebooks){: target="_blank"}
A GitHub repository with our introductory examples of XGBoost, cuDF, cuML, cuGraph, and more.
{: .mb-8 }
### <i class="fa-light fa-notebook"></i> Extended Collection of [Community Notebooks](https://github.com/rapidsai/notebooks-contrib){: target="_blank"}
A collection of examples and tutorials used to introduce new users to the features and capabilities of RAPIDS.
{: .mb-8 }
### <i class="fa-light fa-cloud"></i> Machine Learning Services Integration for [RAPIDS Cloud](https://github.com/rapidsai/cloud-ml-examples){: target="_blank"}
A repository with example notebooks and "getting started" code samples to help you integrate RAPIDS with the hyperparameter optimization services from Azure ML, AWS Sagemaker, Google Cloud, and Databricks.
{: .mb-8 }
### <i class="fa-light fa-screwdriver-wrench"></i> Tools and Guides for [RAPIDS Deployment](/deployment/stable/){: target="_blank"}
Deployment documentation to get you up and running with RAPIDS in AWS, GCP, Azure, IBM and more. Also includes guides for HPC, HPO, Kubernetes, Dask, and more.
{: .mb-8 }
### <i class="fa-sharp fa-solid fa-database"></i> ETL and Dataframe Processing with [cuDF](https://github.com/rapidsai/cudf){: target="_blank"}
Start with the [10 Minutes to cuDF and Dask-cuDF User Guide](/api/cudf/stable/user_guide/10min/){: target="_blank"}. Modeled after 10 Minutes to Pandas, this is a short introduction to cuDF that is geared mainly for new users. The [cuDF User Guide](/api/cudf/stable/user_guide/index/){: target="_blank"} is generally very extensive and helpful.
{: .mb-8 }
### <i class="fa-light fa-list-tree"></i> Accelerated Machine Learning with [cuML](https://github.com/rapidsai/cuml){: target="_blank"}
Start with the [User Guide](/api/cuml/stable/user_guide/){: target="_blank"} and the [Estimator Intro](https://github.com/rapidsai/cuml/blob/branch-{{ site.data.releases.stable.version }}/docs/source/estimator_intro.ipynb){: target="_blank"}, showcasing basic machine learning for training and evaluating machine learning models in cuML. The [Intro and key concepts for cuML](/api/cuml/stable/cuml_intro/) is helpful as well.
{: .mb-8 }
### <i class="fa-light fa-chart-network"></i> Graph Analytics with [cuGraph](https://github.com/rapidsai/cugraph){: target="_blank"}
Start with the [Easy Path](/api/cugraph/stable/basics/nx_transition/#easy-path-use-networkx-graph-objects-accelerated-algorithms){: target="_blank"} to use NetworkX graph objects with accelerated algorithms. There is also general [cuGraph Introduction](/api/cugraph/stable/basics/cugraph_intro/){: target="_blank"}.
{: .mb-8 }
### <i class="fa-light fa-location-crosshairs"></i> Spatial Analytics with [cuSpatial](https://github.com/rapidsai/cuspatial){: target="_blank"}
Start with the [cuSpatial User Guide](/api/cuspatial/stable/user_guide/cuspatial_api_examples/){: target="_blank"} for an intro to GPU Accelerated Spatial Analytics. The [demo notebooks](https://github.com/rapidsai/cuspatial/tree/branch-{{ site.data.releases.stable.version }}/python/cuspatial/demos) are also a good showcase.
{: .mb-8 }
### <i class="fa-light fa-chart-scatter-bubble"></i> Accelerated Cross-filtered Dashboards with [cuxfilter](https://github.com/rapidsai/cuxfilter)
Start with [10 Minutes to Cuxfilter](/api/cuxfilter/stable/10_minutes_to_cuxfilter/){: target="_blank"} to get an overview of how to quickly create a dashboard and [the examples section](/api/cuxfilter/stable/examples/examples/){: target="_blank"} for real dataset examples.
{: .mb-8 }
### <i class="fa-regular fa-signal-stream"></i> Signal Analytics with [cuSignal](https://github.com/rapidsai/cusignal){: target="_blank"}
Start with the [End to End Example](https://github.com/rapidsai/cusignal/blob/branch-{{ site.data.releases.stable.version }}/notebooks/E2E_Example.ipynb){: target="_blank"} for simulating signals and influencing guide as well as the [API Guide](https://github.com/rapidsai/cusignal/tree/branch-{{ site.data.releases.stable.version }}/notebooks/api_guide){: target="_blank"}.
{: .mb-8 }
### <i class="fa-light fa-images"></i> Computer Vision and Analytics with [cuCIM](https://github.com/rapidsai/cucim){: target="_blank"}
Start with the [Welcome Notebook](https://github.com/rapidsai/cucim/blob/branch-{{ site.data.releases.stable.version }}/notebooks/Welcome.ipynb){: target="_blank"} for links to resources guides and a good overview of the project structure.
{: .mb-8 }
### <i class="fa-light fa-file-binary"></i> Algorithms and Primitives for Scientific Computing, Data Science and Machine Learning with [RAFT](https://github.com/rapidsai/raft){: target="_blank"}
Start with the [Quick Start](/api/raft/stable/quick_start/){: target="_blank"} guide for simple python and C++ examples.
{: .mb-8 }
### <i class="fa-light fa-bolt"></i> Accelerated Apache Spark with [Spark RAPIDS](https://nvidia.github.io/spark-rapids/){: target="_blank"}
Start with [the Examples Repository](https://github.com/NVIDIA/spark-rapids-examples){: target="_blank"} for Spark related utilities and examples using the RAPIDS Accelerator, including ETL, ML/DL, and more. A good [overview](https://nvidia.github.io/spark-rapids/){: target="_blank"} is available on their docs introduction.
{: .mb-8 }
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---
title: User Guides | RAPIDS
description: User Guides and Tips
---
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<!-- Intro -->
<section class="section padding-bottom-slant">
<div class="container">
<h1 class="has-text-centered mb-5"> User Guides</h1>
<div class="columns">
<div class="column is-one-third">
<h2><i class="fa-light fa-gallery-thumbnails"></i> Featured Content </h2>
<p> Our choice picks for featured talks, posts, videos, conferences and more.</p>
<a href="/featured">Featured Page <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
<div class="column is-one-third">
<h2><i class="fa-brands fa-twitter"></i> RAPIDS X/Twitter </h2>
<p> Follow the latest from the RAPIDS X/Twitter community. </p>
<a href="https://twitter.com/RAPIDSai" target="_blank">@RAPIDSai <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
<div class="column is-one-third">
<h2><i class="fa-light fa-triangle-exclamation"></i> Support Notices </h2>
<p> Technical notices for our contributors, core developers, and the general community about important updates.</p>
<a href="https://docs.rapids.ai/notices" target="_blank">Support Notices Page <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
</div>
</div>
</section>
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rapidsai_public_repos/rapids.ai/content/user-guides/visualization.md
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---
layout: default
title: Visualization Guide
nav_order: 5
permalink: visualization
---
# RAPIDS Visualization Guide
RAPIDS libraries can easily fit in visualization workflows. This catalog of featured libraries offer direct cuDF support or easy integration.
{: .fs-6 .fw-300 }
<img src="/assets/images/datashader-census-rapids.png" style="width:870px">
*[330 million+ datapoints rendered in under 1.5s via RAPIDS + Plotly Dash 2020 Census Demo](https://github.com/rapidsai/plotly-dash-rapids-census-demo)*
### Featured Libraries
- **[HoloViews](#holoviews):** Declarative objects for quickly building complex interactive plots from high-level specifications. Directly uses cuDF.
- **[hvPlot](#hvplot):** Quickly return interactive plots from cuDF, Pandas, Xarray, or other data structures. Just replace `.plot()` with `.hvplot()`.
- **[Datashader](#datashader):** Rasterizing huge datasets quickly as scatter, line, geospatial, or graph charts. Directly uses cuDF.
- **[Plotly](#plotly):** Charting library that supports Plotly Dash for building complex analytics applications.
- **[Bokeh](#bokeh):** Charting library for building complex interactive visualizations.
- **[Seaborn](#seaborn):** Static single charting library that extends matplotlib.
### Other Notable Libraries
- **[Panel](#panel):** A high-level app and dashboarding solution for the Python ecosystem.
- **[PyDeck](#pydeck):** Python bindings for interactive spatial visualizations with webGL powered deck.gl, optimized for a Jupyter environment.
- **[cuxfilter](#cuxfilter):** RAPIDS developed cross filtering dashboarding tool that integrates many of the libraries above.
- **[node RAPIDS](#noderapids):** RAPIDS bindings in nodeJS, a high performance JS/TypeScript visualization alternative to using Python.
### GPU Accelerated Interaction
The below libraries directly use RAPIDS cuDF/Dask-cuDF and/or cuSpatial to create charts that support accelerated crossfiltering or rendering:
- **[Holoviews with Linked Brushing User Guide](https://holoviews.org/user_guide/Linked_Brushing.html?highlight=linked%20brushing)**
- **[Datashader User Guide](https://datashader.org/user_guide/Performance.html)**
- **[Plotly Dash with Holoviews Docs](https://dash.plotly.com/holoviews#gpu-accelerating-datashader-and-linked-selections-with-rapids)**
- **[cuxfilter GitHub](https://github.com/rapidsai/cuxfilter)**
### **Note:** Web Hosted vs Local Hosted Chart Interaction
When interacting with this page through a website, the interactive examples below are all **static and use pre-computed data.** To run a true interactive version, host through the **active** instance found on our [cuxfilter GitHub Notebooks](https://github.com/rapidsai/cuxfilter/tree/branch-{{ site.data.releases.stable.version }}/notebooks/RAPIDS%20Visualization%20Guide).
{% include viz-cdn-js-css.html %}
<br/><br/>
# Featured Libraries
<a id='holoviews'></a><br/>
<img src="/assets/images/holoviews-logo.png" style="width:150px; display:inline-block; vertical-align:middle;">
<a href="https://holoviews.org/gallery/index.html" target="_blank" title="holoviews NYC taxi example">
<img src="/assets/images/nytaxi_hover.gif" style="width:300px; display:inline-block; vertical-align:middle; padding-left:20px;"></a>
<br/>
- HoloViews is an open-source Python library designed to make data analysis and visualization seamless and simple. [See this diagram](https://holoviz.org/background.html#the-holoviz-ecosystem) for an excellent architecture overview.
- With HoloViews, you can usually express what you want to do in very few lines of code, letting you focus on what you are trying to explore and convey, not on the process of plotting.
- Read about Holoviews at [holoviews.org](https://holoviews.org) and explore its gallery [holoviews.org/gallery/](https://holoviews.org/gallery/).
- Read about [RAPIDS compatibilty](https://holoviews.org/reference_manual/holoviews.core.data.html?highlight=cudf#module-holoviews.core.data.cudf).
**Run an interactive example and cpu / gpu code comparison below:**
{% include holoviews.html %}
<a id='hvplot'></a><br/>
<img src="/assets/images/hvplot-logo.png" style="width:90px; display:inline-block; vertical-align:middle;">
<a href="https://hvplot.holoviz.org/reference/index.html" target="_blank" title="hvplot heat map example">
<img src="/assets/images/heatmap.png" style="width:120px; display:inline-block; vertical-align:middle; padding-left:20px;"></a>
- hvPlot provides an alternative for the static plotting API provided by Pandas and other libraries, with an interactive plotting API. Just replace `.plot()` with `.hvplot()`.
- hvPlot can integrate neatly with the individual libraries if an extension mechanism for the native plot APIs is offered, or it can be used as a standalone component.
- Read about hvPlot at [holoviews.org](http://holoviews.org) and explore its gallery [hvplot.holoviz.org/reference/index.html](https://hvplot.holoviz.org/reference/index.html).
- Read about [RAPIDS compatibility](https://hvplot.holoviz.org/user_guide/Introduction.html?highlight=rapids#).
<br/>
**Run an interactive example and cpu / gpu code comparison below:**
{% include hvplot.html %}
<a id='datashader'></a><br/>
<img src="/assets/images/datashader-logo.png" style="width:150px; display:inline-block; vertical-align:middle;">
<a href="https://panel.holoviz.org/gallery/simple/clifford_interact.html" target="_blank" title="datashader clifford demo">
<img src="/assets/images/clifford_interact.png" style="width:130px; display:inline-block; vertical-align:middle; padding-left:20px; "></a>
- Datashader is a graphics pipeline system for creating meaningful representations of large datasets quickly and flexibly.
- Datashader is able to render a variety of chart types statically, and interactively when combined with other libraries like HoloViews or cuxfilter.
- Read about Datashader at [datashader.org](https://datashader.org) and explore its examples.
- Read about [RAPIDS compatibility](https://datashader.org/user_guide/Performance.html?highlight=cudf#data-objects).
<br/>
**Run an interactive example and cpu / gpu code comparison below:**
{% include datashader.html %}
<a id='plotly'></a><br/>
<img src="/assets/images/plotly-logo.png" style="width:160px; vertical-align:middle;">
<a href="https://dash.gallery/Portal/" target="_blank" title="plotly dash US Opioid Epidemic demo">
<img src="/assets/images/plotly-dash.png" style="width:230px; display:inline-block; vertical-align:middle; padding-left:20px;"></a>
<br/>
- Plotly provides browser based graphing, analytics, and statistics tools to create powerful applications.
- Read about Plotly's Python charting library at [plotly.com/python/](https://plotly.com/python/) and explore the Plotly Dash gallery [ash.gallery/Portal/](https://dash.gallery/Portal/).
- Read about [RAPIDS compatibility](https://dash.plotly.com/holoviews#gpu-accelerating-datashader-and-linked-selections-with-rapids).
**Run an interactive example and cpu / gpu code comparison below:**
{% include plotly.html %}
<a id='bokeh'></a><br/>
<img src="/assets/images/bokeh-logo.svg" style="width:130px; display:inline-block; vertical-align:middle;">
<a href="https://docs.bokeh.org/en/latest/docs/gallery.html" target="_blank" title="bokeh blackbody radiation chart">
<img src="/assets/images/latex_blackbody_radiation.png" style="width:130px; display:inline-block; vertical-align:middle; padding-left:20px;"></a>
<br/>
- Bokeh makes it simple to create common interactive plots, but also can handle custom or specialized use-cases with tools and widgets.
- Plots, dashboards, and apps can be published in web pages or Jupyter notebooks.
- Read about Bokeh at [bokeh.org/](https://bokeh.org/) and explore its demo page [demo.bokeh.org/](https://demo.bokeh.org/).
- Further [Documentation](https://docs.bokeh.org/en/latest/).
**Run an interactive example and cpu / gpu code comparison below:**
{% include bokeh.html %}
<a id='seaborn'></a><br/>
<img src="/assets/images/seaborn-logo.svg" style="width:200px; display:inline-block; vertical-align:middle;">
<a href="https://seaborn.pydata.org/examples/hexbin_marginals.html" target="_blank" title="seaborn hexbin example">
<img src="/assets/images/hexbin_marginals.png" style="width:130px; display:inline-block; vertical-align:middle; padding-left:20px;"></a>
<br/>
- Seaborn is a Python data visualization library based on [matplotlib](https://matplotlib.org/). It provides a high-level interface for drawing static charts.
- Although not directly accelerated with GPU usage, it provides a base example of using a popular Python based visualization library with RAPIDS.
- Read about Seaborn at [seaborn.pydata.org/](https://seaborn.pydata.org/) and explore its gallery [seaborn.pydata.org/examples/index.html](https://seaborn.pydata.org/examples/index.html).
- Further [Documentation](https://seaborn.pydata.org/api.html).
**Run an interactive example and cpu / gpu code comparison below:**
{% include seaborn.html %}
<br/><br/>
# Other Notable Libraries
<a id='panel'></a><br/>
<img src="/assets/images/panel-logo.png" style="width:100px; display:inline-block; vertical-align:middle;">
<a href="https://panel.holoviz.org/gallery/index.html" target="_blank" title="panel gapminder example">
<img src="/assets/images/gapminders.png" style="width:210px; display:inline-block; vertical-align:middle; padding-left:20px;"></a>
<br/>
- Panel is a Python library that lets you create custom interactive web apps and dashboards by connecting user-defined widgets to plots, images, tables, or text.
- Panel -like holoViews, hvPlot, and datashader- is part of the [HoloViz Ecosystem](https://holoviz.org/).
- Panel works well within the Python visualization ecosystem and is **what powers the interactive tools on this page**.
- Read more about Panel at [panel.holoviz.org/](https://panel.holoviz.org/index.html) and explore its gallery [panel.holoviz.org/reference/](https://panel.holoviz.org/reference/index.html).
- Further [Documentation](https://panel.holoviz.org/user_guide/index.html).
<a id='pydeck'></a><br/>
<img src="/assets/images/pyDeck-logo.svg" style="width:200px; display:inline-block; vertical-align:middle;">
<a href="https://deckgl.readthedocs.io/en/latest/layer.html" target="_blank" title="pydeck example page">
<img src="/assets/images/hexagon-layer.jpg" style="width:140px; display:inline-block; vertical-align:middle; padding-left:20px;"></a>
<br/>
- The pyDeck library is a set of Python bindings for making spatial visualizations with deck.gl, optimized for a Jupyter environment.
- Learn more about its core deck.gl webGL based library a [deck.gl](https://deck.gl/).
- Read about pyDeck at [pydeck.gl/](https://pydeck.gl/) and explore its gallery [pydeck gallery](https://pydeck.gl/#gallery).
- Further [Documentation](https://pydeck.gl/layer.html).
<a id='cuxfilter'></a><br/>
<img src="/assets/images/rapids_logo.png" style="width:150px; display:inline-block; vertical-align:middle;">
<span style="color:#7400ff; font-size:2.5em; vertical-align: middle;">cuxfilter</span>
<a href="https://docs.rapids.ai/api/cuxfilter/nightly/examples/examples.html" target="_blank" title="cuxfilter example page">
<img src="/assets/images/cuxfilter-demo.gif" style="width:220px; display:inline-block; vertical-align:middle; padding-left:20px;"></a>
<br/>
- cuxfilter is a RAPIDS developed cross filtering library which enables GPU accelerated dashboards, using best in class charting libraries, with just a few lines of Python.
- Read about cuxfilter at [github.com/rapidsai/cuxfilter](https://github.com/rapidsai/cuxfilter) and explore its examples [docs.rapids.ai/api/cuxfilter/stable/examples/examples.html](https://docs.rapids.ai/api/cuxfilter/stable/examples/examples.html).
- Further [Documentation](https://docs.rapids.ai/api/cuxfilter/stable/10_minutes_to_cuxfilter.html).
<a id='noderapids'></a><br/>
<img src="/assets/images/rapids_logo.png" style="width:150px; display:inline-block; vertical-align:middle;">
<span style="color:#7400ff; font-size:2.5em; vertical-align: middle;">nodeRAPIDS</span>
<a href="https://github.com/rapidsai/node/tree/main/modules/demo" target="_blank" title="nodeRAPIDS demo page">
<img src="/assets/images/nodeRAPIDS-streaming.png" style="width:200px; display:inline-block; vertical-align:middle; padding-left:20px;"></a>
<br/>
- node RAPIDS brings GPU acceleration to the nodeJS and JS/TypeScript user ecosystem.
- Keep large datasets and complex compute processes in GPU memory while using the browser front end just for performant interactions.
- node RAPIDS is [available on NPM](https://www.npmjs.com/package/@rapidsai/core?activeTab=dependents).
- Read about node RAPIDS at [github.com/rapidsai/node ](https://github.com/rapidsai/node) and explore its demo gallery [github.com/rapidsai/node/tree/main/modules/demo](https://github.com/rapidsai/node/tree/main/modules/demo).
- Further [Documentation](https://rapidsai.github.io/node/).
<br/><br/><br/>
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---
title: FAQ | RAPIDS
description: Frequently Asked Questions
---
<!-- Hero Shortcode -->
{{< hero hero-text="Frequently Asked Questions" button-link="#" button-text="FAQ" >}}
## Question 1
text text
## Question 2
text text
### SubQuestion
text text
<!-- Global JS -->
<script src="/js/main.js"></script>
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rapidsai_public_repos/rapids.ai/content/news/_index.html
|
---
title: News | RAPIDS
description: Latest News about RAPIDS
---
<!-- Hero Shortcode -->
{{< hero hero-text="News" button-link="https://medium.com/rapids-ai" button-text="Medium Blog" >}}
<!-- Intro -->
<section class="section padding-bottom-slant">
<div class="container">
<h1 class="text-center mb-5"> Latest RAPIDS Related News</h1>
<div class="row">
<div class="col-md-4 py-3">
<h2><i class="fa-regular fa-books"></i> Featured Blogs </h2>
<p> Find our highlighted content, including videos, talks, posts, guides and more on the <a href="https://developer.nvidia.com/blog/" target="_blank"> NVIDIA Dev Blog</a> and <a href="https://medium.com/rapids-ai" target="_blank">RAPIDS Blog <i class="fa-solid fa-arrow-up-right"></i></a> </p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-brands fa-twitter"></i> RAPIDS X/Twitter </h2>
<p> Follow the latest from the RAPIDS X/Twitter community. </p>
<a href="https://twitter.com/RAPIDSai" target="_blank">@RAPIDSai <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-triangle-exclamation"></i> Support Notices </h2>
<p> Technical notices for our contributors, core developers, and the general community about important updates.</p>
<a href="https://docs.rapids.ai/notices" target="_blank">Support Notices Page <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
</div>
</div>
</section>
<div class="top-slant-container">
<div class="top-slant-down bg-white"></div>
</div>
<section class="row section padding-bottom-slant">
<div class="col">
<!-- Blog Posts -->
{{< post >}}
</div>
</section>
<!-- Global JS -->
<script src="/js/main.js"></script>
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0021.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 21 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "cuDF v21.12.02 Hotfix Release"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v21.12"
notice_created: 2021-12-16
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-12-16
---
## Overview
`cuDF` was hotfixed to version `v21.12.02`.
## Rationale
`cuDF` was hotfixed to `v21.12.02` in order to fix a performance regression as noted in [#9898](https://github.com/rapidsai/cudf/pull/9898).
