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Tbazant-testing-ai-sonnet35 #412

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09c2aad
updated by sonnet
tbazant Jan 15, 2025
9174247
update by AI Sonnet
tbazant Jan 15, 2025
25ac69e
testing commit
tbazant Jan 15, 2025
b9bcdfd
testx
tbazant Jan 16, 2025
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84 changes: 28 additions & 56 deletions concepts/NVIDIA-Operator.xml
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Original file line number Diff line number Diff line change
@@ -1,7 +1,4 @@
<?xml version="1.0" encoding="UTF-8"?>
<!-- This file originates from the project https://github.com/openSUSE/doc-kit
-->
<!-- This file can be edited downstream. -->
<!DOCTYPE topic [ <!ENTITY % entities SYSTEM "../common/generic-entities.ent">
%entities; ]>
<topic xml:id="nvidia-operator" role="concept" xml:lang="en"
Expand All @@ -11,117 +8,92 @@ xmlns:xi="http://www.w3.org/2001/XInclude"
xmlns:xlink="http://www.w3.org/1999/xlink"
xmlns:trans="http://docbook.org/ns/transclusion">
<info>
<title>Introduction to the &nvoperator;</title>
<title>About the &nvoperator;</title>
<meta name="maintainer" content="[email protected]" its:translate="no"/>
<abstract>
<para>
This article explains the &nvoperator;, outlines the &nvidia; GPU
components it manages, and summarizes the benefits of using it.
This article explains the &nvoperator; and its components.
</para>
</abstract>
</info>
<section xml:id="what-is-nvidia-operator">
<title>What is the &nvoperator;?</title>
<title>Overview</title>
<para>
The &nvoperator; is a &kube; operator that simplifies the management and
deployment of &nvidia; GPU resources in a &kube; cluster. It automates the
configuration and monitoring of &nvidia; GPU drivers, as well as
associated components like CUDA, container runtimes, and other GPU-related
software.
The &nvoperator; manages &nvidia; GPU resources in a &kube; cluster. It
automates GPU driver setup and monitoring.
</para>
</section>
<section xml:id="how-does-nvidia-operator-work">
<title>How does the &nvoperator; work?</title>
<title>Operation workflow</title>
<para>
The &nvoperator; follows this workflow:
The &nvoperator; operates in these steps:
</para>
<orderedlist>
<listitem>
<para>
<emphasis role="bold">Operator deployment.</emphasis> The &nvidia;
Operator is deployed as a &helm; chart or using &kube; manifests.
<emphasis role="bold">Deployment.</emphasis> Install the operator
through &helm; chart or &kube; manifests.
</para>
</listitem>
<listitem>
<para>
<emphasis role="bold">Node labeling &amp; GPU discovery.</emphasis>
Once installed, the operator deploys the <emphasis>GPU Feature
Discovery</emphasis> (GFD) daemon, which scans the hardware on each
node for &nvidia; GPUs. It labels nodes with GPU-specific information,
making it easier for &kube; to schedule GPU workloads based on
available hardware.
<emphasis role="bold">Discovery.</emphasis> The GPU Feature Discovery
(GFD) daemon finds &nvidia; GPUs and labels nodes.
</para>
</listitem>
<!--
<listitem>
<para>
<emphasis role="bold">&nvidia; driver installation.</emphasis> The
operator ensures that the appropriate &nvidia; drivers are installed
on the cluster nodes.
</para>
</listitem> -->
<listitem>
<para>
<emphasis role="bold">NVIDIA Container Toolkit
configuration.</emphasis> The GPU operator installs and configures the
&nvidia; Container Toolkit, which allows GPU-accelerated containers to
run in &kube;.
<emphasis role="bold">Runtime setup.</emphasis> The operator installs
the &nvidia; Container Toolkit for GPU workloads.
</para>
</listitem>
<listitem>
<para>
<emphasis role="bold">CUDA runtime and libraries.</emphasis> The
operator ensures that the CUDA toolkit is properly installed, making
it easier for applications requiring CUDA to work seamlessly without
manual intervention.
<emphasis role="bold">CUDA setup.</emphasis> The operator installs
CUDA (Compute Unified Device Architecture) toolkit components.
</para>
</listitem>
<listitem>
<para>
<emphasis role="bold">Validation and health monitoring.</emphasis>
After setting up the environment, the operator continuously monitors
the health of the GPU resources. It also exposes health metrics for
administrators to view and use for decision-making.
<emphasis role="bold">Monitoring.</emphasis> The operator tracks GPU
health and provides metrics.
</para>
</listitem>
<listitem>
<para>
<emphasis role="bold">Scheduling GPU workloads.</emphasis> Once the
environment is configured, you can install workloads that require GPU
acceleration. &kube; will use the node labels and available GPU
resources to schedule these jobs on GPU-enabled nodes automatically.
<emphasis role="bold">Workload management.</emphasis> &kube; schedules
GPU tasks on enabled nodes.
</para>
</listitem>
</orderedlist>
</section>
<section xml:id="nvidia-operator-benefits">
<title>Benefits of using the &nvoperator;</title>
<title>Benefits</title>
<para>
Using the &nvoperator; has the following key benefits:
The &nvoperator; provides these advantages:
</para>
<itemizedlist>
<listitem>
<para>
<emphasis role="bold">Automated setup.</emphasis> No manual runtime
configuration is needed.
<emphasis role="bold">Automation.</emphasis> Setup requires no manual
configuration.
</para>
</listitem>
<listitem>
<para>
<emphasis role="bold">Cluster-wide management.</emphasis> Works across
the entire &kube; cluster, scaling with node additions or removals.
<emphasis role="bold">Cluster management.</emphasis> Works across all
nodes in &kube;.
</para>
</listitem>
<listitem>
<para>
<emphasis role="bold">Simplified updates.</emphasis> Automates
updates for GPU-related components.
<emphasis role="bold">Updates.</emphasis> Automates component updates.
</para>
</listitem>
<listitem>
<para>
<emphasis role="bold">Optimized GPU usage.</emphasis> Ensures that GPU
resources are efficiently allocated and used.
<emphasis role="bold">Resource optimization.</emphasis> Manages GPU
resources efficiently.
</para>
</listitem>
</itemizedlist>
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35 changes: 2 additions & 33 deletions concepts/openwebui-introduction.xml
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Original file line number Diff line number Diff line change
Expand Up @@ -168,40 +168,9 @@ xmlns:trans="http://docbook.org/ns/transclusion">
<term>Main chat window</term>
<listitem>
<para>
Displays your recent queries and corresponding answers provided by
the AI. By using the prompt field at the bottom, you can accomplish
the following tasks related to the current chat:
The main window shows AI responses to your queries. Enter new
questions in the prompt field at the bottom.
</para>
<itemizedlist>
<listitem>
<para>
Enter the query that you want the AI to answer
</para>
</listitem>
<listitem>
<para>
Upload custom documents that you want the AI to process and use
as a source of information when answering
</para>
</listitem>
<listitem>
<para>
Select a document, collection of documents, or URL to extend the
AI model's knowledge base
</para>
</listitem>
<listitem>
<para>
Select a preconfigured AI model for the current chat
</para>
</listitem>
<listitem>
<para>
Interrupt the chatbot from answering if you are already
satisfied with the provided information
</para>
</listitem>
</itemizedlist>
</listitem>
</varlistentry>
</variablelist>
Expand Down
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