NVIDIA GPU Driver and NVIDIA GPU Operator with SUSE #

Creating and deploying NVIDIA GPU-enabled containers with SUSE Linux Enterprise Base Container Images and Rancher Kubernetes Engine 2

Technical Reference Documentation

Author

Alex Arnoldy, Global Alliance Solutions Architect (SUSE)

SUSE Linux Enterprise Base Container Images

SUSE Linux Enterprise Server

Rancher Kubernetes Engine 2

Date: 2023-12-07

Summary

Build NVIDIA GPU Driver enabled container images with SUSE Linux Enterprise Base Container Images and deploy these containers with the NVIDIA GPU Operator to Rancher Kubernetes Engine 2 clusters.

Disclaimer

Documents published as part of the series SUSE Technical Reference Documentation have been contributed voluntarily by SUSE employees and third parties. They are meant to serve as examples of how particular actions can be performed. They have been compiled with utmost attention to detail. However, this does not guarantee complete accuracy. SUSE cannot verify that actions described in these documents do what is claimed or whether actions described have unintended consequences. SUSE LLC, its affiliates, the authors, and the translators may not be held liable for possible errors or the consequences thereof.

1 Introduction #

Graphics Processing Units (GPUs) provide unique capabilities for accelerating a broad spectrum of workloads, such as artificial intelligence and machine learning, scientific and engineering simulations, and many more. Developing and deploying these workloads in containers on Kubernetes clusters offers potential for improved portability, scale, and efficiency. However, GPU resources are not automatically visible or accessible to workloads running in containers.

In this guide, you learn how to:

create OCI-compliant container images that include the NVIDIA GPU Driver using SUSE Linux Enterprise Base Container Images
deploy the NVIDIA GPU Driver-enabled container image on Rancher Kubernetes Engine 2 with the NVIDIA GPU Operator

SUSE Linux Enterprise Base Container Images (SLE BCI) are a trusted choice for organizations with stringent security requirements, providing unparalleled security certifications (including Common Criteria, FIPS, and EAL) and enhanced supportability even when operating heterogeneous software stacks.

1.1 Scope #

This guide covers the following:

building an OCI-compliant container image on SUSE Linux Enterprise Base Container Images that includes the NVIDIA GPU Driver
validating the NVIDIA GPU Driver-enabled container image
publishing the image to a container image registry
deploying the container image with the NVIDIA GPU Operator Helm chart to a Rancher Kubernetes Engine 2 cluster
verifying the deployment

Important

This guide assumes that you are using Data Center class NVIDIA GPUs. Integrating consumer grade GPUs is outside the scope of this document.

1.2 Audience #

This guide is intended for high technology professionals (including Kubernetes administrators, proficient DevOps practitioners, and application developers) seeking to unlock the full potential of their GPU-accelerated containerized applications.

To be successful, you need a foundational understanding of Podman or Docker, Kubernetes, and NVIDIA GPU technologies.

1.3 Acknowledgements #

The author wants to acknowledge contributions to this guide by:

Rhys Oxenham, SUSE, Senior Director of Field PM & Engineering - Edge
Alex Zacharow, SUSE, Solution Engineer - SW Engineering(Systems)
Terry Smith, SUSE, Director of Global Partner Solutions

2 Prerequisites #

Before you embark on the procedures outlined in this guide, ensure that your environment is ready with the resources listed here.