## Impact
All v21.12 users are encouraged to update the `cuDF` library to `v21.12.02` as soon as possible.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0027.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 27 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "RAPIDS Docker Run Command Changes in v22.04"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Docker Run Command Change
notice_rapids_version: "v22.04+"
notice_created: 2022-06-08
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
As we expand out further across platforms and GPU architectures, we have
recently identified and updated the RAPIDS docker run with additional
parameters to provide a more stable way to run Multi Node/Multi GPU (MNMG).
The new parameters are `--shm-size=1g --ulimit memlock=-1`. This change is
currently in the RAPIDS Release Selector and will soon be updated in all
docker instructions. We advise everyone to adopt these additional
parameters for when running RAPIDS on Docker, especially if you're running
RAPIDS on `ARM SBSA` with MNMG.
## Status
- **2022-06-08** - This change is currently in the RAPIDS Release Selector
## Impact
Refer to the examples below for a comparison of `old` & `new` docker run commands:
### Example Old Docker Run Command
```
docker run --gpus all --rm -it \
-p 8888:8888 -p 8787:8787 -p 8786:8786 \
rapidsai/rapidsai-core-arm64:22.06-cuda11.5-runtime-ubuntu20.04-py3.9
```
### Example New Docker Run Command
```
docker run --gpus all --rm -it \
--shm-size=1g --ulimit memlock=-1 \
-p 8888:8888 -p 8787:8787 -p 8786:8786 \
rapidsai/rapidsai-core-arm64:22.06-cuda11.5-runtime-ubuntu20.04-py3.9
```
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0006.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 6 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "v0.16 Release Extension"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v0.16"
notice_created: 2020-10-07
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2020-10-07
---
## Overview
The RAPIDS `v0.16` release date has been extended for 1 week to 2020-10-21
## Impact
See our updated [release schedule]({% link maintainers/maintainers.md %}) for
`v0.16`
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0003.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 3 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "v0.15 Release Extension"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v0.15"
notice_created: 2020-08-05
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2020-08-05
---
## Overview
The RAPIDS `v0.15` release date has been extended for 1 week to 26-Aug-2020 to
better support CUDA 11.
## Rationale
Core RAPIDS dependencies like `CuPy` and `Numba` are planning to release stable
or release candidate versions that support CUDA 11 on or around 19-Aug-2020.
Given their release dates are scheduled on the original release date for RAPIDS
`v0.15`, we are extending the release so we can ship with more stable
dependencies instead.
## Impact
See our updated [release schedule]({% link maintainers/maintainers.md %}) for
`v0.15`
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0026.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 26 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "v22.06 Release Update"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v22.06"
notice_created: 2022-06-07
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
22.06 `devel` containers will be released on Wednesday 6/15/22. Conda packages and `base` container release dates will remain unchanged.
## Rationale
22.06 release artifacts will be bifurcated--conda packages and `base` containers (i.e. those other than `devel`) will be released on Wednesday 6/8/22. `devel` containers will be released on Wednesday 6/15/22.
## Impact
N/A
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0028.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 28 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "22.06 Hotfix for `cuda-python` Package"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v22.06.01"
notice_created: 2022-07-07
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2022-07-07
---
## Overview
RAPIDS v22.06 was hotfixed to pin the `cuda-python` package dependency to a maximum version of `11.7.0` for several RAPIDS libraries.
## Rationale
`cuda-python` version `11.7.1` was recently released, which switched its dependency on the [cudatoolkit](https://anaconda.org/nvidia/cudatoolkit) package to the [cuda-toolkit](https://anaconda.org/nvidia/cuda-toolkit) package. This dependency change had unintended consequences for several RAPIDS libraries, including blocking installation for some users.
## Impact
All users are recommended to use the latest `22.06.01` version of all RAPIDS libraries.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0034.md
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---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 34 # should match notice number
notice_pin: true # set to true to pin to notice page
title: "Deprecation announcement for Pascal GPU support in Release v23.12"
notice_author: RAPIDS Ops
notice_status: In Progress
notice_status_color: yellow
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v23.12"
notice_created: 2023-10-04
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-10-04
---
## Overview
RAPIDS team is planning to deprecate support for Pascal GPUs in its `v23.12` release and to remove support in its `v24.02` release. `v23.12` will be the last version of RAPIDS to support Pascal GPUs.
## Impact
Effective RAPIDS `v24.02` release, RAPIDS will no longer support Pascal GPUs. GPUs with Compute Capability 7.0 or higher will be required. Users of Pascal GPUs will be able to continue to use RAPIDS `v23.12`.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0007.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 7 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "RAPIDS docker image changes in v0.17"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Docker Image Change
notice_rapids_version: "v0.17"
notice_created: 2020-12-10
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2020-12-10
---
## Overview
The RAPIDS `v0.17` docker images have been updated to include [BlazingSQL](https://blazingsql.com/)
by default using existing images and tags. New images with the root name of
`rapidsai-core` have been created that only contain RAPIDS libraries.
## Status
- **10-Dec-2020** - Changes have been pushed with the `v0.17` release
## Impact
Refer to the tables below for a comparison of `v0.16` & `v0.17` behavior and options
### Stable (Release) Images
Docker Repo | Image Type | Previous Behavior | v0.17+ Behavior | Options
--- | --- | --- | --- | ---
`rapidsai/rapidsai` | `base` & `runtime` **conda-based** images | ***ONLY*** RAPIDS | RAPIDS ***AND*** BlazingSQL | Switch to `rapidsai/rapidsai-core` for RAPIDS ***ONLY*** images
`rapidsai/rapidsai-dev` | `devel` **from-source** images | ***ONLY*** RAPIDS | RAPIDS ***AND*** BlazingSQL | Switch to `rapidsai/rapidsai-core-dev` for RAPIDS ***ONLY*** images
### Nightly Images
Docker Repo | Image Type | Previous Behavior | v0.17+ Behavior | Options
--- | --- | --- | --- | ---
`rapidsai/rapidsai-nightly` | `base` & `runtime` **conda-based** images | ***ONLY*** RAPIDS | RAPIDS ***AND*** BlazingSQL | Switch to `rapidsai/rapidsai-core-nightly` for RAPIDS ***ONLY*** images
`rapidsai/rapidsai-dev-nightly` | `devel` **from-source** images | ***ONLY*** RAPIDS | RAPIDS ***AND*** BlazingSQL | Switch to `rapidsai/rapidsai-core-dev-nightly` for RAPIDS ***ONLY*** images
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0014.md
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---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 14 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "EOL Python 3.7 in v22.02"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v22.02"
notice_created: 2022-02-03
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
`Python 3.7` has reached end of life (EOL) in RAPIDS `v22.02` and will
not be supported in the `v22.02` stable release nor the upcoming release of `v22.04`. This includes `v22.02`
nightly support which ended on 2022-02-03.
## Status
### Release support - `v22.02`
- Final release of `conda` packages or `docker` images supporting `Python 3.7`
### Nightly support - `v22.04`
- No further `conda` packages or `docker` images supported for `Python 3.7`
### Documentation
- Updates to Docker Hub and NGC repos will be reflected with the `v22.02` release
- Updated [rapids.ai](https://rapids.ai/start#rapids-release-selector) release
selector to reflect EOL changes and available install options
## Impact
Users should migrate to `Python 3.8` or `Python 3.9` for RAPIDS.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0001.md
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---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 1 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Change minimum support gcc/g++ version to 7.5"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v0.15"
notice_created: 2020-07-17
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2020-07-17
---
## Overview
Changes in the `conda-forge` ecosystem forced RAPIDS to change from
`gcc/g++ 7.3` support to `gcc/g++ 7.5` support for `v0.14` and future releases.
## Status
All `conda` and `docker` images use `gcc/g++ 7.5` to ensure compatibility with
`conda-forge`
## Impact
Users building from source should use `gcc/g++ 7.5` or higher to build RAPIDS.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0033.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 33 # should match notice number
notice_pin: true # set to true to pin to notice page
title: "Dropping Support for Ubuntu 20.04 arm64 containers in Release v23.06"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v23.06"
notice_created: 2023-6-14
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-08-17
---
## Overview
Due to a bug in `glibc 2.31` (https://bugzilla.redhat.com/show_bug.cgi?id=1722181) with no current workaround, we are unable to publish `arm64` `ubuntu20.04` containers effective RAPIDS release `23.04`. `x86_64` containers are not affected. More details may be found in the tracking issue: https://github.com/rapidsai/docker/pull/551
## Impact
`arm64` users should migrate to `ubuntu22.04` as soon as possible.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0015.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 15 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Support for Python 3.9 in v22.02"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v22.02+"
notice_created: 2022-02-04
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
With the EOL of `Python 3.7` announced in [RSN 14](/notices/rsn0014), development
effort has been redirected to support `Python 3.9` in `v22.02` stable and `v22.04` nightly releases.
## Status
- `Python 3.9` nightly support started on 04-Feb-2022 for both `conda` and
`docker`
## Impact
Users are encouraged to test nightly `conda` and `docker` builds and report any
issues in their respective repos.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0012.md
|
---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 12 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "cuDF v0.19.2 Hotfix Release"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v0.19"
notice_created: 2021-04-28
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-04-28
---
## Overview
`cuDF` was hotfixed to version `0.19.2`.
## Rationale
`cuDF` was hotfixed to fix a deadlock that could occur in decompression in cuIO, [#8073](https://github.com/rapidsai/cudf/pull/8073).
## Impact
All v0.19 users are encouraged to update `cudf` libraries to `0.19.2` as soon as possible.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0010.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 10 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Support for CUDA 11.4 in v21.08"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v21.08+"
notice_created: 2021-07-09
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
Development effort has begun on supporting `CUDA 11.4` in `v21.08`. Support is currently experimental for `v21.08`. GA for `CUDA 11.4` is expected in `v21.10`
## Impact
Users are encouraged to use `CUDA 11.4` if possible and provide feedback to the RAPIDS libraries as we develop `v21.08`.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0010.md
|
---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 10 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "cuDF v0.18.2 Hotfix Release"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v0.18"
notice_created: 2021-04-15
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-04-22
---
## Overview
`cuDF` was hotfixed to version `0.18.2`.
## Rationale
`cuDF` was hotfixed for a [bug](https://github.com/rapidsai/cudf/issues/7114) in the parquet file reader.
## Impact
All v0.18 users are encouraged to update `cudf` libraries to `0.18.2` as soon as possible.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0015.md
|
---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 15 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "cuDF v21.06.01 Hotfix Release"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v21.06"
notice_created: 2021-06-17
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-06-22
---
## Overview
`cuDF` was hotfixed to version `21.06.01`.
## Rationale
`cuDF` was hotfixed to fix an offset error which could lead to data corruption when writing ORC files with multiple large string columns, [#8538](https://github.com/rapidsai/cudf/pull/8538).
## Impact
All v21.06 users are encouraged to update `cuDF` libraries to `21.06.01` as soon as possible.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0020.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 20 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Please Pin cuda-python to 11.7.0"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v22.02, v22.04, and v22.06"
notice_created: 2022-07-15
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
We have recently become aware that `cuda-python` `11.7.1` has incorporated changes that makes it
incompatible with current and legacy versions of RAPIDS when you try to install RAPIDS. You will
need to pin `cuda-python` to `11.7.0` in conda during installation, and potentially after. An
affected installation with the `11.7.1` issue results in this error being thrown:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/opt/conda/lib/python3.9/site-packages/cudf/__init__.py", line 5, in <module>
validate_setup()
File "/opt/conda/lib/python3.9/site-packages/cudf/utils/gpu_utils.py", line 20, in validate_setup
from rmm._cuda.gpu import (
File "/opt/conda/lib/python3.9/site-packages/rmm/__init__.py", line 16, in <module>
from rmm import mr
File "/opt/conda/lib/python3.9/site-packages/rmm/mr.py", line 14, in <module>
from rmm._lib.memory_resource import (
File "/opt/conda/lib/python3.9/site-packages/rmm/_lib/__init__.py", line 15, in <module>
from .device_buffer import DeviceBuffer
File "device_buffer.pyx", line 1, in init rmm._lib.device_buffer
TypeError: C function cuda.ccudart.cudaStreamSynchronize has wrong signature (expected __pyx_t_4cuda_7ccudart_cudaError_t (__pyx_t_4cuda_7ccudart_cudaStream_t), got cudaError_t (cudaStream_t)
```
## Status
Currently, we have these two resolution paths to offer:
Resolution Path 1: You can upgrade your RAPIDS version to `v22.06.01`.
- We've made it easy to upgrade: simply use our Release selector and install `v22.06` or rerun you `v22.06` installation script. It will automatically grab `v22.06.01` via Conda or Docker.
Resolution Path 2: If you can NOT upgrade, pin `cuda-python` to `11.7.0` in RAPIDS `v22.02`, `v22.04`, and `v22.06`,
- You can pin `cuda-python` to `11.7.0` by using `cuda-python=11.7.0` when doing an install.
- Example command: `conda install -c nvidia cuda-python=11.7.0`.
Older versions of RAPIDS may also be affected and users should attempt to upgrade or pin.
## Impact
This issue impacts users installing conda packages of RAPIDS 22.02 through 22.06,
which depend on `cuda-python`. This issue also affects existing conda installations of
RAPIDS versions 22.02 - 22.06 if the user installs additional packages depending on
`cuda-python` that result in an update to `cuda-python>11.7.0`.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0017.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 17 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Deprecation announcement for CUDA 11.0 in v22.06"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v22.06+"
notice_created: 2022-06-08
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2022-06-08
---
## Overview
`CUDA 11.0` will be deprecated in our upcoming release of `v22.06`
scheduled for June 2022. After the `v22.06` release, users should expect
that support for `CUDA 11.0` may be dropped at any point.
## Impact
Users should plan to move to `CUDA 11.2+` as soon as possible or update their driver
to `r450.80.02` or higher to take advantage of the CUDA Enhanced Compatibility capability. Future
support of additional `CUDA 11.X` versions are being worked on for upcoming
releases. Further details will be shared in RSN notices as they become
available.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0001.md
|
---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 1 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Stable/Release Branch Renaming to 'main' in v0.15"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Git Repo Change
notice_rapids_version: "v0.15"
notice_created: 2020-07-13
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2020-08-28
---
## Overview
RAPIDS has decided to follow other Open Source projects in renaming their
"default" git branch to `main`. Starting with the `v0.15` release, the existing
RAPIDS stable/release branch will be removed and all references should use the
`main` branch going forward.
>**NOTE:** RAPIDS uses `branch-X.Y` as our GitHub default branch for
development; however, our stable/release branch is typically the "default"
branch for others and new git projects.
For more information read the [GitHub docs](https://github.com/github/renaming/)
detailing their plan for renaming branches.
## Status
### Updates
- **10-Jul-2020** - `main` branches were added to all repos with an existing
stable/release branch
- **15-Jul-2020** - Documentation with outdated references were updated with PRs
to `main`
- **Completed** - PRs to update scripts and other mentions will be merged into
`branch-0.15` and then into `main`
- **26-Aug-2020** - Release `v0.15` occurred and using the `main` branch
- **28-Aug-2020** - Renaming complete, old branches removed
## Impact
Any other projects or developers referring to our current stable/release branch
will no longer work or may redirect incorrectly. This includes search and web
links that link to GitHub.
From the [GitHub docs](https://github.com/github/renaming/) on renaming, there
will be some redirects in place; however, they will redirect to the GitHub
"default" branch which in our case means links to stable/release will redirect
to our development branch. This may cause some confusion, but we will do our
best to ensure the links are updated.
Users that find outdated links should open an issue in the repo they have been
found. For updates on this docs site or [rapids.ai](https://rapids.ai), file an
issue [here](https://github.com/rapidsai/docs/issues/new/choose).
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0021.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 21 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "EOL for CUDA 11.0 in v22.10"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v22.10"
notice_created: 2022-10-05
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
`CUDA 11.0` is now end of life (EOL) in RAPIDS v22.10 and will not be supported in the v22.10 stable release nor the upcoming release of v22.12. This includes v22.10 nightly support which ended on 2022-10-13.
## Impact
Users should migrate to CUDA 11.2, 11.4 or 11.5 for RAPIDS.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0032.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 32 # should match notice number
notice_pin: true # set to true to pin to notice page
title: "Deprecation announcement for cuSignal"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v23.08"
notice_created: 2023-05-26
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-08-17
---
## Overview
The RAPIDS cuSignal repository is integrating into the CuPy repository and will be deprecated in 3 to 4 months. We are tentatively targeting the v23.08 release scheduled for August 10, 2023 as the final release of RAPIDS cuSignal. After the v23.08 release, this repository will be archived during the v23.10 development cycle.
## Impact
Users should prepare to migrate to CuPy, which will include cuSignal functionality: https://github.com/cupy/cupy
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rapidsai_public_repos/rapids.ai/content/news/notices/rdn0002.md
|
---
layout: notice
parent: RAPIDS Developer Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rdn
# Update meta-data for notice
notice_id: 2 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Updates to from-source builds with conda for gcc '7.5.0'"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Build Change
notice_rapids_version: "v0.18"
notice_created: 2021-02-11
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-02-11
---
## Overview
Recently `conda-forge` has switched to publish conda packages using the gcc/g++
`9.3.0` build stack. RAPIDS `v0.18` has also switched to this build stack for
our conda dependencies resulting in the following changes for developers.
## Impact
All from-source builds with conda dependencies for CUDA `10.1/10.2/11.0` using
gcc `7.5.0` are affected and need changes to successfully build RAPIDS `v0.18+`
>**NOTE:** CUDA `11.0` RAPIDS from-source builds with conda dependencies using
gcc `9.3.0` are not impacted (CUDA `10.1/10.2` **do not** support gcc `9.3.0`
for builds)
### Ubuntu 16.04/18.04/20.04
For all Ubuntu versions, we use this PPA to install gcc `7.5.0` and update the
alternatives to set it as the default compiler:
```
sudo apt-get update
sudo apt-get install -y software-properties-common
sudo add-apt-repository -y ppa:ubuntu-toolchain-r/test
sudo apt-get update
sudo apt-get install -y gcc-7 g++-7 libstdc++6
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-7 7
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-7 7
sudo update-alternatives --set gcc /usr/bin/gcc-7
sudo update-alternatives --set g++ /usr/bin/g++-7
```
>**NOTE:** The docker equivalent for this code can be found [here](https://github.com/rapidsai/gpuci-build-environment/blob/branch-0.18/rapidsai/devel.Dockerfile#L58-L68)
With the install of gcc `7.5.0` and an updated `libstdc++6` pkg, you should be
able to build RAPIDS from-source with conda dependencies. If you encounter any
`GLIBC` errors during the build process, be sure the check the version of the
`libstdc++6` package outlined below.
**Check `libstdc++6` package version**
In order to build with conda dependencies from `conda-forge` the installed
`libstdc++6` package must be `>= 9.3.0`. You can verify the current installed
version and available version through the following commands:
```
sudo apt-get update
sudo apt-cache policy `libstdc++6`
```
If the version is not `>= 9.3.0` install the package again to update it:
```
sudo apt-get install libstdc++6
```
### CentOS 7/8 or RHEL 7/8
For CentOS and RHEL we [build](https://github.com/rapidsai/gpuci-build-environment/blob/branch-0.18/builds-gcc7/Dockerfile.centos7)
gcc `7.5.0` from source for our docker images and make it available as a
tarball. Our public tarball is now patched to include a version of `libstdc++`
from a gcc `9.3.0` build that allows from-source builds of RAPIDS with conda
dependencies to work.
**Installing our patched gcc `7.5.0`**
Download and extract the tarball to the target machine or docker image. The
tarball is meant to be extracted from the root and extracts into the following
path: `/usr/local/gcc7`
```
sudo wget --quiet https://gpuci.s3.us-east-2.amazonaws.com/builds/gcc7.tgz -O /gcc7.tgz
sudo tar xzf /gcc7.tgz
sudo rm -f /gcc7.tgz
```
>**NOTE:** The docker equivalent for this code can be found [here](https://github.com/rapidsai/gpuci-build-environment/blob/branch-0.18/rapidsai/devel-centos7.Dockerfile#L118-L120)
Once extracted, setup the environment variables to enable the use of the
installed gcc `7.5.0`:
```
export GCC7_DIR=/usr/local/gcc7
export CC=${GCC7_DIR}/bin/gcc
export CXX=${GCC7_DIR}/bin/g++
export CUDAHOSTCXX=${GCC7_DIR}/bin/g++
export CUDA_HOME=/usr/local/cuda
export LD_LIBRARY_PATH=${GCC7_DIR}/lib64:$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/lib
export PATH=${GCC7_DIR}/bin:$PATH
```
>**NOTE:** The docker equivalent for this code can be found [here](https://github.com/rapidsai/gpuci-build-environment/blob/branch-0.18/rapidsai/devel-centos7.Dockerfile#L18-L24)
From here all `./build.sh` scripts in RAPIDS repos should build without error.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0013.md
|
---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 13 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "RAPIDS switching to CalVer in v0.20 (now v21.06)"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Version Change
notice_rapids_version: "v0.20 / v21.06"
notice_created: 2021-05-05
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-05-17
---
## Overview
All RAPIDS projects are switching their versioning scheme to [Calendar Versioning](https://calver.org).
This versioning will apply to both the overall RAPIDS release and each core library, so we will release `cuDF` `21.06.00`, `cuML` `21.06.00`, etc. as part of the overall RAPIDS `21.06.00` release.
## Impact
Instead of a `0.20.0` release in June 2021, we will release `21.06.00`
New version format for release: `YY.MM.PP`, for example `21.06.00`
New version format for nightlies: `YY.MM.PPaYYMMDD`, for example `21.06.00a210505`
Where `PP` is the two digit patch number not day.
ABI & API compatibility will be maintained within each `YY.MM.xx` release.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0030.md
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---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 30 # should match notice number
notice_pin: true # set to true to pin to notice page
title: "Docker Image Changes in Release v23.08"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v23.08"
notice_created: 2023-04-20
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-08-17
---
## Overview
The RAPIDS 23.08 release has made changes to end-user Docker images to improve functionality, performance, and maintainability.
While many of these changes should be seamless to users, **some of them are breaking**. Users should review the full list of changes in the associated issue: [https://github.com/rapidsai/docker/issues/539](https://github.com/rapidsai/docker/issues/539)
## Impact
Users should be particularly aware of the breaking changes as noted above.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0002.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 2 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "EOL Python 3.6 & CUDA 10.0 in v0.14"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v0.14 & v0.15"
notice_created: 2020-07-13
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2020-07-13
---
## Overview
`Python 3.6` and `CUDA 10.0` have reached end of life (EOL) in RAPIDS `v0.14`
and will not be supported in the upcoming release of `v0.15`. This includes
`v0.15` nightly support which ended on 13-Jul-2020.
