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    <title>Ayaz Salikhov · Jupyter Blog</title>
    <link>https://jupyter.org/medium-archive/hugo/authors/ayaz-salikhov/</link>
    <description>The Project Jupyter blog: news, releases, and community stories, archived from blog.jupyter.org.</description>
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    <lastBuildDate>Tue, 16 Apr 2024 22:08:56 &#43;0000</lastBuildDate>
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      <title>CUDA enabled Jupyter Docker Images</title>
      <link>https://jupyter.org/medium-archive/hugo/posts/2024/cuda-enabled-jupyter-docker-images/</link>
      <pubDate>Tue, 16 Apr 2024 22:08:56 &#43;0000</pubDate>
      <dc:creator>Ayaz Salikhov</dc:creator>
      <guid>https://jupyter.org/medium-archive/hugo/posts/2024/cuda-enabled-jupyter-docker-images/</guid>
      <description>I am happy to announce that Jupyter Docker Stacks project now provides GPU accelerated Docker images. This allows PyTorch or TensorFlow…</description>
      <content:encoded>&lt;p&gt;I am happy to announce that &lt;a href=&#34;https://jupyter-docker-stacks.readthedocs.io/en/latest/index.html&#34;&gt;Jupyter Docker Stacks project&lt;/a&gt; now provides GPU accelerated Docker images. This allows PyTorch or TensorFlow operations to use compatible NVIDIA GPUs for accelerated computation.&lt;/p&gt;
&lt;h3 id=&#34;how-to-find-these-images&#34;&gt;How to find these images&lt;/h3&gt;
&lt;p&gt;All our images are available on &lt;a href=&#34;https://quay.io/organization/jupyter&#34;&gt;Quay.io registry&lt;/a&gt;. We provide CUDA accelerated versions of images are available for &lt;code&gt;tensorflow-notebook&lt;/code&gt; and &lt;code&gt;pytorch-notebook&lt;/code&gt;.&lt;/p&gt;
&lt;p&gt;To use such an image, you have to specify a special prefix tag to the image: versioned CUDA prefix like &lt;code&gt;cuda11-&lt;/code&gt; or &lt;code&gt;cuda12-&lt;/code&gt; for &lt;code&gt;pytorch-notebook&lt;/code&gt; or just &lt;code&gt;cuda-&lt;/code&gt; for &lt;code&gt;tensorflow-notebook&lt;/code&gt;.&lt;/p&gt;
&lt;blockquote&gt;
&lt;p&gt;We build &lt;code&gt;pytorch-notebook&lt;/code&gt; only for 2 last major versions of CUDA, &lt;code&gt;tensorflow-notebook&lt;/code&gt; image supports only the latest CUDA version listed in the &lt;a href=&#34;https://www.tensorflow.org/install/source#gpu&#34;&gt;officially tested build configurations&lt;/a&gt; list. CUDA-enabled images are available on x86_64 platform.&lt;/p&gt;
&lt;/blockquote&gt;
&lt;p&gt;For example, you can use an image &lt;code&gt;quay.io/jupyter/pytorch-notebook:cuda12-python-3.11.8&lt;/code&gt; or &lt;code&gt;quay.io/jupyter/tensorflow-notebook:cuda-latest&lt;/code&gt;.&lt;/p&gt;
&lt;h3 id=&#34;running-the-images&#34;&gt;Running the images&lt;/h3&gt;
&lt;p&gt;To enable CUDA support on &lt;strong&gt;Linux&lt;/strong&gt; host machine, you need to:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;have compatible Nvidia GPU&lt;/li&gt;
&lt;li&gt;have NVIDIA Linux driver installed&lt;/li&gt;
&lt;li&gt;add &lt;code&gt;--gpus all&lt;/code&gt; (or &lt;code&gt;--gpus &#39;&amp;quot;device=all&amp;quot;&#39;&lt;/code&gt;) flag to if you’re using &lt;code&gt;Docker&lt;/code&gt;&lt;/li&gt;
&lt;li&gt;add &lt;code&gt;--device &#39;nvidia.com/gpu=all&#39;&lt;/code&gt; flag if you’re using &lt;code&gt;Podman&lt;/code&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;For example, you can run the image like this: &lt;code&gt;docker run -it --rm -p 8888:8888 --gpus all quay.io/jupyter/tensorflow-notebook:cuda-latest&lt;/code&gt;.&lt;/p&gt;
&lt;p&gt;You can also enable GPU support on &lt;strong&gt;Windows&lt;/strong&gt; using &lt;a href=&#34;https://docs.docker.com/desktop/gpu/&#34;&gt;Docker&lt;/a&gt; or &lt;a href=&#34;https://github.com/containers/podman/issues/19005&#34;&gt;Podman&lt;/a&gt;.&lt;/p&gt;
&lt;h3 id=&#34;reaching-out&#34;&gt;Reaching out&lt;/h3&gt;
&lt;p&gt;You will find our documentation &lt;a href=&#34;http://jupyter-docker-stacks.readthedocs.io&#34;&gt;here&lt;/a&gt;.&lt;br&gt;
If you encounter any problems, please, take a look at &lt;a href=&#34;https://github.com/jupyter/docker-stacks&#34;&gt;GitHub issues&lt;/a&gt;.&lt;br&gt;
If you would like to improve GPU support in our images, please, reach out &lt;a href=&#34;https://github.com/jupyter/docker-stacks/issues/1557&#34;&gt;here&lt;/a&gt;.&lt;/p&gt;
&lt;h3 id=&#34;acknowledgments&#34;&gt;Acknowledgments&lt;/h3&gt;
&lt;p&gt;I would like to thank:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;&lt;a href=&#34;https://github.com/johanna-reiml-hpi&#34;&gt;Johanna Reiml&lt;/a&gt;, for implementing general &lt;code&gt;variant&lt;/code&gt; concept for our images and making it work for &lt;code&gt;pytorch-notebook&lt;/code&gt; (PR &lt;a href=&#34;https://github.com/jupyter/docker-stacks/pull/2091&#34;&gt;#2091&lt;/a&gt;)&lt;/li&gt;
&lt;li&gt;&lt;a href=&#34;https://github.com/ChristofKaufmann&#34;&gt;Christof Kaufmann&lt;/a&gt;, for making it work for &lt;code&gt;tensorflow-notebook&lt;/code&gt; (PR &lt;a href=&#34;https://github.com/jupyter/docker-stacks/pull/2100&#34;&gt;#2100&lt;/a&gt;)&lt;/li&gt;
&lt;li&gt;&lt;a href=&#34;https://github.com/benz0li&#34;&gt;Olivier Benz&lt;/a&gt;, for helping me out to write this blog post&lt;/li&gt;
&lt;/ul&gt;
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