Build host
Your build host is the computer system (physical or virtual) on which you build your OCI-compliant container.
Note
The build host does not require access to an NVIDIA GPU.
Your build host should have the following:
1. Operating system
  This guide is developed on a build host running SUSE Linux Enterprise Server 15 SP5.
  Although not required, it is recommended that your build host’s operating system match the version and service pack of the SUSE Linux Enterprise Base Container Images you will use for the foundation of your container images. You can find available images at the SUSE Container Images Registry.
  Important
  You have the choice of several base container images from SUSE. This guide uses the SLE BCI Go 1.18 development container image available at the time of writing. Be sure to note the version of the Go language in the base container image you choose. You need this during the build process.
2. SUSE Linux Enterprise Server modules
  Modules and extenions provide additional functionality to your SUSE Linux Enterprise Server system.
  Enable the Containers, Desktop Applications, and Development Tools modules:
```
VER=15
SP=5
sudo SUSEConnect -p sle-module-containers/${VER}.${SP}/x86_64
sudo SUSEConnect -p sle-module-desktop-applications/${VER}.${SP}/x86_64
sudo SUSEConnect -p sle-module-development-tools/${VER}.${SP}/x86_64
```
  Note
  Be sure to update the VER and SP variables with the SLES version and service pack that you are using.
3. Podman
  Podman (or Pod Manager Tool) is a daemonless container engine for managing Open Container Initiative (OCI) containers.
  Install Podman:
```
sudo zypper install podman
```
4. Git
  Git is a free and open source, distributed version control system that simplifies access to and management of source code.
  Install core Git tools:
```
sudo zypper install git-core
```
5. Kubectl
  The Kubernetes command line tool, kubectl, allows you to communicate with a Kubernetes cluster’s control plane to deploy applications, inspect and manage cluster resources, and more.
  Install and set up Kubectl on your build host.
  Learn more about How to Manage Kubernetes with Kubectl.
6. Helm
  Helm helps you manage Kubernetes applications. With Helm charts, you can define, install, and upgrade complex Kubernetes applications.
  Install and set up Helm on your build host.
  Note
  You do not need to install Kubectl or Helm if you plan to deploy the NVIDIA GPU Driver container to your Kubernetes cluster from a system other than your build host.
7. Access to SUSE Container Images
  Verify that your build host can access and download base container images from the SUSE Container Images Registry.
Kubernetes cluster
Your Kubernetes cluster must have worker nodes that are equipped and configured with Data Center class NVIDIA GPUs.
1. Containers and NVIDIA Compute modules
  Enable the Containers module and NVIDIA Compute module on each worker node.
```
VER=15
SP=5
sudo SUSEConnect -p sle-module-containers/${VER}.${SP}/x86_64
sudo SUSEConnect -p sle-module-NVIDIA-compute/${VER}/x86_64
```
  Note
  Be sure to update the VER and SP variables with the SLES version and service pack that you are using.
2. NVIDIA software
  Install required NVIDIA software packages on each node.
```
sudo zypper install \
  kernel-firmware-nvidia \
  libnvidia-container-tools \
  libnvidia-container1 \
  nvidia-container-runtime \
  sle-module-NVIDIA-compute-release
```
3. Podman
  Install Podman on at least one of the worker nodes.
```
sudo zypper install podman
```
4. Rancher Kubernetes Engine 2 (RKE2)
  RKE2 is the security focused Kubernetes distribution developed by SUSE.
  Ensure your worker nodes are part of an RKE2 cluster. You can deploy RKE2 on worker nodes manually or use Rancher by SUSE to spin up and configure the cluster.
Access to a container image registry from the build host and from the RKE2 cluster.
Using a container registry streamlines deployment of your GPU-enabled container across all Kubernetes worker nodes. This can be a public or a private registry, on-premises or hosted remotely. But you must be able to push your container images to the registry from your build host and retrieve them on your cluster.
Tip
The container registry does not need to support authentication, but it should be configured with a valid TLS certificate.

3 Setting up your environment #

Certain information is needed multiple times throughout the build process and even deployment process. This information can be stored in environment variables and recalled as needed, helping you to streamline commands, avoid errors, and maintain consistency.

Important

Run all commands on your build host.