## Status
### Nightly support
- Has ended as of **13-Jul-2020**
- No further `conda` packages or `docker` images will be released for these
versions
### Documentation
- Updates to Docker Hub and NGC repos will be reflected with the `v0.15` release
- Updated [rapids.ai](https://rapids.ai/start#rapids-release-selector) release
selector to reflect EOL
## Rationale
### Python 3.6 EOL
Due to [NEP 29](https://numpy.org/neps/nep-0029-deprecation_policy.html) support
for `Python 3.6` in a large number of our dependent libraries was removed in
late June 2020. Some libraries are continuing to publish `Python 3.6` packages;
however, others are working towards discontinuing them in the near future.
Given the push of the community to focus on `Python 3.7 & 3.8` we opted to spend
our resources on `Python 3.8` bring up for `v0.15`. See [RSN 3](/notices/rsn0003)
for updates.
### CUDA 10.0 EOL
Given community input and the release of `CUDA 11.0`, the team has opted to EOL
`CUDA 10.0` in favor of bring up for ***beta*** support of `CUDA 11.0` in
`v0.15`. See [RSN 4](/notices/rsn0004) for updates.
## Impact
Users should migrate to `Python 3.7` & `CUDA 10.1` our new defaults for RAPIDS.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0029.md
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---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 29 # should match notice number
notice_pin: true # set to true to pin to notice page
title: "Dropping Python v3.8 in v23.06"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v23.06"
notice_created: 2023-04-20
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-08-17
---
## Overview
Python 3.8 support will be dropped in the upcoming release of v23.06, scheduled for June 2023. Python 3.9 support will be added at the same time, so that v23.06 will support Python 3.9 and 3.10.
## Impact
Users should plan to move to a supported Python version 3.9 and/or 3.10 as soon as possible.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0031.md
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---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 31 # should match notice number
notice_pin: true # set to true to pin to notice page
title: "CUDA 12 pip Wheels Release in v23.06"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v23.06"
notice_created: 2023-05-16
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-08-17
---
## Overview
RAPIDS packages that build pip wheels (rmm, cudf, raft, cuml, cugraph, cuopt, ucx-py) are now building pip wheels with CUDA 12 support. We plan to release these packages in release v23.06.
CUDA 12 wheels are named with a `-cu12` suffix to distinguish them from CUDA 11 wheels which have a `-cu11` suffix.
## Impact
Users should be aware we now are building pip wheels with CUDA 12 support as noted above.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0023.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 23 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "New 'Try RAPIDS Now' Capability via SageMaker Studio Labs in Beta"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Announcement
notice_rapids_version: "v22.02+"
notice_created: 2022-02-17
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
SageMaker Studio Labs has been added as a new "Try it Now" capability for all Stable (`v22.02`), Nightly (`v22.04`),
and Legacy (`v21.12`) RAPIDS installations. [Open in SageMaker Studio Lab buttons and links](https://rapids.ai/smsl)
can be found in the Getting Started sections of our Website.
[A new, quick-start repository](https://github.com/rapidsai-community/rapids-smsl) can be found in RAPIDS community
with further installation instructions. You can only try RAPIDS in SageMaker Studio Lab after you have
[successfully created a SageMaker Studio Lab account](https://studiolab.sagemaker.aws/). Please share any issues you face in the
[rapids-smsl repo](https://github.com/rapidsai-community/rapids-smsl) and feedback in the
[RAPIDS GoAI Slack](https://join.slack.com/t/rapids-goai/shared_invite/zt-trnsul8g-Sblci8dk6dIoEeGpoFcFOQ)!
## Status
- **12-Feb-2022** - Appropriate links to SageMaker Studio Lab have been added. Quick Start Repository has been made.
## Impact
Users continue to have Try RAPIDS Now options for Stable (`v22.02`), Nightly (`v22.04`),
and Legacy (`v21.12`) RAPIDS versions.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0029.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 29 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "RAPIDS v22.10.01 Hotfix Release"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v22.10.01"
notice_created: 2022-11-09
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
RAPIDS v22.10 was hotfixed to version v22.10.01 to update `cuda-python` and `cupy` dependencies.
## Rationale
`cuda-python` version requirement was updated to `>=11.7.1` to resolve errors on CPU-only machines or machines without CUDA installed. Additionally, the `cupy` dependency for pip packages was changed to `cupy-cuda11x` to resolve installation issues for some users.
## Impact
All users are recommended to use the latest `22.10.01` version of `rmm`, `cuDF`, `cuML`, `cuGraph`, and `cuGraph-ops`.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0011.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 11 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "cuDF & cuXfilter v0.19.1 Hotfix Release"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v0.19"
notice_created: 2021-04-22
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-04-22
---
## Overview
Both `cuDF` and `cuXfilter` were hotfixed to version `0.19.1`.
## Rationale
`cuDF` was hotfixed for two bugs: [#8023](https://github.com/rapidsai/cudf/issues/8023) [#8031](https://github.com/rapidsai/cudf/pull/8031).
`cuXfilter` was hotfixed to resolve a [dependency conflict](https://github.com/rapidsai/cuxfilter/pull/271).
## Impact
All v0.19 users are encouraged to update `cudf` & `cuxfilter` libraries to `0.19.1` as soon as possible.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0012.md
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---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 12 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "SQL migration in v21.12"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v21.12+"
notice_created: 2021-10-13
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2022-02-17
---
## Overview
RAPIDS will preview its migration path from BlazingSQL to dask-based SQL in 21.12
## Impact
21.12 will contain a preview of a migration path for users to use RAPIDS with dask-based SQL
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0016.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 16 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "cuCIM and cuDF 21.08.01 Hotfix Release"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v21.08"
notice_created: 2021-08-09
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-08-09
---
## Overview
`cuCIM` and `cuDF` were hotfixed to version `21.08.01`.
## Rationale
`cucim` was hotfixed to `21.08.01` in order to ensure the compiler stack aligned with the rest of RAPIDS, [#84](https://github.com/rapidsai/cucim/pull/84).
`cudf` was hotfixed to `21.08.01` in order to fix the bug, [#8984](https://github.com/rapidsai/cudf/pull/8984) and performance degradation in concatenate for string columns, [#8968](https://github.com/rapidsai/cudf/pull/8968).
## Impact
All v21.08 users are encouraged to update `cuCIM` and `cuDF` libraries to `21.08.01` as soon as possible.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0020.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 20 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "cuDF v21.12.01 Hotfix Release"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v21.12"
notice_created: 2021-12-09
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-12-09
---
## Overview
`cuDF` was hotfixed to version `v21.12.01`.
## Rationale
`cuDF` was hotfixed to `v21.12.01` in order to fix the bug, [#9868](https://github.com/rapidsai/cudf/issues/9868).
## Impact
All v21.12 users are encouraged to update the `cuDF` library to `v21.12.01` as soon as possible.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0014.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 14 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "cuML v21.06.02 Hotfix Release"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v21.06"
notice_created: 2021-06-10
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-06-22
---
## Overview
`cuML` was hotfixed to version `21.06.02`.
## Rationale
`cuML` was hotfixed (`21.06.01`) to fix a bug with batch sizes larger than 32 bits, [#3971](https://github.com/rapidsai/cuml/pull/3971).
`cuML` was hotfixed (`21.06.02`) to fix a bug with missing OpenMP support, [#3988](https://github.com/rapidsai/cuml/issues/3988).
## Impact
All v21.06 users are encouraged to update `cuML` libraries to `21.06.02` as soon as possible.
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rapidsai_public_repos/rapids.ai/content/news/notices/rdn0003.md
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---
layout: notice
parent: RAPIDS Developer Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rdn
# Update meta-data for notice
notice_id: 3 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Devel Container Release Change"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v21.12"
notice_created: 2021-11-18
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
Effective with the `21.12` release, RAPIDS `devel` packages will only be distributed for CUDA `11.5`.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0002.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 2 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "v0.15 No CUDA 11 Release for 'clx'"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v0.15"
notice_created: 2020-08-03
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2020-08-26
---
## Overview
`clx` depends on PyTorch `v1.6` which does not have `CUDA 11.0` support
currently. The `v0.15` release of `clx` will only support `CUDA 10.1` &
`CUDA 10.2`.
## Status
- **26-Aug-2020** - Released `CUDA 10.1` and `CUDA 10.2` support for `clx`
## Impact
Users are encouraged to use nightly `conda` packages in `v0.16` when `CUDA 11`
support is available.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0019.md
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---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 19 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Stop supporting `CentOS 8` in v22.08"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v22.08"
notice_created: 2022-06-08
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
`CentOS 8` is now at end-of-life, which means RAPIDS will no longer publish any images built on `CentOS 8` following the RAPIDS `v22.06` release.
Additionally, gpuCI CPU builds will be converted over to use `Rocky 8.6` instead of `CentOS 8`.
## Status
Support for `CentOS 8` has ended. RAPIDS `v22.06` is the last version to support `CentOS 8`.
## Impact
Users should consider switching to any of the following container OSes:
- Ubuntu 18.04
- Ubuntu 20.04
- Rocky 8.6
- CentOS 7
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0013.md
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---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 13 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Deprecation announcement for Python v3.7 in v21.12"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v21.12+"
notice_created: 2021-11-16
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2022-02-03
---
## Overview
`Python 3.7` will be deprecated in our upcoming release of `v21.12`
scheduled for December 2021. After the `v21.12` release, users should expect
that support for `Python 3.7` may be dropped at any point.
## Impact
Users should plan to move to `Python 3.8` as soon as possible. Future
support of additional `Python 3.9` version is being worked on for upcoming
releases. Further details will be shared in RSN notices as they become
available.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0004.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 4 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "v0.15 Release Delay for 'cuxfilter'"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v0.15"
notice_created: 2020-08-26
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2020-09-08
---
## Overview
`cuxfilter` depends on Numba `v0.51`. Currently there is only `v0.51.0` there
are known issues with this release for other RAPIDS libraries and we need to
wait for `v0.51.1` to release `cuxfilter`.
## Status
- **26-Aug-2020** - Released RAPIDS `v0.15` without `cuxfilter`
- **08-Sept-2020** - Re-released RAPIDS `v0.15` with `cuxfilter`
## Impact
Users are encouraged to use the previous version of `cuxfilter` from `v0.15`
until this is resolved.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0016.md
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---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 16 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Support for ARM SBSA in v22.04"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v22.04+"
notice_created: 2022-04-15
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
Announcing support of `ARM SBSA` in `v22.04`. ARM users will be able to install RAPIDS via
our `conda` and `docker` channels. This support does not yet extend to `NVIDIA Jetson` products.
See our [release blog for installation details](https://medium.com/rapids-ai/rapids-release-22-04-fe4f1913f29b)s.
## Status
- `ARM SBSA` stable and nightly support started on 08-Apr-2022 for both `conda` and
`docker`
## Impact
Users are encouraged to test nightly `conda` and `docker` builds and report any
issues in their respective repos.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0009.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 9 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "v0.19 Release Extension"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v0.19"
notice_created: 2021-04-14
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-04-14
---
## Overview
The RAPIDS `v0.19` release date has been extended for 1 week to 21-Apr-2021.
## Rationale
The release is being extended in order to fix a [bug](https://github.com/rapidsai/cudf/issues/7114) in the parquet file reader.
## Impact
See our updated [release schedule]({% link maintainers/maintainers.md %}) for `v0.19`
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0019.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 19 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "CUDA Enhanced Compatibility"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Build Change
notice_rapids_version: "v21.12"
notice_created: 2021-11-18
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
RAPIDS `21.12` packages will be built using the latest `11.5` version of `nvcc` and the CUDA runtime and distributed for use with any CUDA driver `>=450.80.02` via the use of CUDA Enhanced Compatibility. We strongly recommend using the CUDA `11.5` runtime. Any runtime `>=11.0` and `<11.5` is supported on a best-effort basis.
## Impact
One limitation this poses for users running older minor versions of the CUDA runtime is that the use of `debug=True` with the numba `@cuda.jit` decorator will result in a runtime error. Users running `11.5` will still be able to use `debug=True`.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0022.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 22 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Google Colab RAPIDS support limited to RAPIDS v21.12"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Breaking Change
notice_rapids_version: "v22.02+"
notice_created: 2022-02-17
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2022-02-17
---
## Overview
RAPIDS `v22.02` requires Python `3.8+`; Google Colab is currently limited to
Python `3.7`. Google Colab will only support up to RAPIDS `v21.12` until
Colab support for Python `3.8+` is complete. Users may make use of [SageMaker
Studio Labs as an alternative "Try it Now"](/notices/rgn0023) for Stable (`v22.02`), Nightly (`v22.04`),
and Legacy (`v21.12`) RAPIDS trials.
**NOTE:** Refer to [RSN 14](/notices/rsn0014) for more information about EOL support
of Python `3.7`.
## Status
- **12-Feb-2022** - Warnings have been added to links to Colab on RAPIDS
website; links to SageMaker Studio Lab have been added.
## Impact
Google Colab support for RAPIDS is currently limited to RAPIDS version `v21.12`.
Users can use SageMaker Studio Lab for all Stable (`v22.02`), Nightly (`v22.04`),
and Legacy (`v21.12`) RAPIDS versions.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0007.md
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---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 7 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Support for CUDA 11.2 in v0.19"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v0.19+"
notice_created: 2021-04-21
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-04-21
---
## Overview
With the EOL of `CUDA 10.X` announced in [RSN 6](/notices/rsn0006), development
effort has been redirected to support `CUDA 11.2` in `v0.19` and `v0.20`.
## Impact
Users are encouraged to use `CUDA 11.2` if possible and provide feedback to the
RAPIDS libraries as we develop `v0.20`.
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rapidsai_public_repos/rapids.ai/content/news
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0025.md
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---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 25 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Support for Ubuntu 22.04 in v23.02"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v22.12"
notice_created: 2022-11-21
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
RAPIDS is planning GA support for `Ubuntu 22.04` in its `v23.02` release. `Ubuntu 22.04` will replace the `Ubuntu 18.04` OS distributions for future RAPIDS releases. Experimental support will begin in `v23.02` nightlies.
## Impact
`Ubuntu 18.04` users are encouraged to migrate to a supported version of Ubuntu as soon as possible.
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rapidsai_public_repos/rapids.ai/content/news
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0028.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 28 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Deprecation announcement for CLX RAPIDS Repository"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v23.04"
notice_created: 2023-02-17
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
RAPIDS CLX repository will be deprecated in our upcoming release of v23.04 scheduled for April 13 2023. After the v23.04 release, this repository will be archived during v23.06 release. v23.04 will be the final release of RAPIDS CLX.
## Impact
Users may wish to migrate to Morpheus, which includes much of the CLX functionality: https://github.com/nv-morpheus/Morpheus
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rapidsai_public_repos/rapids.ai/content/news
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0008.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 8 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "v0.18 Release Extension"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v0.18"
notice_created: 2021-02-11
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-02-11
---
## Overview
The RAPIDS `v0.18` release date has been extended to 2021-02-24 due to issues
encountered in [RDN 2](/notices/rdn0002)
## Impact
- See our updated [release schedule]({% link maintainers/maintainers.md %}) for
`v0.18`
- Refer to [RDN 2](/notices/rdn0002) for more details on gcc `7.5.0`
from-source build changes needed in `v0.18+`
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rapidsai_public_repos/rapids.ai/content/news
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0017.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 17 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Hotfix 21.08 release for five libraries"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v21.08"
notice_created: 2021-08-09
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-08-09
---
## Overview
Four RAPIDS libraries were hotfixed to version `21.08.01` and cuDF was hotfixed to version `21.08.02`.
## Rationale
`rmm`, `cuml`, `cugraph`, and `cuspatial` were hotfixed to `21.08.01`. `cudf` was hotfixed to `21.08.02`. These five libraries were hotfixed in order to fix the conda package location of the CMake configuration files, [#56](https://github.com/rapidsai/rapids-cmake/issues/56).
## Impact
All v21.08 users are encouraged to update `rmm`, `cuml`, `cugraph`, and `cuspatial` libraries to `21.08.01` and `cuDF` to `21.08.02` as soon as possible.
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rapidsai_public_repos/rapids.ai/content/news/notices/rdn0001.md
|
---
layout: notice
parent: RAPIDS Developer Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rdn
# Update meta-data for notice
notice_id: 1 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "'dask-xgboost' is deprecated in v0.15 & removed v0.16"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Library Deprecation
notice_rapids_version: "v0.15"
notice_created: 2020-08-26
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2020-08-26
---
## Overview
[`rapidsai/dask-xgboost`](https://github.com/rapidsai/dask-xgboost) is
deprecated in `v0.15` and will be removed in `v0.16`. As of release 1.0, XGBoost
provides a native [Dask API](https://xgboost.readthedocs.io/en/latest/tutorials/dask.html).
The native XGBoost API has all of the functionality of dask-xgboost, combined
with an updated, clean API and much more extensive testing. All users are
encouraged to switch to the native API. See also this [blog post](https://medium.com/rapids-ai/a-new-official-dask-api-for-xgboost-e8b10f3d1eb7)
for an overview.
## Status
- Added a [deprecation warning](https://github.com/rapidsai/dask-xgboost/pull/4/files)
to the RAPIDS [`rapidsai/dask-xgboost`](https://github.com/rapidsai/dask-xgboost)
repo
## Impact
Any other projects or developers using our version of `rapidsai/dask-xgboost`
should switch to the upstream repo [dask/dask-xgboost](https://github.com/dask/dask-xgboost)
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0005.md
|
---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 5 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Google Colab RAPIDS support limited to RAPIDS 0.14"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Breaking Change
notice_rapids_version: "v0.15"
notice_created: 2020-09-11
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2020-09-15
---
## Overview
RAPIDS `0.15` requires Python `3.7+`; Google Colab is currently limited to
Python `3.6`. Google Colab will only support up to RAPIDS `0.14` until
Colab support for Python `3.7+` is complete. Users may make use of BlazingSQL
Notebooks at <http://app.blazingsql.com> for RAPIDS `0.15` support.
**NOTE:** Refer to [RSN 2](/notices/rsn0002) for more information about EOL support
of Python `3.6` & CUDA `10.0`
## Status
- **11-Sep-2020** - Warnings have been added to links to Colab on RAPIDS
website; links to BlazingSQL Notebooks have been added.
## Impact
Google Colab support for RAPIDS is currently limited to RAPIDS version `0.14`.
Users can use BlazingSQL Notebooks for RAPIDS `0.15`.
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rapidsai_public_repos/rapids.ai/content/news
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0011.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 11 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Minimum driver requirement for CUDA 11.0 in v21.12"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v21.12+"
notice_created: 2021-10-12
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-10-12
---
## Overview
We are increasing the minimum driver version for RAPIDS CUDA 11.0 to 450.80.02+ in order to support CUDA Enhanced Compatibility
## Impact
Users should upgrade their driver to `450.80.02` or newer to continue using RAPIDS in the future
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rapidsai_public_repos/rapids.ai/content/news
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0005.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 5 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Deprecation announcement for CUDA 10.1 & 10.2 in v0.19"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v0.19+"
notice_created: 2021-02-25
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-02-25
---
## Overview
`CUDA 10.1` & `10.2` will be deprecated in our upcoming release of `v0.19`
scheduled for April 2021. After the `v0.19` release, users should expect
that support for `CUDA 10.X` may be dropped at any point.
## Impact
Users should plan to move to `CUDA 11.0+` as soon as possible. Future
support of additinal `CUDA 11.X` versions are being worked on for upcoming
releases. Further details will be shared in RSN notices as they become
available.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0024.md
|
---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 24 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Updated WSL2 Installation Method"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Breaking Change
notice_rapids_version: "v22.02+"
notice_created: 2022-02-17
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
The installation method for a RAPIDS compatible WSL2 instance has changed with the release of NVIDIA's WSL2
capable Windows 11 Production Drivers. If you already have RAPIDS running on WSL2, Please
[update your Windows drivers](https://www.nvidia.com/Download/index.aspx?lang=en-us)
accordingly for continued EA support with RAPIDS `v22.02`. If you are installing RAPIDS inside WSL2 for the
first time, please follow the updated instructions below:
1. Please follow the steps in this MS Blog to install WSL2: https://docs.microsoft.com/en-us/windows/wsl/install
2. Install the latest Windows 11 production drivers on the host machine, which are WSL2 capable: https://www.nvidia.com/Download/index.aspx?lang=en-us
3. Inside WSL2:
a. Install conda or docker environments
b. Install RAPIDS as normal with your environment options of choice.
This makes a complete RAPIDS installation far easier in WSL2. Please do not install any additional NVIDIA drivers, neither GPU nor CUDA, inside your WSL2 instance as it is no longer necessary. CUDA Toolkit (CTK) will be installed when you install RAPIDS in your desired environment.
## Status
- **12-Feb-2022** - EA support continues.
## Impact
Users intending to run RAPIDS `v22.02+` in WSL2 should update their systems in accordance with this updated installation guide.
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0025.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 25 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "rmm v22.04.01 Hotfix Release"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v22.04"
notice_created: 2022-04-15
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
`rmm` was hotfixed to version `v22.04.01`.
## Rationale
`rmm` was hotfixed to `v22.04.01` in order to fix a packaging issue as noted in [#1024](https://github.com/rapidsai/rmm/pull/1024).
## Impact
All v22.04 users are encouraged to update the `rmm` library to `v22.04.01` as soon as possible.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0006.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 6 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "EOL CUDA 10.1 & 10.2 in v0.19"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v0.19 & v0.20"
notice_created: 2021-04-21
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-04-21
---
## Overview
`CUDA 10.1` & `10.2` have reached end of life (EOL) in RAPIDS `v0.19` and will
not be supported in the upcoming release of `v0.20`. This includes `v0.20`
nightly support which ended on 2021-04-05.