Create the /tmp/build-variables.sh file.

cat <<EOF> /tmp/build-variables.sh
export REGISTRY=""
export SLE_VERSION=""
export SLE_SP=""
export DRIVER_VERSION=""
export OPERATOR_VERSION=""
export CUDA_VERSION=""
EOF

Edit the /tmp/build-variables.sh file to supply appropriate values for your project.
- REGISTRY: URL of the registry where the new container image is to be saved
- SLE_VERSION: SUSE Linux Enterprise Base Container Images version
- SLE_SP: SUSE Linux Enterprise Base Container Images service pack number
- DRIVER_VERSION: NVIDIA GPU Driver version
  Find the latest "Data Center Driver for Linux x64" version for your GPU at NVIDIA Driver Downloads.
- OPERATOR_VERSION: NVIDIA GPU Operator version
  Find the associated NVIDIA GPU Operator version.
- CUDA_VERSION: the NVIDIA CUDA version appropriate for the selected NVIDIA GPU Driver
  The CUDA version is listed under "Software Versions" when you find your driver version at NVIDIA Driver Downloads.
For example, your /tmp/build-variables.sh file should look something like:
```
export REGISTRY="registry.example.com"
export SLE_VERSION="15"
export SLE_SP="5"
export DRIVER_VERSION="535.104.05"
export OPERATOR_VERSION="v23.6.1"
export CUDA_VERSION="12.2.2"
```
Source your /tmp/build-variables.sh file to set the variables in your current session environment.
```
source /tmp/build-variables.sh
```

Important

These variables are lost when you disconnect from your terminal session. To recreate them, simply source the build-variables file again.

4 Building the container image #

On your build host, make sure you have sourced your /tmp/build-variables.sh file to set your environment variables.
You can verify your variables with:
```
echo "
REGISTRY=${REGISTRY}
SLE_VERSION=${SLE_VERSION}
SLE_SP=${SLE_SP}
DRIVER_VERSION=${DRIVER_VERSION}
CUDA_VERSION=${CUDA_VERSION}"
```
Clone the NVIDIA driver GitLab repository and change to the driver/sle15 directory.
```
git clone https://gitlab.com/nvidia/container-images/driver/ && cd driver/sle15
```
Locate the file, Dockerfile, and update it to reflect your build requirements.
1. Make a backup of Dockerfile before modifying the original.
```
cp Dockerfile /tmp/Dockerfile.orig
```
2. Update the golang build container image to version 1.18.
```
sed -i "/^FROM/ s/golang\:1\.../golang\:1.18/" Dockerfile
```
3. Update the base container image to the SLES 15 SP5 BCI:
```
sed -i '/^FROM/ s/suse\/sle15/bci\/bci-base/' Dockerfile
```
4. Verify that the changes have been made correctly to Dockerfile.
```
diff /tmp/Dockerfile.orig Dockerfile
```

Build the container image.

Important

When building the container image, you may be prompted for the registry that contains the nvidia/cuda image. If so, select the image located in docker.io.

Execute the podman build command, passing necessary arguments.

sudo podman build -t \
${REGISTRY}/nvidia-sle${SLE_VERSION}sp${SLE_SP}-${DRIVER_VERSION}:${DRIVER_VERSION} \
  --build-arg SLES_VERSION="${SLE_VERSION}.${SLE_SP}" \
  --build-arg DRIVER_ARCH="x86_64" \
  --build-arg DRIVER_VERSION="${DRIVER_VERSION}" \
  --build-arg CUDA_VERSION="${CUDA_VERSION}" \
  --build-arg PRIVATE_KEY=empty  \
.

Watch the build output for errors, warnings, and failures.
You can safely ignore errors and warnings that do not stop the build process.

Verify that the build process finishes successfully.

You should see a message like:

COMMIT registry.susealliances.com/nvidia-sle15sp5-535.104.05
--> cf976870489
Successfully tagged registry.susealliances.com/nvidia-sle15sp5-535.104.05:latest
cf9768704892c4b8b9e37a4ef591472e121b81949519204811dcc37d2be9d16c

Remove intermediate container images created during the build process.

for X in $(sudo podman images | awk '/none/ {print$3}'); do sudo podman rmi ${X}; done

Push the newly built image to the container registry.

Important

If the target container registry requires authentication, use the Podman’s login command to successfully authenticate before continuing.