## Status
### Release support - `v0.19`
- Final release of `conda` packages or `docker` images supporting `CUDA 10.X`
### Nightly support - `v0.20`
- No further `conda` packages or `docker` images supporting for `CUDA 10.X`
### Documentation
- Updates to Docker Hub and NGC repos will be reflected with the `v0.19` release
- Updated [rapids.ai](https://rapids.ai/start#rapids-release-selector) release
selector to reflect EOL changes and available install options
## Impact
Users should migrate to `CUDA 11.0` or `11.2` for RAPIDS.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0009.md
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---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 9 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Stop supporting Ubuntu 16.04 in v21.08"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v21.08"
notice_created: 2021-05-05
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
Ubuntu 16.04 is now at end-of-life, which means RAPIDS will no longer publish any images built on Ubuntu 16.04.
Additionally, gpuCI CPU builds will be converted over to use CentOS 7 instead of Ubuntu 16.04.
## Status
Dropping full support for Ubuntu 16.04 is an ongoing effort.
## Impact
Users should consider switching to any of the following supported operating systems for any `rapidsai/rapidsai` image:
- Ubuntu 18.04
- Ubuntu 20.04
- CentOS 7
- CentOS 8
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rapidsai_public_repos/rapids.ai/content/news/notices/rgn0018.md
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---
layout: notice
parent: RAPIDS General Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rgn
# Update meta-data for notice
notice_id: 18 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Hotfix 21.10 release for RMM and cuDF"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Release Change
notice_rapids_version: "v21.10"
notice_created: 2021-10-11
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-10-11
---
## Overview
`rmm` and `cuDF` libraries were hotfixed to version `21.10.01`.
## Rationale
`rmm` and `cuDF` were hotfixed to resolve conda packaging issue observed with third-party files
## Impact
The fix moves the third-party cmake files from `lib64` to `lib` subdirectory
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rapidsai_public_repos/rapids.ai/content/news/notices/_index.md
|
---
cascade:
draft: true
---
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rapidsai_public_repos/rapids.ai/content/news
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0026.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 26 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Support for 22.10 cuml/cugraph Users"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v22.10"
notice_created: 2022-12-14
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
RAPIDS 22.10 cuML and cuGraph users will need to add `libcusparse<12` `libcusolver<=11.4.1.48` to conda install commands for installing cuML or cuGraph.
### Example
```
conda create -n rapids-22.10 -c rapidsai -c conda-forge -c nvidia cugraph=22.10 python=3.8 cudatoolkit=11.5 libcusparse<12 libcusolver<=11.4.1.48
```
## Impact
Impact is limited to RAPIDS 22.10 `cuml` and `cugraph` users.
## Background
Since the release of RAPIDS 22.10, some packages that cuML and cuGraph depend on have upgraded and introduced incompatibilities. Conda will install these newer dependencies by default when installing 22.10 cuML or cuGraph, which will result in runtime errors such as:
`error while loading shared libraries: libnvJitLink.so.12: cannot open shared object file: No such file or directory`
In order to restrict conda to installing only compatible versions of these dependencies, the workaround above should be applied. This workaround is not needed for RAPIDS releases 22.12 and beyond.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0022.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 22 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Deprecation announcement for Python v3.9 in v22.12"
notice_author: RAPIDS TPM
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v22.12+"
notice_created: 2022-11-21
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
Python 3.9 will be deprecated in our upcoming release of v22.12 scheduled for December 2022. After the v22.12 release, users should expect that support for Python 3.9 may be dropped at any point.
## Impact
Users should plan to move to a supported Python version as soon as possible. Support for Python 3.8 is being maintained, and support for Python 3.10 is being targeted for RAPIDS 23.02 (see [RSN 23](/notices/rsn0023)).
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0027.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 27 # should match notice number
notice_pin: true # set to true to pin to notice page
title: "Deprecation announcement for CUDA 11.4 and 11.5 containers"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v23.04+"
notice_created: 2023-03-08
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-08-17
---
## Overview
RAPIDS is deprecating `CUDA 11.4` and `CUDA 11.5` containers effective its `v23.04` release. RAPIDS will plan to EOL these containers in a future release (currently targeting `v23.06`), at which point `CUDA 11.4` and `CUDA 11.5` containers will no longer be published.
## Impact
Once these containers reach EOL (currently targeting `v23.06` release), RAPIDS will no longer publish these containers. Note that conda packages will still support `CUDA 11.4` and `CUDA 11.5` due to CUDA Enhanced Compatibility.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0004.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 4 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Support for CUDA 11.0 in v0.15"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v0.15"
notice_created: 2020-07-13
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2020-08-26
---
## Overview
With the EOL of `CUDA 10.0` announced in [RSN 2](/notices/rsn0002), development
effort has been redirected to support `CUDA 11.0` in `v0.15`.
`CuPy` has released `v7.8.0` with `CUDA 11.0` support. We have temporarily built
a version of the `cupy` package in `rapidsai` [channel](https://anaconda.org/rapidsai/cupy/files?version=7.8.0)
that has `CUDA 11.0` support. In addition we have temporarily built `faiss`,
`faiss-gpu`, `libfaiss` to support `CUDA 11.0` in the `rapidsai` [channel](https://anaconda.org/rapidsai/faiss/files?version=7.8.0).
These packages are a stop-gap until `conda-forge` provides support for
`CUDA 11.0`. Once packages are up on `conda-forge` we will remove our packages.
>**NOTE:** `v0.16` nightlies will continue to use our `v7.8.0` package for
`CUDA 11.0` until an update is made on `conda-forge`
## Status
### Updates
- **21-Jul-2020** - Working on getting core `conda` dependencies for
`CUDA 11.0` built to enable testing and bring up
- **12-Aug-2020** - CUDA 11 packages released in `rapidsai-nightly` channel
- **26-Aug-2020** - CUDA 11 `condatoolkit` published in `anaconda` and
`defaults` channels (also available on `nvidia` channel)
- **26-Aug-2020** - Released v0.15 with CUDA 11 support
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0008.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 8 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Change minimum support gcc/g++ version to 9.x"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v0.20 / v21.06"
notice_created: 2021-04-29
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2021-05-05
---
## Overview
All RAPIDS projects will require `gcc/g++ 9.0+` in order to take advantage of new C++ features, notably including moving to C++17.
This also aligns RAPIDS with the current conda-forge build stack.
## Status
All `conda` builds and `docker` images use `gcc/g++ 9.3` starting with `v0.20` (now `v21.06`).
## Impact
Users building from source should use `gcc/g++ 9.0` or higher to build RAPIDS.
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0024.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 24 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Deprecation announcement for Ubuntu 18.04 in v22.12"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v22.12+"
notice_created: 2022-11-21
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
Ubuntu 18.04 will be deprecated in our upcoming release of v22.12 scheduled for December 2022. After the v22.12 release, users should expect that support for Ubuntu 18.04 may be dropped at any point.
## Impact
Users should consider switching to any of the following supported operating systems for any `rapidsai/rapidsai` image:
- Ubuntu 20.04
- Ubuntu 22.04 (support targeted for RAPIDS 23.02 -- see [RSN 25](/notices/rsn0025))
- CentOS 7
- Rocky Linux 8
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0003.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 3 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Support for Python 3.8 in v0.15"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v0.15"
notice_created: 2020-07-13
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2020-07-17
---
## Overview
With the EOL of `Python 3.6` announced in [RSN 2](/notices/rsn0002), development
effort has been redirected to support `Python 3.8` in `v0.15`.
## Status
- `Python 3.8` nightly support started on 16-Jul-2020 for both `conda` and
`docker`
## Impact
Users are encouraged to test nightly `conda` and `docker` builds and report any
issues in their respective repos.
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rapidsai_public_repos/rapids.ai/content/news
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0023.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 23 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Support for Python 3.10 in v23.02"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v22.12+"
notice_created: 2022-11-21
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
With the deprecation of `Python 3.9` announced in [RSN 22](/notices/rsn0022), development
effort has been redirected to support `Python 3.10` in `v23.02` nightly releases.
## Impact
Users are encouraged to test nightly `conda` and `docker` builds and report any
issues in their respective repos.
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rapidsai_public_repos/rapids.ai/content/news
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rapidsai_public_repos/rapids.ai/content/news/notices/rsn0018.md
|
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 18 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Support for Rocky 8.6 in v22.08"
notice_author: RAPIDS Ops
notice_status: Completed
notice_status_color: green
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v22.08+"
notice_created: 2022-06-08
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2023-09-05
---
## Overview
Development effort will begin supporting `Rocky 8.6` in `v22.08`. `Rocky 8.6` will replace the `CentOS 8` OS distributions for future RAPIDS releases. Experimental support will begin in `v22.08` nightlies. GA support for `Rocky 8.6` is expected for `v22.10` stable.
## Impact
`CentOS 8` users are encouraged to migrate to `Rocky 8.6` if possible and provide feedback to the RAPIDS libraries as we develop `v22.08`.
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rapidsai_public_repos/rapids.ai/content
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rapidsai_public_repos/rapids.ai/content/drafts/rsn.html
|
---
title: RAPIDS Support Notices | RAPIDS
description: RAPIDS Developer and Support Notices
draft: true
---
<!-- Hero Shortcode -->
{{< hero hero-text="RAPIDS Support Notices" button-link="#" button-text="Blank" >}}
<section class="row section padding-bottom-slant">
<div class="col">
<div class="container">
<h1 class="mb-5">Full RAPIDS Support Notice List</h1>
<!-- Full RSN list -->
<div x-data="{ fullResults: {} }" x-init="Papa.parse('https://docs.google.com/spreadsheets/d/e/2PACX-1vSPxywR0IGYZsCpqfdaEHNmx4LA9ADoeasCpScd79IhxlI44KjJUYTX52GCxMWgLwN6nEvUXOLDOj31/pub?output=csv', {
download: true,
header: true,
complete: function(results) {
fullResults = results.data
}})
">
<template x-for="notices in fullResults">
<div class="row mt-4" x-bind:id="notices.Index">
<div class="col-md-9 py-3 mt-5">
<h2> <span x-text="notices.Index"></span>: <span x-text="notices.Status"></span> </h2>
<h3> <span x-text="notices.Title"></span> </h3>
<h3> RAPIDS Version: <span x-text="notices.Version"></span></h3>
<p> <strong>Created: </strong><span x-text="notices.Created"></span> | <strong>Updated: </strong><span x-text="notices.Updated"></span> | <strong>Topic: </strong><span x-text="notices.Topic"></span> | <strong>Author: </strong><span x-text="notices.Author"></span> </p>
<br>
<p> <strong>Overview: </strong><span x-text="notices.Overview"></span> </p>
<p> <strong>Impact: </strong><span x-text="notices.Overview"></span> </p>
</div>
</div>
</template>
</div>
</div>
</div>
</div>
</section>
| 0 |
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rapidsai_public_repos/rapids.ai/content/drafts/templates.html
|
---
title: Site Template | RAPIDS
description: Design guides for rapids.ai
draft: true
---
<!-- Hero Shortcode -->
{{< hero hero-text="Template Page" button-link="#" button-text="Blank" >}}
<!-- Single Col -->
<section class="row section">
<div class="col">
<div class="container">
<h1 class="text-center mb-4">Single Col Centered</h1>
<div class="row">
<div class="col-md-1 py-3">
<p class="subtitle text-center"> Subtitle: Leverage agile frameworks to provide a robust synopsis for
high level
overviews.
Iterative approaches to corporate strategy foster collaborative thinking to further the overall value
proposition. Organically grow the holistic world view of disruptive innovation via workplace diversity and
empowerment.
</p>
</div>
</div>
</div>
</div>
</section>
<section class="row section">
<div class="col">
<div class="container">
<h1>Single Col</h1>
<div class="row">
<div class="col-md-1 py-3">
<p> Leverage agile frameworks to provide a robust synopsis for high level overviews. Iterative approaches to
corporate strategy foster collaborative thinking to further the overall value proposition. Organically grow
the holistic world view of disruptive innovation via workplace diversity and empowerment.
</p>
<h3 class="mt-5"> Subheader</h3>
<p>
Iterative approaches to corporate strategy foster collaborative thinking to further the overall value
proposition. Organically grow the holistic world view of disruptive innovation via workplace diversity and
empowerment.
</p>
<h3 class="mt-5"> Inline bold text and inline links</h3>
<p>
Iterative approaches to <strong>corporate strategy</strong> foster collaborative thinking to further the
overall value
proposition. <a href="#">Organically grow</a> the holistic world view of disruptive innovation via workplace
diversity and
empowerment.
<a href="#">Try Out Now <i class="fa-solid fa-arrow-up-right"></i> </a>
</p>
</div>
</div>
</div>
</div>
</section>
<!-- Double Col -->
<section class="row section">
<div class="col">
<div class="container">
<h1>Double Col</h1>
<div class="row">
<div class="col-md-6 py-3">
<h2><i class="fa-light fa-square-code icon"></i> Header</h2>
<p> Leverage agile frameworks to provide a robust synopsis for high level overviews. Iterative approaches to
corporate strategy foster collaborative thinking to further the overall value proposition. Organically grow
the holistic world view of disruptive innovation via workplace diversity and empowerment.</p>
</div>
<div class="col-md-6 py-3">
<h2><i class="fa-light fa-square-code icon"></i> Header</h2>
<p> Leverage agile frameworks to provide a robust synopsis for high level overviews. Iterative approaches to
corporate strategy foster collaborative thinking to further the overall value proposition. Organically grow
the holistic world view of disruptive innovation via workplace diversity and empowerment.</p>
</div>
</div>
</div>
</div>
</section>
<!-- Triple Col -->
<section class="row section">
<div class="col">
<div class="container">
<h1>Triple Col</h1>
<div class="row">
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-square-code"></i> Header</h2>
<p> Leverage agile frameworks to provide a robust synopsis for high level overviews. Iterative approaches to
corporate strategy foster collaborative thinking to further the overall value proposition. Organically grow
the
holistic world view of disruptive innovation via workplace diversity and empowerment.</p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-square-code"></i> Header</h2>
<p> Leverage agile frameworks to provide a robust synopsis for high level overviews. Iterative approaches to
corporate strategy foster collaborative thinking to further the overall value proposition. Organically grow
the
holistic world view of disruptive innovation via workplace diversity and empowerment.</p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-square-code"></i> Header</h2>
<p>Leverage agile frameworks to provide a robust synopsis for high level overviews. Iterative approaches to
corporate strategy foster collaborative thinking to further the overall value proposition. Organically grow
the holistic world view of disruptive innovation via workplace diversity and empowerment.</p>
</div>
</div>
</div>
</div>
</section>
<!-- Special Cases -->
<section class="row section padding-bottom-slant">
<div class="col">
<div class="container">
<h1>Special Cases</h1>
<div class="row">
<div class="col-md-6 py-3">
<h2><i class="fa-light fa-square-code icon"></i> Code Block</h2>
<p> Example code:</p>
<!-- Code samples must use <pre><code> tags together, specific code highlight must be in <span> tags -->
<pre
class="highlight"><code>git clone https://github.com/rapidsai/notebooks.git git submodule update --init --remote --no-single-branch --depth 1</code></pre>
</div>
<div class="col-md-1 py-3">
<h2> 1 Col </h2>
<p>Iterative corporate strategy. </p>
</div>
<div class="col-md-1 py-3">
<h2> 1 Col </h2>
<p>Collaborative thinking. </p>
</div>
<div class="col-md-2 py-3">
<h2> 2 Col </h2>
<p>Further the overall value proposition. </p>
</div>
<div class="col-md-2 py-3">
<h2> 2 Col </h2>
<p>Iterative overall value proposition. </p>
</div>
</div>
<div class="row">
<div class="col-md-1 py-3">
<h2>Common Icons</h2>
<h2>
<i class="fa-brands fa-python"></i> <i class="fa-brands fa-windows"></i> <i class="fa-brands fa-docker"></i>
<i class="fa-brands fa-ubuntu"></i> <i class="fa-brands fa-github"></i> <i class="fa-brands fa-twitter"></i>
<i class="fa-brands fa-slack"></i> <i class="fa-brands fa-stack-overflow"></i>
<i class="fa-regular fa-code-branch"></i> <i class="fa-regular fa-code"></i> <i
class="fa-light fa-square-terminal"></i> <i class="fa-light fa-file-code"></i> <i
class="fa-light fa-square-code"></i>
<i class="fa-light fa-download"></i> <i class="fa-regular fa-cloud-arrow-down"></i> <i
class="fa-regular fa-cloud"></i> <i class="fa-regular fa-list-check"></i> <i
class="fa-light fa-maximize"></i> <i class="fa-solid fa-arrow-up-right"></i> <i
class="fa-regular fa-user-group"></i>
<i class="fa-light fa-computer"></i> <i class="fa-light fa-microchip"></i> <i
class="fa-light fa-memory"></i> <i class="fa-light fa-laptop-code"></i> <i class="fa-light fa-server"></i>
<i class="fa-light fa-microchip-ai"></i> <i class="fa-regular fa-caret-down"></i> <i
class="fa-regular fa-caret-right"></i>
<i class="fa-regular fa-bolt"></i> <i class="fa-regular fa-arrow-pointer"></i> <i
class="fa-regular fa-circle-check"></i> <i class="fa-regular fa-circle-info"></i> <i
class="fa-regular fa-bookmark"></i> <i class="fa-regular fa-flag-swallowtail"></i>
</h2>
</div>
</div>
</div>
</div>
</section>
<!-- Slant Up Purple w/ BG Color -->
<div class="top-slant-container">
<div class="top-slant-up has-background-rapids-purple-primary text-white"></div>
</div>
<section class="row section has-background-rapids-purple-primary padding-bottom-slant">
<div class="col">
<div class="container">
<h1 class="text-white">Purple Slant Section</h1>
<div class="row">
<div class="col-md-6 py-3">
<h2 class="text-white"><i class="fa-light fa-square-code icon"></i> Header</h2>
<p> Leverage agile frameworks to provide a robust synopsis for high level overviews.
Iterative approaches to
corporate strategy foster collaborative thinking to further the overall value proposition. Organically grow
the holistic world view of disruptive innovation via workplace diversity and empowerment.</p>
<a href="#"><button class="button-rapids-white mt-3">White button</button></a>
</div>
<div class="col-md-6 py-3 text-white">
<h2 class="text-white"><i class="fa-light fa-square-code icon"></i> Header</h2>
<p> Leverage agile frameworks to provide a robust synopsis for high level overviews.