Add a tag to the image that will be used when deploying the image to a Kubernetes cluster.

sudo podman tag ${REGISTRY}/nvidia-sle${SLE_VERSION}sp${SLE_SP}-${DRIVER_VERSION}:${DRIVER_VERSION} ${REGISTRY}/driver:${DRIVER_VERSION}-sles${SLE_VERSION}.${SLE_SP}

Push the image with both tags.

sudo podman push ${REGISTRY}/nvidia-sle${SLE_VERSION}sp${SLE_SP}-${DRIVER_VERSION}:${DRIVER_VERSION} &&
sudo podman push ${REGISTRY}/driver:${DRIVER_VERSION}-sles${SLE_VERSION}.${SLE_SP}

Verify the image is saved in the registry, and remotely available.

sudo podman search --list-tags ${REGISTRY}/driver:${DRIVER_VERSION}-sles${SLE_VERSION}.${SLE_SP}

(optional) Validate the container image with Podman
To validate the container outside the context of Kubernetes, use the worker node on which you installed Podman.
1. Open a terminal session to the worker node you will use for testing.
2. Create the /run/nvidia directory, if it does not yet exist.
```
sudo mkdir -p /run/nvidia
```
3. Copy your /tmp/build-variables.sh file to the node.
4. Source the /tmp/build-variables.sh file to set your environment variables.
```
source /tmp/build-variables.sh
```
5. Run the NVIDIA GPU Driver container locally.
```
sudo podman run -d \
  --name driver.${DRIVER_VERSION}-sles${SLE_VERSION}.${SLE_SP} \
  --privileged \
  --pid=host \
  -v /run/nvidia:/run/nvidia:shared \
  -v /var/log:/var/log \
  --restart=unless-stopped \
  ${REGISTRY}/driver:${DRIVER_VERSION}-sles${SLE_VERSION}.${SLE_SP}
```
6. Confirm that the container is running.
```
sudo podman ps -a
```
  Note
  The container’s STATUS should show "Up" and the amount of time it has been up should increment with repeated runs of the command.
7. Monitor the deployment of the NVIDIA GPU Driver by reviewing the standard output of the running container.
```
sudo podman logs -f driver.${DRIVER_VERSION}-sles${SLE_VERSION}.${SLE_SP}
```
8. Verify that the deployment process completes successfully.
  You should see the following message in the output:
```
Mounting {nvidia-org} driver rootfs...
Done, now waiting for signal
```
9. Close the log viewing session by pressing CTRL+C.
10. Check that the NVIDIA kernel modules have been loaded.
```
sudo lsmod | grep nvidia
```
  You should see the nvidia, nvidia_modeset, and nvidia_uvm kernel modules have been loaded.
11. Verify the nvidia-smi utility can communicate with the GPU.
```
sudo podman exec -it \
     driver.${DRIVER_VERSION}-sles${SLE_VERSION}.${SLE_SP} nvidia-smi
```
12. When ready to move forward, stop and remove the container.
```
sudo podman stop driver.${DRIVER_VERSION}-sles${SLE_VERSION}.${SLE_SP} &&
sudo podman rm driver.${DRIVER_VERSION}-sles${SLE_VERSION}.${SLE_SP}
```

5 Deploying to a Kubernetes cluster #

Kubernetes provides access to special hardware, such as GPUs, network adapters, and other devices through the device plugin framework. Configuring and managing these resources involves multiple software components, including drivers, libraries, and container runtimes. This can be difficult and prone to error. The NVIDIA GPU Operator helps overcome these difficulties using the Kubernetes operator framework to automate management of NVIDIA software components.

The preferred method for installing the NVIDIA GPU Operator is with the Helm Kubernetes package manager. Learn more about How to Manage Kubernetes with Kubectl.

In addition to Helm and Kubectl, you also need the kubeconfig file for your target Kubernetes cluster. If you are using Rancher by SUSE to manage your cluster, you can use the download the kubeconfig file of your cluster for use on your build host or other Linux system.

Note

If you are using a system other than your build host to deploy your container, be sure you have:

Kubectl and Helm
the kubeconfig file for your cluster
the /tmp/build-variables.sh file from Section 3, “Setting up your environment”

Caution

The kubeconfig file gives the rights (in many cases administrator level) to make changes to the Kubernetes cluster. Use extra care to keep it secure and remove it from any hosts/nodes after it is no longer needed.

Before starting your deployment, make sure that the NVIDIA kernel modules are not loaded on any of the Kubernetes worker nodes.
1. Log in to each node and list loaded NVIDIA kernel modules.
```
sudo lsmod | grep nvidia
```
  Tip
  If no NVIDIA modules are loaded, the output of the command should be empty.
2. Unload any modules containing 'nvidia'.
```
sudo modprobe -r <module-name>
```
  where <module-name> is the name of the kernel module displayed by the lsmod command.
  Note
  If any modules fail to unload, reboot the node.
Log in to your build host or the system you are using to manage deployment to your cluster.
Make sure your environment variables are set.

Add the NVIDIA helm software repository.

helm repo add https://helm.ngc.nvidia.com/nvidia
helm repo update

Verify that you are targeting the correct cluster.
```
echo
echo "Cluster name: $(kubectl config current-context)"
echo ""
kubectl get nodes -o wide
echo ""
```
If this is not the correct cluster, check that you have properly set up your kubeconfig file.

Deploy the NVIDIA GPU Operator with Helm.

helm install -n gpu-operator \
  --generate-name \
  --wait \
  --create-namespace \
  --version=${OPERATOR_VERSION} \
    nvidia/gpu-operator \
  --set driver.repository=${REGISTRY} \
  --set driver.version=${DRIVER_VERSION} \
  --set operator.defaultRuntime=containerd \
  --set toolkit.env[0].name=CONTAINERD_CONFIG \
  --set toolkit.env[0].value=/var/lib/rancher/rke2/agent/etc/containerd/config.toml \
  --set toolkit.env[1].name=CONTAINERD_SOCKET \
  --set toolkit.env[1].value=/run/k3s/containerd/containerd.sock \
  --set toolkit.env[2].name=CONTAINERD_RUNTIME_CLASS \
  --set toolkit.env[2].value=nvidia \
  --set toolkit.env[3].name=CONTAINERD_SET_AS_DEFAULT \
  --set-string toolkit.env[3].value=true

Verify the NVIDIA GPU Operator, NVIDIA GPU Driver, and associated elements have been deployed correctly.

kubectl get pods -n gpu-operator

You should see output similar to the following:

NAME                                                          READY   STATUS      RESTARTS   AGE

gpu-feature-discovery-crrsq                                   1/1     Running     0          60s

gpu-operator-7fb75556c7-x8spj                                 1/1     Running     0          5m13s

gpu-operator-node-feature-discovery-master-58d884d5cc-w7q7b   1/1     Running     0          5m13s

gpu-operator-node-feature-discovery-worker-6rht2              1/1     Running     0          5m13s

gpu-operator-node-feature-discovery-worker-9r8js              1/1     Running     0          5m13s

nvidia-container-toolkit-daemonset-lhgqf                      1/1     Running     0          4m53s

nvidia-cuda-validator-rhvbb                                   0/1     Completed   0          54s

nvidia-dcgm-5jqzg                                             1/1     Running     0          60s

nvidia-dcgm-exporter-h964h                                    1/1     Running     0          60s

nvidia-device-plugin-daemonset-d9ntc                          1/1     Running     0          60s

nvidia-device-plugin-validator-cm2fd                          0/1     Completed   0          48s

nvidia-driver-daemonset-5xj6g                                 1/1     Running     0          4m53s

nvidia-mig-manager-89z9b                                      1/1     Running     0          4m53s

nvidia-operator-validator-bwx99                               1/1     Running     0          58s

6 Validating the state of software #

The NVIDIA GPU Operator Helm chart provides two pods that validate the state of the installed software.