Iterative approaches to
corporate strategy foster collaborative thinking to further the overall value proposition. Organically grow
the holistic world view of disruptive innovation via workplace diversity and empowerment.</p>
<a href="#"><button class="button-rapids-teal mt-3">Teal button</button></a>
</div>
</div>
</div>
</div>
</section>
<!-- Slant Up Grat w/ BG Color -->
<div class="top-slant-container">
<div class="top-slant-down has-background-rapids-gray"></div>
</div>
<section class="row section has-background-rapids-gray padding-bottom-slant">
<div class="col">
<div class="container">
<h1>Gray Slant Section</h1>
<div class="row">
<div class="col-md-6 py-3">
<h2><i class="fa-light fa-square-code icon"></i> Header</h2>
<p> Leverage agile frameworks to provide a robust synopsis for high level overviews. Iterative approaches to
corporate strategy foster collaborative thinking to further the overall value proposition. Organically grow
the holistic world view of disruptive innovation via workplace diversity and empowerment.</p>
<a href="#"><button class="button-rapids-purple mt-3">Purple button</button></a>
</div>
<div class="col-md-6 py-3">
<h2><i class="fa-light fa-square-code icon"></i> Header</h2>
<p> Leverage agile frameworks to provide a robust synopsis for high level overviews. Iterative approaches to
corporate strategy foster collaborative thinking to further the overall value proposition. Organically grow
the holistic world view of disruptive innovation via workplace diversity and empowerment.</p>
<a href="#"><button class="button-rapids-teal mt-3">Teal button</button></a>
</div>
</div>
</div>
</div>
</section>
<div class="bottom-slant-container">
<div class="bottom-slant-up has-background-rapids-gray"></div>
</div>
<!-- Images -->
<section class="row section padding-top-slant">
<div class="col">
<div class="container">
<h1>Image Layouts</h1>
<div class="row">
<div class="col-md-4 py-3">
<h3 class="text-center">1/2 size center</h3>
<img class="image img-half img-center" src="/images/RAPIDS-cloud.png">
</div>
<div class="col-md-4 py-3">
<h3 class="text-center">1/2 size center</h3>
<img class="image img-half img-center" src="/images/RAPIDS-cloud.png">
</div>
<div class="col-md-4 py-3">
<h3 class="text-center">1/2 size center</h3>
<img class="image img-half img-center" src="/images/RAPIDS-cloud.png">
</div>
</div>
<div class="row">
<div class="col-md-4 py-3">
<h3>1/2 size</h3>
<img class="image img-half" src="/images/RAPIDS-cloud.png">
</div>
<div class="col-md-4 py-3">
<h3>1/3 size</h3>
<img class="image img-third" src="/images/RAPIDS-cloud.png">
</div>
<div class="col-md-4 py-3">
<h3>1/4 size</h3>
<img class="image img-quarter" src="/images/RAPIDS-cloud.png">
</div>
</div>
<div class="row">
<div class="col-md-4 py-3 offset-md-4">
<h3 class="text-center">sized by column</h3>
<img class="image" src="/images/RAPIDS-cloud.png">
</div>
</div>
<div class="row">
<div class="col-md-6 py-3">
<h3 class="text-center">sized by column</h3>
<img class="image img-center" src="/images/RAPIDS-cloud.png">
</div>
<div class="col-md-6 py-3">
<h3 class="text-center">sized by column</h3>
<img class="image img-center" src="/images/RAPIDS-cloud.png">
</div>
</div>
</div>
</div>
</section>
<div class="bottom-slant-container">
<div class="bottom-slant-up bg-white"></div>
</div>
<section class="row padding-top-slant padding-bottom-slant">
<div class="col">
<!-- Blog Posts -->
{{< post >}}
</div>
</section>
<section class="row padding-bottom-slant">
<div class="col">
<!-- Hero Shortcode -->
{{< open-source >}}
{{< adopters-contributors >}}
</div>
</section>
<!-- Global JS -->
<script src="/js/main.js"></script>
| 0 |
rapidsai_public_repos/rapids.ai/content
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rapidsai_public_repos/rapids.ai/content/drafts/events.html
|
---
title: Events | RAPIDS
description: Upcoming and past RAPIDS events
draft: true
---
<!-- Hero Shortcode -->
{{< hero hero-text="RAPIDS Events" button-link="#" button-text="Blank" >}}
<section class="row section padding-bottom-slant">
<div class="col">
<div class="container">
<h1 class="mb-5">List of Upcoming and Past RAPIDS Events</h1>
<!-- Full RSN list -->
<div x-data="{ fullResults: {} }" x-init="Papa.parse('https://docs.google.com/spreadsheets/d/e/2PACX-1vTUSMyTJWjiYtuV6nvoQIDFSrt6yf00Mt4J9ZaXUMgVi1bAIhcOfnASLhsIH2PhZEbuMCg7Olv9bcZF/pub?output=csv', {
download: true,
header: true,
complete: function(results) {
fullResults = results.data
}})
">
<template x-for="event in fullResults">
<div class="row mt-4">
<div class="col-md-9 py-3 mt-5">
<h2> <span x-text="event.Title"></span> | <span x-text="event.Date"></span> </h2>
<h3> <span x-text="event.Type"></span> </h3>
<p> <span x-text="event.Description"></span> </p>
<a x-bing:href="event.Link" target="_blank"> Learn More <i class="fa-solid fa-arrow-up-right"></i></a>
</div>
</div>
</template>
</div>
</div>
</div>
</div>
</section>
| 0 |
rapidsai_public_repos/rapids.ai/content
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rapidsai_public_repos/rapids.ai/content/ecosystem/_index.html
|
---
title: Ecosystem | RAPIDS
description: RAPIDS libraries, frameworks, extensions and more
---
<!-- Hero Shortcode -->
{{< hero hero-text="Ecosystem" button-link="#featured-software" button-text="Featured Software">}}
<!-- Intro -->
<section class="row section mb-6">
<div class="col">
<div class="container">
<h1 class="text-center mb-5"> An ecosystem of hardware, <br> software, and developers</h1>
<div class="row">
<div class="col-md-4 py-3">
<h2><i class="fa-regular fa-microchip"></i> Hardware </h2>
<p> RAPIDS runs on hardware powered by CUDA, the fundamental set of tools for GPU computing built by
NVIDIA. RAPIDS works on PCs, workstations, data centers, and the cloud. Learn more about the different types
of hardware and find the best fit for your use case on NVIDA's product page for <a href="https://www.nvidia.com/en-us/deep-learning-ai/solutions/data-science/" target="_blank"> Data Science Hardware <i class="fa-solid fa-arrow-up-right"></i></a> </p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-regular fa-code"></i> Software </h2>
<p> Set on a foundation of powerful hardware and parallelized by CUDA, the RAPIDS ecosystem is based on core
projects, those extending its capabilities, and those built on top of RAPIDS.</p>
<a href="#featured-software">Jump to Section <i class="fa-solid fa-arrow-up-right"></i></a>
<br>
<img class="image img-center mt-5" src="/images/rapid-layers.png">
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-regular fa-laptop-code"></i> Developers </h2>
<p> We hope you will consider integrating RAPIDS into your solution or workflow. RAPIDS is built for Python and C++ developers alike. Build something great with RAPIDS. </p> <a href="#developers">Jump to Section <i class="fa-solid fa-arrow-up-right"></i></a>
</div>
</div>
</div>
</div>
</section>
<!-- Software RAPIDS Libs -->
<div id="featured-software"></div>
<div class="top-slant-container">
<div class="top-slant-down has-background-rapids-purple-primary"></div>
</div>
<section class="row section has-background-rapids-purple-primary">
<div class="col">
<div class="container">
<h1 class="text-white">Featured RAPIDS Libraries</h1>
<p class="subheading text-white mb-5">Featured components of the RAPIDS ecosystem.</p>
<div class="row">
<div class="col-md-4 py-3">
<h2 class="text-white"><i class="fa-regular fa-terminal"></i> cuDF</h2>
<div class="tags-container border-top border-2 border-white">
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> PANDAS </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> DATAFRAME </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> PYTHON / C++ </span>
</div>
<p class="text-white"> cuDF is a library for data science and engineering designed for people familiar with the pandas API. Use cuDF in the new pandas Accelerator Mode to speed up pandas workflows with zero code change or use the classic GPU-only mode to unlock maximum performance on dataframes.</p>
<a href="https://github.com/rapidsai/cudf" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.rapids.ai/api/cudf/stable/" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://github.com/orgs/rapidsai/projects/51/views/19" target="_blank">Roadmap <i class="fa-solid fa-arrow-up-right"></i> </a>
<br><br>
<h3 class="text-white">libcudf</h3>
<p class="text-white">libcudf provides the CUDA C++ building blocks powering cuDF.</p>
<a href="https://github.com/rapidsai/cudf" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.rapids.ai/api/libcudf/stable/" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i>
</a>
</div>
<div class="col-md-4 py-3">
<h2 class="text-white"><i class="fa-regular fa-terminal"></i> cuML</h2>
<div class="tags-container border-top border-2 border-white">
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> SCIKIT-LEARN </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> MACHINE LEARNING</span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> PYTHON / C++ </span>
</div>
<p class="text-white"> cuML is a library for executing machine learning algorithms on GPUs with an API
that closely follows the Scikit-Learn API. Reduce the time to fit your model from hours or minutes to seconds.</p>
<a href="https://github.com/rapidsai/cuml" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.rapids.ai/api/cuml/stable/" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a>
<br><br>
<h3 class="text-white">libcuml</h3>
<p class="text-white">libcuml provides the CUDA C++ building blocks powering cuML.</p>
<a href="https://github.com/rapidsai/cuml" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.rapids.ai/api/libcudf/stable/" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i>
</a>
</div>
<div class="col-md-4 py-3">
<h2 class="text-white"><i class="fa-regular fa-terminal"></i> cuGraph</h2>
<div class="tags-container border-top border-2 border-white">
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> NETWORKX </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> GRAPH </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> PYTHON / C++ </span>
</div>
<p class="text-white"> cuGraph is a library to make graph analytics available to everyone. With a Python
API that follows NetworkX, you can analyze networks of millions of nodes without specialized software faster
than ever.</p>
<a href="https://github.com/rapidsai/cugraph" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.rapids.ai/api/cugraph/stable/" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a>
<br><br>
<h3 class="text-white">libcugraph</h3>
<p class="text-white">libcugraph provides the CUDA C++ building blocks powering cuGraph.</p>
<a href="https://github.com/rapidsai/cugraph" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.rapids.ai/api/libcugraph/stable" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
</div>
<div class="row">
<div class="col-md-4 py-3">
<h2 class="text-white"><i class="fa-regular fa-terminal"></i> cuSpatial</h2>
<div class="tags-container border-top border-2 border-white">
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> GEOPANDAS </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> GEOSPATIAL </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> PYTHON / C++ </span>
</div>
<p class="text-white">cuSpatial is a library for lightning-fast spatial analytics. Fully integrated with GeoPandas and growing fast, this toolkit will feel familiar to Python users of GIS tools.</p>
<a href="https://github.com/rapidsai/cuspatial" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.rapids.ai/api/cuspatial/stable/" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://github.com/orgs/rapidsai/projects/41/views/5" target="_blank">Roadmap <i class="fa-solid fa-arrow-up-right"></i> </a>
<br><br>
<h3 class="text-white">libcuspatial</h3>
<p class="text-white">libcuspatial provides the CUDA C++ building blocks powering cuSpatial.</p>
<a href="https://github.com/rapidsai/cuspatial" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.rapids.ai/api/libcuspatial/stable" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
<div class="col-md-4 py-3">
<h2 class="text-white"><i class="fa-regular fa-terminal"></i> RAFT</h2>
<div class="tags-container border-top border-2 border-white">
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> PRIMITIVES </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> ALGORITHMS </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> CUDA / PYTHON / C++ </span>
</div>
<p class="text-white"> RAFT contains CUDA accelerated primitives for rapidly composing analytics, and is used by other RAPIDS libraries. Its building blocks include dense algebra, sparse algebra, spatial computations, clustering, solvers, and statistics. </p>
<a href="https://github.com/rapidsai/raft" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.rapids.ai/api/raft/stable" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
<div class="col-md-4 py-3">
<h2 class="text-white"><i class="fa-regular fa-terminal"></i> cuxfilter </h2>
<div class="tags-container border-top border-2 border-white">
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> DASHBOARDS </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> VISUALIZATION </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> PYTHON </span>
</div>
<p class="text-white"> Quickly visualize and filter through large datasets, with a few lines of code,
using best in class charting libraries. </p>
<a href="https://github.com/rapidsai/cuxfilter" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.rapids.ai/api/cuxfilter/stable/" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://github.com/orgs/rapidsai/projects/67/views/1" target="_blank">Roadmap <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
</div>
<div class="row">
<div class="col-md-4 py-3">
<h2 class="text-white"><i class="fa-regular fa-terminal"></i> kvikIO </h2>
<div class="tags-container border-top border-2 border-white">
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> FILE IO </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> GPU DIRECT STORAGE </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> PYTHON / C++ </span>
</div>
<p class="text-white"> Take full advantage of GPU Direct Storage (GDS) through powerful bindings to cuFile. </p>
<a href="https://github.com/rapidsai/kvikio" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.rapids.ai/api/kvikio/stable" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a>
<br><br>
<h3 class="text-white">libkvikio</h3>
<p class="text-white">libkvikio provides the CUDA C++ building blocks powering kvikIO. </p>
<a href="https://github.com/rapidsai/kvikio" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.rapids.ai/api/libkvikio/stable" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
<div class="col-md-4 py-3">
<h2 class="text-white"><i class="fa-regular fa-terminal"></i> cuSignal </h2>
<div class="tags-container border-top border-2 border-white">
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> SCIPY-SIGNAL </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> SIGNAL PROCESSING </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> PYTHON </span>
</div>
<p class="text-white"> cuSignal accelerates manipulation and analysis of signal data in a Scipy Signal-like API. </p>
<a href="https://github.com/rapidsai/cusignal" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.rapids.ai/api/cusignal/stable" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://github.com/orgs/rapidsai/projects/41/views/5" target="_blank">Roadmap <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
<div class="col-md-4 py-3">
<h2 class="text-white"><i class="fa-regular fa-terminal"></i> cuCIM </h2>
<div class="tags-container border-top border-2 border-white">
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> COMPUTER VISION </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> IMAGE PROCESSING </span>
<span class="tags-item text-white border-white"><i class="fa-solid fa-tag"></i> PYTHON </span>
</div>
<p class="text-white"> Greatly accelerate your computer vision and image processing tasks, especially for biomedical imaging.</p>
<a href="https://github.com/rapidsai/cucim" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.rapids.ai/api/cucim/stable/" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i>
</a> <br>
<a href="https://github.com/orgs/rapidsai/projects/62/views/1" target="_blank">Roadmap <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
</div>
<div class="row mt-5">
<div class="col-md-4 py-3">
<h2 class="text-white"><i class="fa-regular fa-terminal"></i> Many More...</h2>
<p class="text-white"> Visit our <a href="https://github.com/rapidsai" target="_blank"> GitHub organization page</a> or our <a href="https://docs.rapids.ai/api" target="_blank">documentation </a> for a more extensive list of projects.</p>
</div>
</div>
</div>
</div>
</section>
<div id="rapids-integration"></div>
<div class="bottom-slant-container">
<div class="bottom-slant-up has-background-rapids-purple-primary"></div>
</div>
<!-- RAPIDS Integrated -->
<section class="row section has-background-rapids-gray padding-top-slant padding-bottom-slant">
<div class="col">
<div class="container">
<h1>RAPIDS Integration</h1>
<p class="subheading mb-5">Projects and services that have RAPIDS acceleration as an added feature. </p>
<div class="row">
<div class="col-md-6 py-3">
<img class="image img-w100" src="/images/spark-logo-trademark.png">
<h2><i class="fa-regular fa-code-merge"></i> Spark RAPIDS</h2>
<div class="tags-container border-top border-2 has-border-rapids-purple-primary">
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> APACHE SPARK </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> SQL</span>
</div>
<p> NVIDIA is bringing RAPIDS to Apache Spark to accelerate ETL workflows with no code change, improving performance, and reducing total costs.</p>
<a href="https://nvidia.github.io/spark-rapids/" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://nvidia.github.io/spark-rapids/" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
<div class="col-md-6 py-3">
<img class="image img-w100" src="/images/dask_logo.png">
<h2><i class="fa-regular fa-code-merge"></i> Dask </h2>
<div class="tags-container border-top border-2 has-border-rapids-purple-primary">
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> DISTRIBUTED </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> PARALLEL COMPUTING </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> PYTHON </span>
</div>
<p> Scale out your workload onto multiple GPUs and multiple machines with Dask. RAPIDS also develops the <a href="https://github.com/rapidsai/dask-cuda" target="_blank"> Dask-CUDA </a> library for GPU-friendly cluster deployment</p>
<a href="https://github.com/dask" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.dask.org/en/stable/gpu.html" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
</div>
<div class="row">
<div class="col-md-6 py-3">
<img class="image img-w100" src="/images/xgboost_logo.png">
<h2><i class="fa-regular fa-code-merge"></i> XGboost </h2>
<div class="tags-container border-top border-2 has-border-rapids-purple-primary">
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> GRADIENT BOOSTING </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> CLASSIFICATION </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> PYTHON / C++ </span>
</div>
<p> XGBoost is the gold standard in single model performance for classification and regression. RAPIDS was built from the start to integrate with this amazing algorithm. </p>
<a href="https://github.com/dmlc/xgboost" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://xgboost.readthedocs.io/en/stable/gpu/index.html" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
<div class="col-md-6 py-3">
<img class="image img-w100" src="/images/RAPIDS-SQL.png">
<h2><i class="fa-regular fa-code-merge"></i> Dask SQL </h2>
<div class="tags-container border-top border-2 has-border-rapids-purple-primary">
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> DISTRIBUTED </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> SQL </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> PYTHON </span>
</div>
<p> Scale out workloads with Dask via tried-and-true SQL queries on your data.</p>
<a href="https://github.com/dask-contrib/dask-sql" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://dask-sql.readthedocs.io/en/latest/" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
</div>
<div class="row">
<div class="col-md-6 py-3">
<img class="image img-w100" src="/images/Rapids-viz-logo.png">
<h2><i class="fa-regular fa-code-merge"></i> Visualization </h2>
<div class="tags-container border-top border-2 has-border-rapids-purple-primary">
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> PLOTLY DASH </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> HOLOVIZ </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> CUXFILTER </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> NODE RAPIDS </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> PYTHON / JS </span>
</div>
<p> RAPIDS integrates with popular and powerful visualization projects, such as Plotly Dash, HoloViz, Bokeh, and more.</p>
<a href="https://docs.rapids.ai/visualization" target="_blank">RAPIDS Visualization Guide<i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
<div class="col-md-6 py-3">
<img class="image img-w100" src="/images/RAPIDS-cloud.png">
<h2><i class="fa-regular fa-code-merge"></i> Cloud / Deployment </h2>
<div class="tags-container border-top border-2 has-border-rapids-purple-primary">
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> CSP </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> HPC </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> HPO </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary "><i class="fa-solid fa-tag"></i> DEPLOYMENT </span>
</div>
<p> RAPIDS is built to be fast where ever it runs. Learn how to run RAPIDS on all the major cloud providers,
with open-source Hyperparameter Optimization tools, and High Performance Computing like Slurm.</p>
<a href="https://docs.rapids.ai/deployment/stable/" target="_blank">Deployment Documentation <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
</div>
</div>
</div>
</section>
<div id="rapids-accelerated"></div>
<div class="bottom-slant-container">
<div class="bottom-slant-down has-background-rapids-gray"></div>
</div>
<!-- RAPIDS Accelerated -->
<section class="row section padding-top-slant">
<div class="col">
<div class="container">
<h1>RAPIDS Accelerated </h1>
<p class="subheading mb-5">Cutting edge software built with RAPIDS.</p>
<div class="row">
<div class="col-md-6 py-3">
<h2><i class="fa-regular fa-gauge-circle-bolt"></i> Triton </h2>
<div class="tags-container border-top border-2 has-border-rapids-purple-primary">
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary"><i class="fa-solid fa-tag"></i> INFERENCE </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary"><i class="fa-solid fa-tag"></i> NVIDIA AI </span>
</div>
<p> Triton Inference Server, part of the NVIDIA AI platform, streamlines and standardizes AI inference by
enabling teams to deploy, run, and scale trained AI models from any framework on any GPU or CPU-based
infrastructure. </p>
<a href="https://github.com/triton-inference-server" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://developer.nvidia.com/nvidia-triton-inference-server" target="_blank">Learn More <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
<div class="col-md-6 py-3">
<h2><i class="fa-regular fa-gauge-circle-bolt"></i> Merlin </h2>
<div class="tags-container border-top border-2 has-border-rapids-purple-primary">
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary"><i class="fa-solid fa-tag"></i> RECOMMENDERS </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary"><i class="fa-solid fa-tag"></i> NVIDIA AI </span>
</div>
<p> NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems. Merlin
leverages RAPIDS cuDF and Dask cuDF for dataframe transformation during ETL and inference, as well as for
the optimized dataloaders in TensorFlow, PyTorch or HugeCTR to accelerate deep learning training. </p>
<a href="https://github.com/NVIDIA-Merlin" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://developer.nvidia.com/nvidia-merlin" target="_blank">Learn More <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
</div>
<div class="row">
<div class="col-md-6 py-3">
<h2><i class="fa-regular fa-gauge-circle-bolt"></i> cuOpt</h2>
<div class="tags-container border-top border-2 has-border-rapids-purple-primary">
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary"><i class="fa-solid fa-tag"></i> ROUTING </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary"><i class="fa-solid fa-tag"></i> NVIDIA AI </span>
</div>
<p> NVIDIA cuOpt is an operations research optimization API using AI to help developers create complex,
real-time fleet routing. These APIs can be used to solve complex routing problems with multiple constraints
and deliver new capabilities, like dynamic rerouting, job scheduling, and robotic simulations, with
subsecond solver response time. </p>
<a href="https://developer.nvidia.com/cuopt-logistics-optimization" target="_blank">Learn More <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
<div class="col-md-6 py-3">
<h2><i class="fa-regular fa-gauge-circle-bolt"></i> Morpheus </h2>
<div class="tags-container border-top border-2 has-border-rapids-purple-primary">
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary"><i class="fa-solid fa-tag"></i> CYBER SECURITY </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary"><i class="fa-solid fa-tag"></i> NVIDIA AI </span>
</div>
<p> NVIDIA Morpheus is an open application framework that enables cybersecurity developers to create optimized
AI pipelines for filtering, processing, and classifying large volumes of real-time data.</p>
<a href="https://github.com/nv-morpheus" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.nvidia.com/morpheus/index.html" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
</div>
<div class="row">
<div class="col-md-6 py-3">
<h2><i class="fa-regular fa-gauge-circle-bolt"></i>Clara </h2>
<div class="tags-container border-top border-2 has-border-rapids-purple-primary">
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary"><i class="fa-solid fa-tag"></i> MEDICAL </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary"><i class="fa-solid fa-tag"></i> NVIDIA AI </span>
</div>
<p> NVIDIA Clara is a platform of AI applications and accelerated frameworks for healthcare developers,
researchers, and medical device makers creating AI solutions to improve healthcare delivery and accelerate
drug discovery.</p>
<a href="https://www.nvidia.com/en-us/clara/" target="_blank">Learn More <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://docs.nvidia.com/clara/" target="_blank">Documentation <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
<div class="col-md-6 py-3">
<h2><i class="fa-regular fa-gauge-circle-bolt"></i> Monai </h2>
<div class="tags-container border-top border-2 has-border-rapids-purple-primary">
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary"><i class="fa-solid fa-tag"></i> MEDICAL IMAGING </span>
<span class="tags-item has-text-rapids-purple-primary has-border-rapids-purple-primary"><i class="fa-solid fa-tag"></i> cuCIM </span>
</div>
<p> RAPIDS cuCIM has been integrated into the MONAI Transforms component to accelerate the data pathology training pipeline on GPU.</p>
<a href="https://github.com/Project-MONAI" target="_blank"> GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://monai.io/" target="_blank">Project Page <i class="fa-solid fa-arrow-up-right"></i> </a>
</div>
</div>
</div>
</div>
</section>
<!-- RAPIDS Workflows -->
<div class="bottom-slant-container">
<div class="bottom-slant-up bg-white"></div>
</div>
<div id="rapids-workflows"></div>
<section class="row section bg-white padding-top-slant padding-bottom-slant">
<div class="col">
<div class="container">
<h1>RAPIDS Workflows </h1>
<p class="subheading mb-5">Complex pipelines that utilize RAPIDS components. </p>
<div class="row">
<div class="col-md-6 py-3">
<h2><i class="fa-regular fa-split"></i> Data Science Workflows </h2>
<p>Integrating and combining RAPIDS libraries forms powerful workflows that optimize data science pipelines.