Validate the state of the NVIDIA GPU Operator software.
```
kubectl logs -n gpu-operator -l app=nvidia-operator-validator
```
The output should be similar to:
Defaulted container "nvidia-operator-validator" out of: nvidia-operator-validator, driver-validation (init), toolkit-validation (init), cuda-validation (init), plugin-validation (init)
all validations are successful
Validate the state of the NVIDIA CUDA Toolkit software.
```
kubectl logs -n gpu-operator -l app=nvidia-cuda-validator
```
The output should be similar to:
Defaulted container "nvidia-cuda-validator" out of: nvidia-cuda-validator, cuda-validation (init)
cuda workload validation is successful
Validate that the NVIDIA GPU Driver is communicating with the GPU.
```
kubectl exec -it \
"$(for EACH in \
$(kubectl get pods -n gpu-operator \
-l app=nvidia-driver-daemonset \
-o jsonpath={.items..metadata.name}); \
do echo ${EACH}; done)" \
-n gpu-operator \
nvidia-smi
```
Tip
This command can also be used to verify which application processes are running on the NVIDIA GPUs and how many resources are being consumed.
The output should be similar to the nvidia-smi output when validating the NVIDIA GPU Driver container image functionality through Podman.

7 Cleaning up #

After completing this procedure, remove the /tmp/build-variables.sh and the /tmp/Dockerfile.orig files from the build host and any Kubernetes worker nodes.

Also, when ready, remove the Kubernetes cluster kubeconfig file from the build host and/or any other nodes to which it may have been copied.

8 Summary #

Graphics Processing Units (GPUs) have become an essential technology of the modern era, accelerating time to insight and expanding capabilities. GPUs have had dramatic impacts in artificial intelligence, machine learning, scientific and engineering simulation, and other high-performance computing applications. Equally dramatic have been the impacts of container technologies, reshaping how applications are developed, deployed, and managed. Bringing these two technologies together offers many benefits, including faster development, improved application portability, easier scaling, and streamlined administration.

In this guide, you learned how to:

build OCI-compliant container images with the NVIDIA GPU Driver on SUSE Linux Enterprise Base Container Images
deploy your NVIDIA GPU Driver-enabled container image with NVIDIA GPU Operator on Rancher Kubernetes Engine 2 clusters

The strategic choice of SUSE Linux Enterprise Base Container Images as the foundation for this integration underscores a commitment to security and supportability. Organizations with exacting security requirements depend on the numerous certifications of SUSE Linux Enterprise Server, including Common Criteria, FIPS, and EAL. This is enhanced with the choice of a security focused Kubernetes distribution, such as Rancher Kubernetes Engine 2. With SUSE’s commitment to providing robust support for heterogeneous software stacks, customers can design their IT landscapes to suit their unique challenges without compromising on security, capability, or performance.

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If you publish printed copies (or copies in media that commonly have printed covers) of the Document, numbering more than 100, and the Document’s license notice requires Cover Texts, you must enclose the copies in covers that carry, clearly and legibly, all these Cover Texts: Front-Cover Texts on the front cover, and Back-Cover Texts on the back cover. Both covers must also clearly and legibly identify you as the publisher of these copies. The front cover must present the full title with all words of the title equally prominent and visible. You may add other material on the covers in addition. Copying with changes limited to the covers, as long as they preserve the title of the Document and satisfy these conditions, can be treated as verbatim copying in other respects.

If the required texts for either cover are too voluminous to fit legibly, you should put the first ones listed (as many as fit reasonably) on the actual cover, and continue the rest onto adjacent pages.

If you publish or distribute Opaque copies of the Document numbering more than 100, you must either include a machine-readable Transparent copy along with each Opaque copy, or state in or with each Opaque copy a computer-network location from which the general network-using public has access to download using public-standard network protocols a complete Transparent copy of the Document, free of added material. If you use the latter option, you must take reasonably prudent steps, when you begin distribution of Opaque copies in quantity, to ensure that this Transparent copy will remain thus accessible at the stated location until at least one year after the last time you distribute an Opaque copy (directly or through your agents or retailers) of that edition to the public.

It is requested, but not required, that you contact the authors of the Document well before redistributing any large number of copies, to give them a chance to provide you with an updated version of the Document.