Learn more about real world workflows and featured success stories in our <a href="/learn-more/#use-cases">Use Cases Section <i class="fa-solid fa-arrow-up-right"></i> </a></p>
</div>
<div class="col-md-6 py-3">
<h2><i class="fa-regular fa-panel-fire"></i> MLOps Guides</h2>
<p>Deploy and maintain RAPIDS in production environments with these machine learning operations, hyper parameter optimization, and integration guides on our <a href="https://github.com/rapidsai/cloud-ml-examples" target="_blank">Cloud ML Examples Repository</a> and <a href="https://docs.rapids.ai/deployment/stable/" target="_blank">Deployments Page <i class="fa-solid fa-arrow-up-right"></i></a> </p>
</div>
</div>
</div>
</div>
</section>
<!-- Developers -->
<div id="developers"></div>
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<div class="col">
<div class="container">
<h1> Developers </h1>
<p class="subheading mb-5">Guides and resources for RAPIDS developers.</p>
<div class="row">
<div class="col-md-6 py-3">
<h2><i class="fa-regular fa-chalkboard-user"></i> Maintainer Guides </h2>
<p>RAPIDS projects stay cohesive thanks to detailed maintainer guides and ops procedures. Look up release
schedules, get CI help, and stay up to date on our <a href="https://docs.rapids.ai/maintainers" target="_blank"> Maintainer Documentation Page <i class="fa-solid fa-arrow-up-right"></i> </a> </p>
</div>
<div class="col-md-6 py-3">
<h2><i class="fa-regular fa-code-pull-request"></i>Contribution Guides </h2>
<p>Open source projects stay healthy with active contributions. Overall contribution guides can be found on our <a href="https://docs.rapids.ai/contributing" target="_blank">Documentation</a>. Each RAPIDS repository also has helpful and
detailed contributing guides, such as <a href="https://github.com/rapidsai/cudf/#contributing" target="_blank">cuDF's example</a>. Check out each project's README and documentation for their specific requirements in the <a href="https://github.com/rapidsai" target="_blank">RAPIDS Repositories <i class="fa-solid fa-arrow-up-right"></i> </a> </p>
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---
title: cuDF Pandas | RAPIDS
description: cuDF pandas Accelerator Mode
---
<!-- Hero Shortcode -->
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<!-- Intro -->
<section class="row section mb-6">
<div class="col">
<div class="container">
<h1 class="text-center mb-10"> OPEN BETA: ACCELERATING PANDAS <br> WITH ZERO CODE CHANGE </h1>
<div class="row">
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-file-binary"></i> Zero Code Change Acceleration </h2>
<p>Write your code with the full flexibility of pandas. Just load cudf.pandas to accelerate on the GPU, with automatic CPU fallback if needed.</p>
<br>
<h2 class="mt-4"><i class="fa-light fa-laptop-binary"></i> One Code Path <br> Differing Hardware </h2>
<p>Develop, test, and run in production with a single code path, regardless of hardware.</p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-boxes-stacked"></i> Third-Party Library Compatible </h2>
<p>pandas accelerator mode is compatible with most third-party libraries that operate on pandas objects — it will even accelerate pandas operations <strong>within</strong> these libraries.</p>
<br>
<h2 class="mt-4"><i class="fa-light fa-bolt-lightning"></i> Accelerates the Entire pandas Ecosystem </h2>
<p>Bringing the speed of cuDF to pandas users and the ecosystem built for them. With GPUs, you can keep using pandas as your data grows.</p>
</div>
<div class="col-md-4 py-3">
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<!-- How it works -->
<section class="row section padding-top-slant padding-bottom-slant">
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<div class="container">
<h1 class="mb-4"> Bringing the Speed of cuDF <br> to Every Pandas User </h1>
<div class="row">
<div class="col-md-6 py-3">
<h2><i class="fa-light fa-square-info"></i> How to Use It </h2>
<p>This new mode is available in the standard cuDF package. To accelerate IPython or Jupyter Notebooks, use the magic:</p>
<code class="code-sample mt-3">
%load_ext cudf.pandas <br>
import pandas as pd <br>
...
</code>
<br><br>
<p>To accelerate a Python script, use the Python module flag on the command line:</p>
<code class="code-sample mt-3">python -m cudf.pandas script.py</code>
<br><br>
<p>Or, explicitly enable cudf.pandas via import if you can't use command line flags:</p>
<code class="code-sample mt-3">
import cudf.pandas <br>
cudf.pandas.install() <br><br>
import pandas as pd <br>
...
</code>
</div>
<div class="col-md-6 py-3">
<h2><i class="fa-light fa-gauge-high"></i> 150x Faster, Zero Code Change </h2>
<canvas id="perfchart" width="500" height="375"></canvas>
<p class="fs-7 fw-lighter text-center">* Grace Hopper vs Intel Xeon Platinum 8480CL CPU <a href="https://developer.nvidia.com/blog/rapids-cudf-accelerates-pandas-nearly-150x-with-zero-code-changes/" target="_blank">Learn More <i class="fa-solid fa-arrow-up-right"></i> </a></p>
</div>
</div>
<h1 class="mt-10 mb-4"> How It Works</h1>
<div class="row">
<div class="col-md-6 py-3">
<h2><i class="fa-sharp fa-light fa-gear-complex-code"></i> Under the Hood </h2>
<p>When cudf.pandas is enabled, import pandas (or any of its submodules) imports a magic module, rather than “regular” pandas. This magic module contains proxy types and proxy functions:</p>
<code class="code-sample mt-3">
In [1]: %load_ext cudf.pandas <br>
In [2]: import pandas as pd <br><br>
In [3]: pd <br>
Out[3]: <module 'pandas' (ModuleAccelerator(fast=cudf, slow=pandas))>
</code>
<br><br>
<p>Operations on proxy types and functions execute on the GPU where possible and on the CPU otherwise, synchronizing under the hood as needed. This applies to pandas operations in both your code and in third-party libraries you may be using.</p>
<br>
<p>All cudf.pandas objects are a proxy to either a GPU (cuDF) or CPU (pandas) object at any given time. Operations are first attempted on the GPU (copying from CPU if necessary). If that fails, the operation is attempted on the CPU (copying from GPU if necessary).</p>
<br>
<p>When using cudf.pandas, cuDF's pandas compatibility mode is automatically enabled, ensuring consistency with pandas-specific semantics like default sort ordering.</p>
</div>
<div class="col-md-6 py-3">
<h2><i class="fa-light fa-diagram-subtask"></i> Execution Flow </h2>
<img src="/images/Cudf-Pandas.png " class="img-full">
</div>
</div>
</div>
</div>
</section>
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<div id="get-started"></div>
<div class="top-slant-container">
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<section class="row section has-background-rapids-gray padding-top-slant padding-bottom-slant">
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<h1 class="mb-4"> Bringing the Speed of cuDF <br> to Every Pandas User </h1>
<div class="row">
<div class="col py-3">
<h2><i class="fa-light fa-bookmark"></i> Try Now on Colab</h2>
<a href="https://nvda.ws/rapids-cudf" target="_blank"><img src="/images/OpenGoogleColab.png" class="img-w200"></a>
<p>Take cuDF's new pandas accelerator mode for a test-drive in a free GPU-enabled notebook environment using your Google account by <a href="https://nvda.ws/rapids-cudf" target="_blank">launching on CoLab <i class="fa-solid fa-arrow-up-right"></i> </a></p>
<br>
<p>cuDF's pandas accelerator mode is part of the cuDF package and works smoothly with all RAPIDS libraries. Visit the RAPIDS <a href="https://rapids.ai/#quick-start" target="_blank">Quick Start</a> to get started with any RAPIDS library on your favorite platform.</p>
</div>
<div class="col py-3">
<h2><i class="fa-light fa-head-side-gear"></i> Learn More</h2>
<p>cuDF pandas accelerator mode is in open beta and under active development. It's ready for wide use, but has a few known limitations and edge cases. You can <a href="https://docs.rapids.ai/api/cudf/nightly/" target="_blank">learn more through the documentation</a> and <a href="https://developer.nvidia.com/blog/rapids-cudf-accelerates-pandas-nearly-150x-with-zero-code-changes/" target="_blank">the release blog <i class="fa-solid fa-arrow-up-right"></i> </a> </p>
<br>
<p>Prefer conference presentations to documentation? Get all the details about how cudf.pandas works, how we test it, and why we developed it at the <a href="https://www.nvidia.com/en-us/events/ai-data-science-virtual-summit/" target="_blank">AI and Data Science Virtual Summit <i class="fa-solid fa-arrow-up-right"></i> </a> </p>
<br>
<p>Want to contribute or share feedback, reach out <a href="https://github.com/rapidsai/cudf" target="_blank">on GitHub <i class="fa-solid fa-arrow-up-right"></i> </a> </p>
</div>
</div>
</div>
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---
title: Learn More | RAPIDS
description: Use cases and enterprise topics
---
<!-- Hero Shortcode -->
{{< hero hero-text="Learn More" button-link="https://www.nvidia.com/en-us/data-center/products/ai-enterprise/" button-text="Try RAPIDS + NVIDIA AI Enterprise" >}}
<!-- Intro -->
<section class="row section mb-6">
<div class="col">
<div class="container">
<h1 class="text-center mb-5"> Learn about the project, use cases, <br> and engagement with RAPIDS </h1>
<div class="row">
<div class="col-md-4 py-3">
<h2><i class="fa-regular fa-circle-info"></i> About </h2>
<p>RAPIDS is a collection of open source software libraries and APIs that gives you the ability to execute end-to-end
data science and analytics pipelines entirely on NVIDIA GPUs using familiar PyData APIs. <a href="#about">Jump To Section <i class="fa-solid fa-arrow-up-right"></i></a> </p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-regular fa-chart-user"></i> Use Cases </h2>
<p> Learn more about RAPIDS success stories, use cases, applications, research and other topics related to GPU accelerated data science. <a href="#use-cases">Jump To Section <i class="fa-solid fa-arrow-up-right"></i></a></p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-regular fa-message-exclamation"></i> Get Involved </h2>
<p> Get in contact with RAPIDS, find enhanced support with NVIDIA enterprise services, and reach out to the broader developer community. <a href="#get-involved">Jump To Section <i class="fa-solid fa-arrow-up-right"></i></a></p>
</div>
</div>
</div>
</div>
</section>
<div class="bottom-slant-container">
<div class="bottom-slant-down bg-white"></div>
</div>
<!-- About -->
<div id="about"></div>
<section class="row section padding-top-slant padding-bottom-slant">
<div class="col">
<div class="container">
<h1 class="mb-5"> About The Project</h1>
<div class="row">
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-house-laptop"></i> Familiar </h2>
<p>Utilizing NVIDIA CUDA primitives for low-level compute optimization, RAPIDS exposes GPU parallelism and high-bandwidth memory speed through user-friendly interfaces:</p> <br>
<div class="content fs-7">
<i class="fa fa-caret-right"></i> Dataframe processing with <a href="https://github.com/rapidsai/cudf" target="_blank">cuDF</a> (similar API to pandas) <br>
<i class="fa fa-caret-right"></i> Machine learning with <a href="https://github.com/rapidsai/cuml" target="_blank">cuML</a> (similar API to scikit-learn) <br>
<i class="fa fa-caret-right"></i> Graph processing with <a href="https://github.com/rapidsai/cugraph" target="_blank">cuGraph</a> (similar API to networkX) <br>
<i class="fa fa-caret-right"></i> Spatial analytics with <a href="https://github.com/rapidsai/cuspatial" target="_blank">cuSpatial</a> (similar API to geoPandas) <br>
<i class="fa fa-caret-right"></i> Image processing with <a href="https://github.com/rapidsai/cucim" target="_blank">cuCIM</a> (similar API to scikit-image) <br>
<i class="fa fa-caret-right"></i> Signal processing <a href="https://github.com/rapidsai/cusignal" target="_blank">cuSignal</a> (similar API to scipy.signal) <br>
<i class="fa fa-caret-right"></i> Seamless cross-filtered dashboards with <a href="https://github.com/rapidsai/cuxfilter" target="_blank">cuxfilter</a> <br>
<i class="fa fa-caret-right"></i> Low level compute primitives with <a href="https://github.com/rapidsai/raft" target="_blank">RAFT</a> <br>
<i class="fa fa-caret-right"></i> Apache Spark acceleration with <a href="https://nvidia.github.io/spark-rapids/" target="_blank">Spark RAPIDS</a> <br><br>
and <a href="https://github.com/rapidsai" target="_blank">many more projects</a>...
</div>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-layer-plus"></i> Scalable </h2>
<p> RAPIDS delivers impressive acceleration from on a single GPU desktop system all the way to MNMG (multi-node multi-GPU) configurations on an expansive range of <a href="https://www.nvidia.com/en-us/deep-learning-ai/solutions/data-science/" target="_blank">NVIDIA hardware</a>. </p> <br>
<div class="content fs-7">
<i class="fa fa-caret-right"></i> Impressive single GPU performance out of the box <br>
<i class="fa fa-caret-right"></i> MNMG with <a href="https://docs.dask.org/en/stable/gpu.html" target="_blank"> RAPIDS + Dask</a> and <a href="https://nvidia.github.io/spark-rapids/" target="_blank">RAPIDS + Spark</a> <br>
<i class="fa light fa-caret-right"></i> HPC with <a href="https://docs.rapids.ai/deployment/stable/hpc.html" target="_blank">RAPIDS + Slurm</a> <br>
</div>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-message-code"></i> Open Source </h2>
<p> RAPIDS had its start from the <a href="https://arrow.apache.org/" target="_blank">Apache Arrow</a> and <a href="https://developer.nvidia.com/blog/goai-open-gpu-accelerated-data-analytics/" target="_blank">GoAi</a> projects based on a columnar, in-memory data structure that delivers efficient and fast data interchange with flexibility to support complex data models. </p>
<br>
<p> With <a href="https://developer.nvidia.com/rapids" target="_blank">NVIDIA backing</a>, it has maintained a focus on open source development (typically Apache 2.0 licensed) and collaboration with a broad community of cutting edge data science projects. </p>
</div>
</div>
<div id="accelerators"></div>
<h1 class="mt-10 mb-5"> PyData Accelerators </h1>
<div class="row">
<div class="col-md-6 py-3">
<h2><i class="fa-light fa-gauge-circle-bolt"></i> cuDF Pandas Accelerator Mode </h2>
<p>cuDF has a new pandas accelerator mode to speed up pandas workflows with zero code change. This is part of an on-going effort to streamline accelerated data science.
<a href="/cudf-pandas">Learn More on the Launch Page <i class="fa-solid fa-arrow-up-right"></i> </a> </p>
</div>
<div class="col-md-6 py-3"></div>
</div>
</div>
</div>
</section>
<!-- Use Cases -->
<div id="use-cases"></div>
<div class="top-slant-container">
<div class="top-slant-up has-background-rapids-gray"></div>
</div>
<section class="row section has-background-rapids-gray pb-9">
<div class="col">
<div class="container">
<h1 class="mb-4">Enterprise Use Cases</h1>
<div class="row">
<div class="col-md-6 py-3">
<h2><i class="fa-light fa-cart-shopping-fast"></i> Walmart + RAPIDS ML</h2>
<p> When you are a global-scale company, precision is everything. Learn how Walmart implemented XGBoost to increase forecast accuracy and potentially save billions of dollars.
<a href="https://www.datanami.com/2019/03/22/how-walmart-uses-gpus-for-better-demand-forecasting/" target="_blank">Read More <i class="fa-solid fa-arrow-up-right"></i> </a> </p>
</div>
<div class="col-md-6 py-3">
<h2><i class="fa-light fa-bee"></i> Bumble + RAPIDS ML</h2>
<p> Buzzwords is Bumble's open-source GPU-powered topic modelling tool, developed in house and building upon the work found in BERTopic and Top2Vec. Buzzwords uses cuML's UMAP and HDBSCAN algorithms.
<a href="https://medium.com/bumble-tech/multilingual-gpu-powered-topic-modelling-at-scale-dc8bd08609ef" target="_blank">Read More <i class="fa-solid fa-arrow-up-right"></i> </a> </p>
</div>
</div>
<div class="row">
<div class="col-md-6 py-3">
<h2><i class="fa-light fa-circle-phone-hangup"></i> AT&T + RAPIDS ETL</h2>
<p> AT&T was able to do more, faster by moving data science workloads to GPU. Hear about their analysis and use of NVIDIA capabilities across different domains and share specific use case examples, their efficiency gains, and corresponding impacts.
<a href="https://www.nvidia.com/en-us/on-demand/session/gtcfall22-a41235/" target="_blank">Hear More <i class="fa-solid fa-arrow-up-right"></i> </a> </p>
</div>
<div class="col-md-6 py-3">
<h2><i class="fa-brands fa-aws"></i> Amazon + RAPIDS GNN</h2>
<p> See how RAPIDS is enabling work on the very cutting edge by enabling Graph Neural Networks (GNN) for applications including drug discovery, recommender systems, fraud detection, and cybersecurity.
<a href="https://www.nvidia.com/en-us/on-demand/session/gtcfall22-a41386/" target="_blank">Hear More <i class="fa-solid fa-arrow-up-right"></i> </a> </p>
</div>
</div>
<div class="row">
<div class="col-md-6 py-3">
<h2><i class="fa-light fa-bolt"></i> More Industry Use Cases...</h2>
<p> Find more resources for industry specific ML, AI, and data science uses cases on NVIDIA's industry page.
<a href="https://www.nvidia.com/en-us/industries/" target="_blank">Read More <i class="fa-solid fa-arrow-up-right"></i> </a> </p>
</div>
<div class="col-md-6 py-3"> </div>
</div>
<h1 class="mt-10 mb-4">Data Science Research</h1>
<div class="row">
<div class="col-md-6 py-3">
<h2><i class="fa-light fa-chess-queen"></i> KGMON + RAPIDS</h2>
<p> Learn about Kaggle Grandmasters of NVIDIA (KGMoN), and see how they use RAPIDS to build winning recommender systems, predict degradation rates in RNA molecules, identify melanoma in medical imaging, and more.
<a href="https://www.nvidia.com/en-us/ai-data-science/kaggle-grandmasters/" target="_blank">Read More on the KGMON Page<i class="fa-solid fa-arrow-up-right"></i> </a> </p>
</div>
<div class="col-md-6 py-3">
<h2><i class="fa-light fa-book-bookmark"></i> Research Papers</h2>
<p> Using RAPIDS in your data science research and development? Let us know for opportunities to promote it. <a href="/branding">See the RAPIDS Citation Guide <i class="fa-solid fa-arrow-up-right"></i> </a> </p>
</div>
</div>
</div>
</div>
</section>
<div id="get-involved"></div>
<div class="bottom-slant-container">
<div class="bottom-slant-down has-background-rapids-gray"></div>
</div>
<!-- Engagement -->
<section class="row section padding-top-slant padding-bottom-slant">
<div class="col">
<div class="container">
<h1 class="mb-5"> Get Involved </h1>
<div class="row">
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-briefcase"></i> Business </h2>
<p>Use RAPIDS directly or through NVIDIA AI Enterprise, which provides extensive optimization, certified hardware profiles, and direct IT support.
<a href="https://www.nvidia.com/en-us/data-center/products/ai-enterprise/" target="_blank"> Read more about NVIDIA AI Enterprise<i class="fa-solid fa-arrow-up-right"></i> </a> </p>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-users-line"></i> Community </h2>
<p> Reach out and engage with the RAPIDS community on the following channels: </p>
<a href="/slack-invite" target="_blank"><i class="fa-brands fa-slack"></i> Slack Channel <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://stackoverflow.com/tags/rapids" target="_blank"><i class="fa-brands fa-stack-overflow"></i> Stack Overflow <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://twitter.com/rapidsai" target="_blank"><i class="fa-brands fa-twitter"></i> X/Twitter <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://developer.nvidia.com/blog/tag/rapids/" target="_blank"><i class="fa-light fa-square-rss"></i> NVIDIA Developer Blogs <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
</div>
<div class="col-md-4 py-3">
<h2><i class="fa-light fa-bullhorn"></i> Evangelism </h2>
<p> Promote and foster more use of RAPIDS with these Deep Learning Institute (DLI) and Launchpad</a> courses: </p>
<a href="https://courses.nvidia.com/courses/course-v1:DLI+S-DS-01+V1/" target="_blank">Accelerating End-to-End Data Science Workflows <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://courses.nvidia.com/courses/course-v1:DLI+S-DS-01+V1/" target="_blank">Fundamentals of Accelerated Data Science <i class="fa-solid fa-arrow-up-right"></i> </a> <br>
<a href="https://www.nvidia.com/en-us/launchpad/" target="_blank">NVIDIA LaunchPad Data Science Lab <i class="fa-solid fa-arrow-up-right"></i></a>
</div>
</div>
</div>
</div>
</section>
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---
title: API Docs | RAPIDS
description: Library API Documentation
draft: true
---
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{{< hero hero-text="API Documentation" button-link="#" button-text="API Docs" >}}
## Question 1
text text
## Question 2
text text
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---
title: Docs | RAPIDS
description: Documentation Resources
draft: true
---
<!-- Hero Shortcode -->
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## Heading
text text text
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---
title: Build and Test Automation
draft: true
---
## Overview
This is how our automated build and test processes work.
## Pull Request Testing
This is how pull requests are built
## Releases
This is how we do releases
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---
layout: default
nav_order: 4
parent: Maintainer Docs
title: Testing Practices
---
# Testing Practices
## Overview
Summary of the testing practices used by RAPIDS projects.
### Intended audience
Developers
{: .label .label-green}
Project Leads
{: .label .label-blue}
Operations
{: .label .label-purple}
## Infrastructure
Overall goal, follow the open source ecosystem for infrastructure choices
### GitHub Actions
See docs [here]({% link resources/github-actions.md %}).
### GitHub
- All projects are hosted on GitHub for open source visibility
### Docker
- Industry standard for containerized software
- Allows for isolating all builds
## Code Style / Formatting
- Run style checks and/or auto-formatters per commit to ensure code is uniformly formatted in a clean and consistent way before it is ever merged to the repository
- Handles things like maximum line length, trailing whitespace, linebreak semantics, etc.
### Follow open source ecosystem in use of code formatters
- C++
- Clang-Format (Planned)
- Python
- Flake8
- Auto-formatting with Black (Planned)
## Unit Testing
- Runs per commit to ensure code is never pushed in a broken state
- Reports back to github to give end user feedback of exactly what the issue(s) is
- Matrix of tests across supported Operating System / CUDA / Python versions along with running through CUDA-memcheck (planned)
- Tests that project builds successfully both with and without GPUs, and then ensures that the suite of unit tests run successfully with GPUs
- Tests building of packages for conda and pip
- Tests are designed as black box tests for both external user facing functions and internal functions
- Tests are written to compare against Pandas / Numpy / Scikit-Learn / NetworkX / etc. to ensure the results are completely in line with expectations of end users
### Follow open source ecosystem in use of testing frameworks
- C++
- GTest
- [https://github.com/google/googletest/blob/master/googletest/docs/primer.md](https://github.com/google/googletest/blob/master/googletest/docs/primer.md)
- I.E. cuDF GTests:
- [https://github.com/rapidsai/cudf/tree/branch-0.7/cpp/tests](https://github.com/rapidsai/cudf/tree/branch-0.7/cpp/tests)
- Python
- Pytest
- [https://docs.pytest.org/en/latest/getting-started.html](https://docs.pytest.org/en/latest/getting-started.html)
- I.E. cuDF PyTests:
- [https://github.com/rapidsai/cudf/tree/branch-0.7/python/cudf/tests](https://github.com/rapidsai/cudf/tree/branch-0.7/python/cudf/tests)
## Datasets
- Many tests depend on the presence of specific datasets in order to properly verify code correctness. See [datasets]({% link maintainers/datasets.md %}) for more details.
## Integration / Workflow Testing and Benchmarking
- Runs nightly to ensure the different libraries integrate as expected similar to how other Python libraries integrate (i.e. cuDF with cuML vs Pandas with SKLearn)
- In addition to checking the runs succeed without error and checking correctness, measures performance regressions in the workflows
- Pipe output of Google Benchmark into ASV dashboards for easy consumption
- Run with profiling and dump an nvprof / nsight profile per workflow for easy analysis by developers (planned)
- Allows for naturally using example / workflow notebooks for integration / workflow / performance testing as well
- Matrix of tests across supported Operating System / CUDA / Python versions
### Follow open source ecosystem in use of testing frameworks
- C++
- GTest
- Google Benchmark (Planned)
- [https://github.com/google/benchmark#example-usage](https://github.com/google/benchmark#example-usage)
- Python
- Pytest
- Airspeed Velocity (ASV)
- [https://asv.readthedocs.io/en/stable/using.html](https://asv.readthedocs.io/en/stable/using.html)
## Packaging and Release
- Follow open source ecosystem in packaging and delivery mechanisms:
- Conda
- Pip
- Docker
- Releases
- Release every ~6 weeks with no known critical bugs
- Allows users to have a stable release that won't introduce performance regressions / bugs during the development process
- Full set of unit / integration / workflow tests are performed before publish packages / containers
- "Nightlies"
- Allows cutting edge users to install the latest conda package to test new functionality coming in the next release
- Conda packages are created for each project on a per merge basis
- Docker containers are built nightly and have integration tests run and must pass before publishing containers
## Examples of Testing in Action
- DLPack support for cuDF
- [https://github.com/rapidsai/cudf/pull/913](https://github.com/rapidsai/cudf/pull/913)
- C++ implementation with GTest unit tests
- [https://github.com/rapidsai/cudf/pull/1159](https://github.com/rapidsai/cudf/pull/1159)
- Python bindings implementation with PyTest unit tests and integration correctness tests with CuPy/Chainer
- Found some additional issues in other libraries implementations that required some fixes in the C++ implementation
- String support for cuDF
- [https://github.com/rapidsai/cudf/pull/1032](https://github.com/rapidsai/cudf/pull/1032)
- C++ implementation and Python bindings
- Originally depended on an unreleased version of a different library so CI builds failed and prevented merging into the main repository until it was resolved
- GTests and PyTest unit tests where results of each incrementally drove development across both C++ and Python
- Heavily uses unit test parameterization to effectively test different function parameters for sufficient test coverage
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---
layout: default
nav_order: 2
parent: Maintainer Docs
title: Dependency Management
---
# Dependency Management Documentation
## Overview
Outlines how to test and change dependencies of the RAPIDS projects
### Intended audience
Developers
{: .label .label-green}
Project Leads
{: .label .label-blue}
Operations
{: .label .label-purple}
## Adding a Dependency
The [RAPIDS Integration repository](https://github.com/rapidsai/integration) contains all the information needed for adding a dependency to the RAPIDS projects. Which `meta.yaml` changed is based on the purpose of the package being installed. The purpose of each meta-package is listed below:
Package Name | Purpose
--- | ---
`rapids-build-env` | Installs all `conda` build dependencies to build & test RAPIDS libraries from source
`rapids-doc-env` | Installs all tools needed to build RAPIDS documentation
`rapids-notebook-env` | Installs a Jupyter Notebook server and other dependencies to run RAPIDS example notebooks; used in the `runtime` [stable](https://hub.docker.com/r/rapidsai/rapidsai/tags?page=1&name=runtime) and [nightly](https://hub.docker.com/r/rapidsai/rapidsai-nightly/tags?page=1&name=runtime) RAPIDS containers.
### Adding Versions
For new packages or those that do not have defined versions they need to be
added.
#### Modifying Recipes
To add a package with versioning to the recipe a `PACKAGE_NAME` and
the `VERSIONING_NAME` must be added to the file.
- `PACKAGE_NAME` - is the conda package name
- `VERSIONING_NAME` - is the conda package name with `-` replaced with `_` and a suffix of `_version` added
- For example
- `cupy` would become `cupy_version`
- `scikit-learn` would become `scikit_learn_version`
Once the `PACKAGE_NAME` and `VERSIONING_NAME` are ready, add them to
the `meta.yml` as follows:
```
PACKAGE_NAME {% raw %}{{ VERSIONING_NAME }}{% endraw %}
```
- **NOTE:** The `VERSIONING_NAME` must be surrounded by the `{% raw %}{{ }}{% endraw %}` for the substitution to work.
Using the examples of `cupy` and `scikit-learn` the entries in the `meta.yaml` would be:
```
cupy {% raw %}{{ cupy_version }}{% endraw %}
```
```
scikit-learn {% raw %}{{ scikit_learn_version }}{% endraw %}
```
#### Modifying Versions Files
There are two versions files that are in `conda/recipes`:
- `release-versions.yaml` - These are versions used by the `ci/axis/release.yaml` for RELEASE builds
- `nightly-versions.yaml` - These are versions used by the `ci/axis/nightly.yaml` for NIGHTLY builds
Both of these files will need a config added to specify the version for the
newly created `VERSIONING_NAME`.
For each `VERSIONING_NAME` there must be a `VERSION_SPEC`. This can be any of the
standard `conda` version specifiers:
```
>=1.8.0
>=0.48,<0.49
>=7.0,<8.0.0a0,!=7.1.0
=2.5.*
```
Combined together each of the versions files would add the following for each
`VERSIONING_NAME`:
```
VERSIONING_NAME:
- 'VERSION_SPEC'
```
Using the examples of `cupy` and `scikit-learn` the entries in the `*-versions.yaml` would be:
```
cupy_version:
- '>=7,<8.0.0a0,!=7.1.0'
```
```
scikit_learn_version:
- '=0.21.3'
```
### Updating Versions
There are two versions files that are in `conda/recipes`:
- `release-versions.yaml` - These are versions used by the `ci/axis/release.yaml` for RELEASE builds
- `nightly-versions.yaml` - These are versions used by the `ci/axis/nightly.yaml` for NIGHTLY builds
Edit the files above and update the `VERSION_SPEC` as desired.
For more information see the [Modifying Versions Files](#modifying-versions-files)
Once done, submit a PR to the `integration` repository. The changes will be built and tested on a development docker image to confirm that it doesn't conflict with other RAPIDS libraries.
## Testing a Dependency
The build scripts located in the `ci/gpu` folder of the project can be easily modified to test a dependency. For example, the [build script for cuDF](https://github.com/rapidsai/cudf/blob/branch-0.14/ci/gpu/build.sh) may contain these lines to install packages required to build from source and test notebooks. To test a new dependency before adding to or updating the integration repo, follow these steps:
```
conda install "rmm=$MINOR_VERSION.*" "rapids-build-env=$MINOR_VERSION.*" \
"rapids-notebook-env=$MINOR_VERSION.*"
```
`rapids-build-env` and `rapids-notebook-env` are meta-packages that are used to keep dependencies across the projects consistent. These packages have various packages with specific versions listed as its dependencies. To change these dependencies as a test on a PR, the meta-package should be removed. Removing it allows the installation of different versions of dependencies without causing conda conflicts. Here is what to add to the script to allow this:
```
conda install "rmm=$MINOR_VERSION.*" "rapids-build-env=$MINOR_VERSION.*" \
"rapids-notebook-env=$MINOR_VERSION.*"
conda remove --force rapids-build-env rapids-notebook-env
conda install "your-pkg=1.0.0"
```
With this method, dependency changes can be tested inside a PR. However, this should only be used as a temporary test, and not a permanent change. Once it is confirmed that the change works, the new dependency should be updated or added to the `integration` repository.
**Important**: Please note that the `conda remove --force...` command does NOT work with `mamba remove --force...`. See [mamba-org/mamba#412](https://github.com/mamba-org/mamba/issues/412).
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rapidsai_public_repos/rapids.ai/content/docs/maintainers/forward-merger.md
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---
layout: default
nav_order: 3
parent: Maintainer Docs
title: Forward Mergers
---
# Forward Mergers
## Overview
The forward mergers are automated pull requests to merge a branch in burndown into the next versioned branch. For example merging `branch-22.12` into `branch-23.02`. This ensures all changes to the current branch are reflected in the next version.
The forward merger jobs are located here: [https://gpuci.gpuopenanalytics.com/job/rapidsai/job/forward-mergers/](https://gpuci.gpuopenanalytics.com/job/rapidsai/job/forward-mergers/)
### Intended audience
Developers
{: .label .label-green}
Project Leads
{: .label .label-blue}
Operations
{: .label .label-purple}
## Forward Mergers
During the release process, the branch for the next release is created and set as default. Once this happens, the forward-merger branch jobs are activated. Forward-mergers automatically merge any commits made to the release branch to the latest default branch during burn down.
**When Forward Merging Fails**
It is important to note that the forward-merge jobs will sometimes fail due to merge conflicts, and will request a manual merge to be done. *Never* use the GitHub Web UI to fix the merge conflicts as it will cause changes in the default branch to be merged into the release branch. Please use the following steps to fix the merge conflicts manually:
Using the example of `branch-{{ site.data.releases.stable.version }}` release branch and a new default `branch-{{ site.data.releases.nightly.version }}`.
```
git checkout branch-{{ site.data.releases.stable.version }}
git pull <rapidsai remote>
git checkout branch-{{ site.data.releases.nightly.version }}
git pull <rapidsai remote>
git checkout -b branch-{{ site.data.releases.nightly.version }}-merge-{{ site.data.releases.stable.version }}
git merge --no-squash branch-{{ site.data.releases.stable.version }}
# Fix any merge conflicts caused by this merge
git commit -am "Merge branch-{{ site.data.releases.stable.version }} into branch-{{ site.data.releases.nightly.version }}"
git push <personal fork> branch-{{ site.data.releases.nightly.version }}-merge-{{ site.data.releases.stable.version }}
```
Once this is done, open a PR that targets the new default branch (`branch-{{ site.data.releases.nightly.version }}` in this example) with your changes.
**IMPORTANT**: When merging this PR, do not use the [auto-merger]({% link resources/auto-merger.md %}) (i.e. the `/merge` comment). Instead, an admin must manually merge by changing the merging strategy to `Create a Merge Commit`. Otherwise, history will be lost and the branches become incompatible.
Once this PR is approved and merged, the original forward-merger PR should automatically be merged since it will contain the same commit hashes.
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rapidsai_public_repos/rapids.ai/content/docs/maintainers/datasets.md
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---
layout: default
nav_order: 1
parent: Maintainer Docs
title: Datasets
---
# Datasets
## Overview
Many tests depend on the presence of specific datasets in order to properly verify code correctness. Some datasets are small enough that they can be included with the source code, but others are relatively large and cannot practically coexist with the source. In both cases, a test author should not write a test to assume datasets are located in a particular place (either with a relative path, since the executable could be moved, or an absolute path, since different machines will likely use different absolute paths), and should instead allow for the location of the datasets to be provided by a user.
### Intended audience
Developers
{: .label .label-green}
Project Leads
{: .label .label-blue}
Operations
{: .label .label-purple}
## Running Tests That Use Datasets
Tests using the RAPIDS dataset locating utilities (see below) allow a user to specify the location of datasets using one of the following mechanisms:
### The `RAPIDS_DATASET_ROOT_DIR` option to `cmake`
The `cmake` command responsible for building the test executables supports the option `RAPIDS_DATASET_ROOT_DIR`, which can be used as shown below:
```
cmake -DRAPIDS_DATASET_ROOT_DIR=/location/to/datasets
```
This mechanism allows a user building tests from source to create test executables that will find their datasets in the directory specified.
### The `RAPIDS_DATASET_ROOT_DIR` environment variable
If a user needs to override the `RAPIDS_DATASET_ROOT_DIR` build option, or if the build option was not used, the `RAPIDS_DATASET_ROOT_DIR` environment variable can be set to the location of the datasets.
This environment variable takes precedence over the build option, meaning both options can be used. This can be useful for experimenting on different datasets without requiring a rebuild, or for running the test binaries on a different system that has the datasets installed to an alternate location. The environment variable can be set as shown below prior to running the tests (showing a bash shell):
```
export RAPIDS_DATASET_ROOT_DIR=/location/to/datasets
```
### The built-in `/datasets` default
Finally, if neither the build option nor the environment variable are set, tests using the RAPIDS dataset locating utilities will default to `/datasets` as the location where datasets will be accessed.
## Writing Tests That Use Datasets
Test developers can use the RAPIDS dataset locating utilities by calling the following function:
```
const std::string& get_rapids_dataset_root_dir()
```
`get_rapids_dataset_root_dir()` will return a `std::string` reference to the root directory containing the datasets, as determined by the user-accessible options described above, or a default value of `/datasets` if the user did not use the options.
### Example API usage
```
const std::string& rapidsDatasetRootDir = get_rapids_dataset_root_dir();
readDataset(rapidsDatasetRootDir + "/golden_data/web-BerkStan.pagerank_val_0.85.bin");
```
### Best Practices
- Test authors should document the relative paths under the datasets root dir that tests require in a README or similar document.
- Instructions on how to obtain the datasets (if they are not included with the source) should also be included in a README or similar document. Optionally, a description of each dataset should be included as well if it's useful.
- Test authors should consider using test fixtures that have a `Setup()` method that ensures the datasets exist prior to accessing them. The `Setup()` method should throw an exception with the path to the dataset the test is using so users know to set or check one of the dataset location override mechanisms if necessary.
*NOTE: At the moment, only the `cugraph` library has adopted the `get_rapids_dataset_root_dir()` functionality.*
## Datasets for benchmarks
Developers and end users alike may need to run benchmarks to evaluate the performance of RAPIDS libraries. Benchmarks currently vary from RAPIDS repo to repo in how they're written, how they need to be run, and if and how they use datasets. At the moment, only the `cugraph` library has standardized on a convention for benchmark datasets, as described below:
- Datasets for both tests and benchmarks are located in `<repo root>/datasets`. This allows benchmark developers to use the same dataset locating APIs (`get_rapids_dataset_root_dir()`, etc.) with the same settings described above for running tests.
- Some datasets are small enough that they can be included in the repository with the source code. This is convenient for certain cases where a very small dataset is acceptable, but larger datasets must not be committed due to limitations of the source repository. Instead, larger datasets (approximately 2MB or larger) should be hosted separately and made available to download and install via the script described below.
- A script is provided for downloading and installing different datasets for different use cases. The `-h` option to the script will describe the options available. For cugraph benchmarks, run the script with the `--benchmark` option from the `datasets` dir:
```
cd <repo root>/datasets
./get_test_data.sh --benchmark
```
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rapidsai_public_repos/rapids.ai/content/docs/maintainers/maintainers.md
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---
layout: default
title: Maintainer Docs
nav_order: 6
has_children: true
permalink: maintainers
---
# RAPIDS Maintainers Docs
{:.no_toc}
RAPIDS projects use an established set of guidelines and procedures for all projects. These are available for the community to review and provide feedback on.
{: .fs-6 .fw-300 }
### Intended audience
Developers
{: .label .label-green}
Project Leads
{: .label .label-blue}
Operations
{: .label .label-purple}
## Release v{{ site.data.releases.nightly.version }} Schedule
**NOTE:** *Dates are subject to change at anytime. Completed release schedules are posted [here]({% link releases/schedule.md %}).*
Phase | Start | End | Duration
-- | -- | -- | --
Development (cuDF/RMM/rapids-cmake/cugraph-ops/raft/dask-cuda/ucx-py) | {{ site.data.releases.nightly.cudf_dev.start | date: "%a, %b %e, %Y" }} | {{ site.data.releases.nightly.cudf_dev.end | date: "%a, %b %e, %Y" }} | {{ site.data.releases.nightly.cudf_dev.days }} days
Development (others) | {{ site.data.releases.nightly.other_dev.start | date: "%a, %b %e, %Y" }} | {{ site.data.releases.nightly.other_dev.end | date: "%a, %b %e, %Y" }} | {{ site.data.releases.nightly.other_dev.days }} days
[Burn Down]({% link releases/process.md %}#burn-down)(cuDF/RMM/rapids-cmake/cugraph-ops/raft/dask-cuda/ucx-py) | {{ site.data.releases.nightly.cudf_burndown.start | date: "%a, %b %e, %Y" }} | {{ site.data.releases.nightly.cudf_burndown.end | date: "%a, %b %e, %Y" }} | {{ site.data.releases.nightly.cudf_burndown.days }} days
[Burn Down]({% link releases/process.md %}#burn-down) (others) | {{ site.data.releases.nightly.other_burndown.start | date: "%a, %b %e, %Y" }} | {{ site.data.releases.nightly.other_burndown.end | date: "%a, %b %e, %Y" }} | {{ site.data.releases.nightly.other_burndown.days }} days
[Code Freeze/Testing]({% link releases/process.md %}#code-freeze) (cuDF/RMM/rapids-cmake/cugraph-ops/raft/dask-cuda/ucx-py) [^1] | {{ site.data.releases.nightly.cudf_codefreeze.start | date: "%a, %b %e, %Y" }} | {{ site.data.releases.nightly.cudf_codefreeze.end | date: "%a, %b %e, %Y" }} | {{ site.data.releases.nightly.cudf_codefreeze.days }} days
[Code Freeze/Testing]({% link releases/process.md %}#code-freeze) (others) | {{ site.data.releases.nightly.other_codefreeze.start | date: "%a, %b %e, %Y" }} | {{ site.data.releases.nightly.other_codefreeze.end | date: "%a, %b %e, %Y" }} | {{ site.data.releases.nightly.other_codefreeze.days }} days
[Release]({% link releases/process.md %}#releasing) | {{ site.data.releases.nightly.release.start | date: "%a, %b %e, %Y" }} | {{ site.data.releases.nightly.release.end | date: "%a, %b %e, %Y" }} | {{ site.data.releases.nightly.release.days }} days
## _PROPOSED_ Release v{{ site.data.releases.next_nightly.version }} Schedule
Phase | Start | End | Duration
-- | -- | -- | --
Development (cuDF/RMM/rapids-cmake/cugraph-ops/raft/dask-cuda/ucx-py) | {{ site.data.releases.next_nightly.cudf_dev.start | date: "%a, %b %e, %Y" }} | {{ site.data.releases.next_nightly.cudf_dev.end | date: "%a, %b %e, %Y" }} | {{ site.data.releases.next_nightly.cudf_dev.days }} days
Development (others) | {{ site.data.releases.next_nightly.other_dev.start | date: "%a, %b %e, %Y" }} | {{ site.data.releases.next_nightly.other_dev.end | date: "%a, %b %e, %Y" }} | {{ site.data.releases.next_nightly.other_dev.days }} days
[Burn Down]({% link releases/process.md %}#burn-down)(cuDF/RMM/rapids-cmake/cugraph-ops/raft/dask-cuda/ucx-py) | {{ site.data.releases.next_nightly.cudf_burndown.start | date: "%a, %b %e, %Y" }} | {{ site.data.releases.next_nightly.cudf_burndown.end | date: "%a, %b %e, %Y" }} | {{ site.data.releases.next_nightly.cudf_burndown.days }} days
[Burn Down]({% link releases/process.md %}#burn-down) (others) | {{ site.data.releases.next_nightly.other_burndown.start | date: "%a, %b %e, %Y" }} | {{ site.data.releases.next_nightly.other_burndown.end | date: "%a, %b %e, %Y" }} | {{ site.data.releases.next_nightly.other_burndown.days }} days
[Code Freeze/Testing]({% link releases/process.md %}#code-freeze) (cuDF/RMM/rapids-cmake/cugraph-ops/raft/dask-cuda/ucx-py) [^1] | {{ site.data.releases.next_nightly.cudf_codefreeze.start | date: "%a, %b %e, %Y" }} | {{ site.data.releases.next_nightly.cudf_codefreeze.end | date: "%a, %b %e, %Y" }} | {{ site.data.releases.next_nightly.cudf_codefreeze.days }} days
[Code Freeze/Testing]({% link releases/process.md %}#code-freeze) (others) | {{ site.data.releases.next_nightly.other_codefreeze.start | date: "%a, %b %e, %Y" }} | {{ site.data.releases.next_nightly.other_codefreeze.end | date: "%a, %b %e, %Y" }} | {{ site.data.releases.next_nightly.other_codefreeze.days }} days
[Release]({% link releases/process.md %}#releasing) | {{ site.data.releases.next_nightly.release.start | date: "%a, %b %e, %Y" }} | {{ site.data.releases.next_nightly.release.end | date: "%a, %b %e, %Y" }} | {{ site.data.releases.next_nightly.release.days }} days
[^1]: Cross-library dependencies are pinned during this time-frame. For example: Dask and Distributed.
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rapidsai_public_repos/rapids.ai/content/docs/maintainers
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rapidsai_public_repos/rapids.ai/content/docs/maintainers/releases/releases.md
|
---
layout: default
title: Release Docs
parent: Maintainer Docs
nav_order: 6
has_children: true
permalink: releases
---
# Releases
{:.no_toc}
Releases are planned using the processes and schedules outlined below.
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rapidsai_public_repos/rapids.ai/content/docs/maintainers
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rapidsai_public_repos/rapids.ai/content/docs/maintainers/releases/triage.md
|
---
layout: default
nav_order: 1
parent: Release Docs
grand_parent: Maintainer Docs
title: Issue Triage
---
# Issue Triage
## Overview
Summary of the issue triage methodology used for RAPIDS projects.
### Intended audience
Developers
{: .label .label-green}
Project Leads
{: .label .label-blue}
## Triage goals
RAPIDS projects are continuously triaging new issues and re-triaging existing issues frequently. This is to ensure that high priority issues are remedied in a timely manner and the community receives frequent updates on a filed issue.
## Triage process
### Timing
- Label and prioritize new issues within **2 business days**
- Re-prioritize existing issues **every week** using the project's issue tracking boards
### Tracking boards
For each project there are 3 issue tracking boards and 1 release tracking board:
- [Bug Squashing](https://github.com/rapidsai/cudf/projects/1) - track and prioritize bugs
- [Feature Planning](https://github.com/rapidsai/cudf/projects/9) - track and prioritize feature requests
- [Other Issues](https://github.com/rapidsai/cudf/projects/10) - track documentation, questions, and other issues
- [Release](https://github.com/rapidsai/cudf/projects/14) - tracks the progress of the current release
Bug Squashing, Feature Planning and Other Issues are permanent tracking boards, and are used as the basis for release planning. The Release board is not permanent and is closed once a release is completed. The example boards above are from the [cuDF](https://github.com/rapidsai/cudf) project.
Each permanent project board (Bug Squashing, Feature Planning,and Other Issues) has the following columns:
| Column | Purpose |
|:-------|:--------|
| Needs prioritizing | Issues that have gone through the `Initial triage` phase and now need to be prioritized |
| Hotfix - current release | Hotfix issues that need to be addressed immediately for the current `M.A` release |
| Next release | Issues that should tackled during the current development cycle for the next `M.B` release |
| Future release | Issues that should be prioritized for the next `M.C` or `M.D` releases |
| Backlog | All other open issues |
| Closed | Issues that are closed will **automatically** be moved to this column |
See [Release Board](https://docs.rapids.ai/releases/planning/) for the column definition that pertain to the Release Board.
**IMPORTANT:**
In leveraging the tracking boards for issue management, project leads can _schedule_ issues by placing them in the appropriate column and then _prioritize_ issues by dragging & sorting the issues from highest priority at the top of the column to lowest at the bottom. We can also use labels on the issues/PRs to filter and _prioritize_ work.
By placing the issues in one of these permanent boards (Bug Squashing, Feature Planning, or Other Issues) filers and the community will see updates to the issue and can get a sense of when they can expect feedback. For example, on a given issue a user may see `Future release in Other Issues` and this allows the filer or the community to comment on if they believe the issue should be addressed faster.
## Process cycle
The general process cycle for every issue is:
```
/------------> Hotfix --> Assign developer --> Link to PR --> Automatically close issue on PR merge
|
New issue filed --> Initial triage --> Prioritize & schedule --> Next release --> Prioritize in release --> Assign developer --> Link to PR --> Automatically close issue on PR merge
|
\------------> Future release --> Re-prioritize every week
```
Issues can be closed during the `Initial triage` step and will be appropriately documented as to why. Examples include: duplicate issues, issues determined to be out of scope, and/or issues that won't be fixed.
### New issue filed
New issues are typically filed with an issue template from the project. This automatically labels an issue with the type of the issue and the <span class="label" style="background: #e99695; color: #44434d; text-transform: none">? - Needs Triage</span> label. This helps identify and move issues to the correct project boards for triage.
For issues not using the issue template, these should be marked with the <span class="label" style="background: #e99695; color: #44434d; text-transform: none">? - Needs Triage</span> label and correct issue type label. Once labeled they should be moved to the appropriate project board for the given issue type.
### Finding issues
Each tracking board type has a filter that can be used on when using the `Add cards` feature. This limits the results displayed to those that are for the tracking board and does not show pull requests.
| Board | Filter |
|:------|:-------|
| Bug Squashing | `is:open is:issue label:bug no:project` |
| Feature Planning | `is:open is:issue label:"feature request" no:project` |
| Other Issues | `is:open is:issue -label:bug -label:"feature request" no:project` |
### Initial triage
Project Leads - Daily
{: .label .label-blue}
1. Ensure the issue type is correct, i.e. is the issue really a bug or is it a feature request?
2. Review the content of the issue, has the filer provided all of the needed information for that issue type? If not, ask for clarification.
3. Add any relevant project labels like `cuda`, `python`, etc.
4. Consider adding <span class="label" style="background: #7057ff; color: #ffffff; text-transform: none">good first issue</span> or <span class="label" style="background: #008672; color: #ffffff; text-transform: none">help wanted</span> labels to the issue if applicable.
4. Remove the <span class="label" style="background: #e99695; color: #44434d; text-transform: none">? - Needs Triage</span> label.
5. Move issue to its associated tracking board. This will place the issue in the `Needs prioritizing` column of that board and read for the next phase.
### Prioritize & schedule
Once issues have been triaged, we can prioritize and schedule them for a release.
**IMPORTANT:** By leveraging the tracking boards for issues, project leads can _schedule_ issues by placing them in the appropriate column and then _prioritize_ issues by dragging & sorting the issues from highest priority at the top of the column to lowest at the bottom.
Project Leads - Daily
{: .label .label-blue}
1. For each issue in the `Needs prioritizing` column, review the issue and prioritize it.
2. For issues added to `Hotfix` and `Next release` columns follow the steps below.
3. Repeat this process for all 3 tracking boards.
Project Leads - Weekly
{: .label .label-blue}
1. Archvie all issues in the `Closed` column.
2. Review all issues in each column of `Next release`, `Future release`, and `Backlog` to make sure issues are still scheduled appropriately.
3. Prioritize any issues in `Future release`, and `Backlog` columns. `Hotfix` and `Next release` do not need to be re-prioritized as they should be in active development already.
4. Discuss the status of all issues with the team in `Hotfix` and `Next release` columns to ensure development progress is being made and there are no blockers.
5. Repeat this process for all 3 tracking boards.
#### Hotfix
1. Verify the issue is a [hotfix]({% link releases/hotfix.md %}).
2. Identify the project lead(s) needed to resolve the hotfix.
3. Host a meeting about the proposed hotfix with the stakeholders and operations to determine the path forward.
4. Assign a developer or team to fix the issue ASAP.
#### Next release
1. Ensure each issue is added to the release board project.
2. Communicate to the team the priority of the issue.
3. Update the issue on the release board with the agreed upon priority.
4. Based on priority of the issue assign a developer or wait for other higher priority issues to be completed first.
### Assign developer
Developers should be assigned to issues they are responsible for delivering. Try to limit overcommitting developers. A general rule is to limit active development to **5 or fewer** issues.
**IMPORTANT:** This is crucial for community involvement as an assigned issue looks like the issue is covered and won't receive any input or help.
### Link to PR
Every pull request should have the issue number in the descriptions of the PR with `Addresses #[issue number]` so when the PR is merged the issue that created the PR will automatically close as well.
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rapidsai_public_repos/rapids.ai/content/docs/maintainers
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rapidsai_public_repos/rapids.ai/content/docs/maintainers/releases/planning.md
|
---
layout: default
nav_order: 2
parent: Release Docs
grand_parent: Maintainer Docs
title: Release Planning
---
# Release Planning
## Overview
Summary of the release planning process used by RAPIDS projects.
### Intended audience
Project Leads
{: .label .label-blue}
### See also
- [Versions and Tags]({% link resources/versions.md %})
- [Release Process]({% link releases/process.md %})
## Planning process
### Timing
**NOTE:** The processes below use the current release of `M.A`, the next release of `M.B` and future release `M.C` (where `B=A+1`, `C=B+1`) for examples.
Releases are planned in two phases:
1. `Fuzzy planning` from [Issue Triage]({% link releases/triage.md %}) which is ongoing.
2. `Focus planning` which starts when release `M.B` is **frozen**.
### Release boards
RAPIDS projects use GitHub project boards for tracking releases with a customized setup and automation that is copied from existing boards.
For each project there is a Release board for each release. As an example [v0.5 Release](https://github.com/rapidsai/cudf/projects/5) tracks the progress for the v0.5 release. Release boards are closed once a release is completed, and are labeled `vM.A Release` where `M` & `A` are the major & minor release version numbers.
Each Release board has the following columns:
| Column | Purpose |
|:-------|:--------|
| Issue-Needs prioritizing | Issues that have gone through the [Issue Triage]({% link releases/triage.md %}) process and need to be prioritized |
| Issue-P0 | Issues that should be worked on first |
| Issue-P1 | Issues that should be worked on only if all `P0` issues are complete or assigned |
| Issue-P2 | Issues that should be worked on only if all `P1` issues are complete or assigned |
| PR-WIP | Newly opened PRs and re-opened PRs |
| PR-Needs Review | PRs move **automatically** to this column when pending approval by reviewer |
| PR-Reviewer approved | PRs move **automatically** to this column when approved by reviewer |
| Done | Issues and PRs that are closed will **automatically** be moved to this column |
**IMPORTANT:** By leveraging the Release board for issues, Project Leads can _schedule_ issues by placing them in the appropriate column and then _prioritize_ issues by dragging & sorting the issues from highest priority at the top of the column to lowest at the bottom. We can also use labels on the issues/PRs to filter and _prioritize_ work.
#### Using the release board
- Assigning and priortizing work
- Scroll to the left to see all the columns labeled `Issue-*`
- Re-prioritize issues in `P0`, `P1`, `P2` by moving issuses between columns
- Move high priority issues within a column to the top; this promotes "pop off the top of the stack" development
- Expediting and finishing work
- Scroll to the right to see all columns labeled `PR-*`
- Identify PRs that need reviewers, input from authors, and other help
### Fuzzy planning
During `Fuzzy planning` issues are triaged and scheduled in their respective tracking boards. This naturally creates a pool of issues to consider from across the tracking boards during `Focus planning` under the columns `Future release`.
### Focus planning
Once a **freeze** has occurred for the release that is a WIP (i.e. release `M.B`), then planning for release `M.C` will start.
Project Leads
{: .label .label-blue}
1. Review all issues in the current WIP release `M.B` and find issues that will slip.
2. Move issues that will not make the release `M.B` to the release board for `M.C`.
3. Review each of the tracking boards and examine all issues in the `Future release` columns.
4. Add issues determined to be in-scope for the `M.C` release to the release board and move the issue to the `Next release` column in the tracking board.
5. Prioritize all issues into columns `P0`, `P1`, or `P2` on the `M.C` release board with input from project leads.
6. Rank issues within columns `P0`, `P1`, or `P2` to communicate priority for developers.
7. Review with team on day after release of `M.B` for feedback and input before adopting as the initial release plan.
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rapidsai_public_repos/rapids.ai/content/docs/maintainers/releases/process.md
|
---
layout: default
nav_order: 3
parent: Release Docs
grand_parent: Maintainer Docs
title: Release Process
---
# Release Process
## Overview
Summary of the RAPIDS release process for major and minor releases.
### Intended audience
Project Leads
{: .label .label-blue}
Operations
{: .label .label-purple}
### See also
* [Git branching model]({% link resources/git.md %})
* [Major and minor release versioning]({% link resources/versions.md %})
## Git branching model
RAPIDS uses a custom git branching model, adapted from git-flow to leverage the tools GitHub provides and also focus on release-driven development. From more details see our guide for our [git branching]({% link resources/git.md %}) methodology.
### Migrating projects
For RAPIDS projects that are using another branching/development model, continue to develop with that approach until the next **minor** release. Given the version `M.A.0` (where `M` is the major version and `A` is the minor version), create a development branch `branch-M.B` where `B=A+1` from the `main` branch that has the latest minor release.
From this point forward you can follow the git branching & release model used by the RAPIDS team.
## Major and minor releases
Both major and minor releases follow the same steps with little variation. For both, release types there are two key dates that need to be known well in advance:
* `Burn down date`
* `Code freeze date`
* `Release date`
The `burn down date` will always be several days before the `code freeze date` which in turn is several days before the `release date`. This is to ensure there is enough time to finish active development, and to handle any unknown bugs/issues.
### Hotfixes
Hotfixes have their own process and are described [here]({% link releases/hotfix.md %}).
## Burn down
Burn down is the process of locking down all issues slated for the release and moving issues not in this release to the following release. Additionally, all pending pull requests should be reviewed and aim to be merged before the code freeze date.
### Timing
For the selection of a `burn down date`, the general guidelines should be followed:
* Choose a `burn down date` at least **3 business days** before a `code freeze date`
* Consult project leads to ensure key features will make the release with the anticipated date
* Communicate the decided `burn down date` to the development team immediately to ensure they can meet the deadline
Burn down ends at 11:59 PM PT on the final day of the process.
### Process
**NOTE:** The processes below use the current release of `M.A`, the next release of `M.B` and future release `M.C` (where `B=A+1`, `C=B+1`) for examples.
Project Leads
{: .label .label-blue}
1. Beginning of the `burn down date` remind development team to stop accepting new issues for the `M.B` release (unless they are critical bugs/issues)
2. Work to merge existing pull requests targeting `M.B`
3. Move any pull requests or issues that are no longer a part of the `M.B` release to the `M.C` project board or backlog (for backlog remove the issue from the project board)
Operations
{: .label .label-purple}
1. Beginning of the `burn down date` announce the burn down of `branch-M.B`
2. Fork `branch-M.B` into `branch-M.C` for the new development branch
3. Create release `M.C` project board
4. Notify project leads process is complete
Also see the [Burn down guide]({% link resources/burn-down-guide.md %})
## Code freeze
Code freeze is the process when the release undergoes thorough testing. Pull requests are no longer accepted into the development branch. An exception may be made for [hotfix]({% link releases/hotfix.md %}) issues. All pull requests from Burn Down should be merged before Code Freeze begins or be moved to the next release.
### Timing
For the selection of a `code freeze date`, the general guidelines should be followed:
* Choose a `code freeze date` at least **3 business days** before the `release date`
* Communicate the decided `code freeze date` to the development team immediately to ensure they can meet the deadline
Code freeze begins at 12:00AM PT the day immediately after Burn Down ends.
For example, if Burn down runs from Wednesday Feb 3rd until Tuesday Feb 9th, then Burn down ends at 11:59PM PT on Feb 9th and Code Freeze begins 12:00AM PT Feb 10th.
### Process
**NOTE:** The processes below use the current release of `M.A`, the next release of `M.B` and future release `M.C` (where `B=A+1`, `C=B+1`) for examples.
Generally the process for Code Freeze occurs around 10:00AM PT on the first day of Code Freeze.
Project Leads
{: .label .label-blue}
1. Move any open pull requests targeting `branch-M.B` to target `branch-M.C` instead
2. Wait for confirmation from operations on the branch switch
3. Continue `M.C` development
4. Respond promptly to operations if any issues are found with the `M.B` release
Operations
{: .label .label-purple}
1. Beginning of the `code freeze date` announce the code freeze of `branch-M.B`
2. Switch GitHub default branch of project to `branch-M.C`
3. Create `M.B` release tracking project board
4. Notify project leads process is complete
## Releasing
### Timing
For the selection of a `release date`, the general guidelines should be followed:
* Choose a `release date` at least **3-4 weeks** from the previous `release date`
* Consult project leads to ensure key features will make the release with the anticipated date
* Communicate the decided `release date` to the development team immediately to ensure they can meet the deadline
### Process
**NOTE:** The processes below use the current release of `M.A`, the next release of `M.B` and future release `M.C` (where `B=A+1`, `C=B+1`) for examples.
Project Leads
{: .label .label-blue}
1. Beginning of the `release date` work with developers to close all outstanding issues and PRs
2. Assist operations team in testing and verifying documentation in release `M.B` PR
3. Review release `M.B` for approval
4. Help operations team in spot checking the deliverables post-release
Operations
{: .label .label-purple}
1. Beginning of the `release date` announce the release of `branch-M.B`
2. Create release PR from `branch-M.B` that targets `main`
3. Begin testing of conda, containers, and notebooks for correctness and functionality
4. Work with development team to close outstanding PRs
5. Review documentation to ensure version numbers and instructions are correct
6. Enlist project reviewers to approve the release PR
7. Merge release PR after approval
8. Monitor process of automated tools
9. Spot check deliverables to ensure correctness
| 0 |
rapidsai_public_repos/rapids.ai/content/docs/maintainers
|
rapidsai_public_repos/rapids.ai/content/docs/maintainers/releases/hotfix.md
|
---
layout: default
nav_order: 3
parent: Release Docs
grand_parent: Maintainer Docs
title: Hotfix Process
---
# Hotfix Process
## Overview
Summary of the RAPIDS release process for hotfixes.
### Intended audience
Developers
{: .label .label-green}
Project Leads
{: .label .label-blue}
Operations
{: .label .label-purple}
### See also
* [Hotfix versioning]({% link resources/versions.md %})
* [Major and minor releases]({% link releases/process.md %})
## Hotfixes
Hotfix (or patch) releases are not preplanned and are made to address critical issues with the current release. The criteria and process below are set as a guideline to help determine what is a hotfix.
### Criteria
A hotfix is a _significant_ bug that affects the _majority_ of users for which there is no _reasonable_ workaround.
So consider these questions:
- __Is this bug significant?__
- Does it produces incorrect results?
- Are there compile or runtime errors with valid input?
- Is there major incorrect functionality?
- __Does it affect the majority of users?__
- Does the bug affect a common or major function?
- Is the input that causes the bug a common or edge case?
- Will the average user encounter the bug during normal, average usage?
- __Is there a reasonable workaround?__
- Is there even a workaround?
- Can a potential workaround be communicated effectively to the community?
- Will the average user understand the workaround?
- How many steps/code changes does a workaround take?
- When the bug is fixed, does the workaround continue to work?
Also consider the timing of when the next release is scheduled. If the freeze or release date is within a few days, consider waiting and including the hotfix in the next release instead.
### Process
**NOTE:** The processes below use these releases as examples:
- Current release `M.A.X`
- Next minor release `M.B.0` (where `B=A+1`)
- Next patch release `M.A.Y` (where `Y=X+1`)
Developers
{: .label .label-green}
1. Hotfix issues will be assigned to you
2. Create your branch from the `branch-M.A` branch
3. Implement the fix succinctly
1. Change the minimal amount of code required
2. Update related documentation and unit tests
3. It is acceptable to implement a quick fix and open a new issue for a more in depth solution
4. Once complete, create a pull request targeting `branch-M.A`
5. Notify the project lead
Project Leads
{: .label .label-blue}
1. During [triage]({% link releases/triage.md %}), identify potential hotfixes
2. Ensure that the [hotfix criteria](#criteria) is met
3. Assign the issue and track its progress
4. Notify Operations that a hotfix is being worked on
5. Once notified that the pull request is created, review and approve it. Do NOT merge the pull request.
6. Notify Operations that the hotfix pull request is ready for merging
Operations
{: .label .label-purple}
1. Once notified by a Project Lead, review the pull request
2. Begin testing of conda and containers for correctness and functionality
3. Review documentation to ensure version numbers (updating to `M.A.Y`) and instructions are correct
4. Merge the developer's PR targeting `branch-M.A` after approval
5. Create a new PR from `branch-M.A` targeting `main`
6. Merge the PR targeting `main` after review and approval
7. Monitor process of automated tools
8. Spot check deliverables to ensure correctness
| 0 |
rapidsai_public_repos/rapids.ai/content/docs/maintainers
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rapidsai_public_repos/rapids.ai/content/docs/maintainers/releases/schedule.md
|
---
layout: default
nav_order: 3
parent: Release Docs
grand_parent: Maintainer Docs
title: Release Schedule
---
### Intended audience
{:.no_toc}
Community
{: .label .label-yellow}
Developers
{: .label .label-green}
Operations
{: .label .label-purple}
## Table of contents
{: .no_toc .text-delta }
1. TOC
{:toc}
## Current release
The current release schedule is posted on the [RAPIDS Maintainers Docs]({% link maintainers/maintainers.md %}) page.
## Completed Releases
Historical list of completed releases
{% for release in site.data.previous_releases %}
### Release v{{ release.version }} Schedule
{% if release.dev %}
Phase | Start | End | Duration
-- | -- | -- | --
Development | {{ release.dev.start | date: "%a, %b %e, %Y" }} | {{ release.dev.end | date: "%a, %b %e, %Y" }} | {{ release.dev.days }} days
Burn Down | {{ release.burndown.start | date: "%a, %b %e, %Y" }} | {{ release.burndown.end | date: "%a, %b %e, %Y" }} | {{ release.burndown.days }} days
Code Freeze/Testing | {{ release.codefreeze.start | date: "%a, %b %e, %Y" }} | {{ release.codefreeze.end | date: "%a, %b %e, %Y" }} | {{ release.codefreeze.days }} days
Release | {{ release.release.start | date: "%a, %b %e, %Y" }} | {{ release.release.end | date: "%a, %b %e, %Y" }} | {{ release.release.days }} days
{% else %}
{% if release.date %}
Phase | Date
-- | --
Release | {{ release.date | date: "%a, %b %e, %Y" }}
{% else %}
Phase | Start | End | Duration
-- | -- | -- | --
Development (cuDF/RMM{% if release.version >= '23.06' %}/rapids-cmake/cugraph-ops/raft{% endif %}) | {{ release.cudf_dev.start | date: "%a, %b %e, %Y" }} | {{ release.cudf_dev.end | date: "%a, %b %e, %Y" }} | {{ release.cudf_dev.days }} days
Development (others) | {{ release.other_dev.start | date: "%a, %b %e, %Y" }} | {{ release.other_dev.end | date: "%a, %b %e, %Y" }} | {{ release.other_dev.days }} days
[Burn Down]({% link releases/process.md %}#burn-down)(cuDF/RMM{% if release.version >= '23.06' %}/rapids-cmake/cugraph-ops/raft{% endif %}) | {{ release.cudf_burndown.start | date: "%a, %b %e, %Y" }} | {{ release.cudf_burndown.end | date: "%a, %b %e, %Y" }} | {{ release.cudf_burndown.days }} days
[Burn Down]({% link releases/process.md %}#burn-down) (others) | {{ release.other_burndown.start | date: "%a, %b %e, %Y" }} | {{ release.other_burndown.end | date: "%a, %b %e, %Y" }} | {{ release.other_burndown.days }} days
[Code Freeze/Testing]({% link releases/process.md %}#code-freeze) (cuDF/RMM/rapids-cmake/cugraph-ops/raft) | {{ release.cudf_codefreeze.start | date: "%a, %b %e, %Y" }} | {{ release.cudf_codefreeze.end | date: "%a, %b %e, %Y" }} | {{ release.cudf_codefreeze.days }} days
[Code Freeze/Testing]({% link releases/process.md %}#code-freeze) (others) | {{ release.other_codefreeze.start | date: "%a, %b %e, %Y" }} | {{ release.other_codefreeze.end | date: "%a, %b %e, %Y" }} | {{ release.other_codefreeze.days }} days
[Release]({% link releases/process.md %}#releasing) | {{ release.release.start | date: "%a, %b %e, %Y" }} | {{ release.release.end | date: "%a, %b %e, %Y" }} | {{ release.release.days }} days
{% endif %}
{% endif %}
{% endfor %}
| 0 |
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