4. MODIFICATIONS#

You may copy and distribute a Modified Version of the Document under the conditions of sections 2 and 3 above, provided that you release the Modified Version under precisely this License, with the Modified Version filling the role of the Document, thus licensing distribution and modification of the Modified Version to whoever possesses a copy of it. In addition, you must do these things in the Modified Version:

Use in the Title Page (and on the covers, if any) a title distinct from that of the Document, and from those of previous versions (which should, if there were any, be listed in the History section of the Document). You may use the same title as a previous version if the original publisher of that version gives permission.
List on the Title Page, as authors, one or more persons or entities responsible for authorship of the modifications in the Modified Version, together with at least five of the principal authors of the Document (all of its principal authors, if it has fewer than five), unless they release you from this requirement.
State on the Title page the name of the publisher of the Modified Version, as the publisher.
Preserve all the copyright notices of the Document.
Add an appropriate copyright notice for your modifications adjacent to the other copyright notices.
Include, immediately after the copyright notices, a license notice giving the public permission to use the Modified Version under the terms of this License, in the form shown in the Addendum below.
Preserve in that license notice the full lists of Invariant Sections and required Cover Texts given in the Document’s license notice.
Include an unaltered copy of this License.
Preserve the section Entitled "History", Preserve its Title, and add to it an item stating at least the title, year, new authors, and publisher of the Modified Version as given on the Title Page. If there is no section Entitled "History" in the Document, create one stating the title, year, authors, and publisher of the Document as given on its Title Page, then add an item describing the Modified Version as stated in the previous sentence.
Preserve the network location, if any, given in the Document for public access to a Transparent copy of the Document, and likewise the network locations given in the Document for previous versions it was based on. These may be placed in the "History" section. You may omit a network location for a work that was published at least four years before the Document itself, or if the original publisher of the version it refers to gives permission.
For any section Entitled "Acknowledgements" or "Dedications", Preserve the Title of the section, and preserve in the section all the substance and tone of each of the contributor acknowledgements and/or dedications given therein.
Preserve all the Invariant Sections of the Document, unaltered in their text and in their titles. Section numbers or the equivalent are not considered part of the section titles.
Delete any section Entitled "Endorsements". Such a section may not be included in the Modified Version.
Do not retitle any existing section to be Entitled "Endorsements" or to conflict in title with any Invariant Section.
Preserve any Warranty Disclaimers.

If the Modified Version includes new front-matter sections or appendices that qualify as Secondary Sections and contain no material copied from the Document, you may at your option designate some or all of these sections as invariant. To do this, add their titles to the list of Invariant Sections in the Modified Version’s license notice. These titles must be distinct from any other section titles.

You may add a section Entitled "Endorsements", provided it contains nothing but endorsements of your Modified Version by various parties—for example, statements of peer review or that the text has been approved by an organization as the authoritative definition of a standard.

You may add a passage of up to five words as a Front-Cover Text, and a passage of up to 25 words as a Back-Cover Text, to the end of the list of Cover Texts in the Modified Version. Only one passage of Front-Cover Text and one of Back-Cover Text may be added by (or through arrangements made by) any one entity. If the Document already includes a cover text for the same cover, previously added by you or by arrangement made by the same entity you are acting on behalf of, you may not add another; but you may replace the old one, on explicit permission from the previous publisher that added the old one.

The author(s) and publisher(s) of the Document do not by this License give permission to use their names for publicity for or to assert or imply endorsement of any Modified Version.

5. COMBINING DOCUMENTS#

You may combine the Document with other documents released under this License, under the terms defined in section 4 above for modified versions, provided that you include in the combination all of the Invariant Sections of all of the original documents, unmodified, and list them all as Invariant Sections of your combined work in its license notice, and that you preserve all their Warranty Disclaimers.

The combined work need only contain one copy of this License, and multiple identical Invariant Sections may be replaced with a single copy. If there are multiple Invariant Sections with the same name but different contents, make the title of each such section unique by adding at the end of it, in parentheses, the name of the original author or publisher of that section if known, or else a unique number. Make the same adjustment to the section titles in the list of Invariant Sections in the license notice of the combined work.

In the combination, you must combine any sections Entitled "History" in the various original documents, forming one section Entitled "History"; likewise combine any sections Entitled "Acknowledgements", and any sections Entitled "Dedications". You must delete all sections Entitled "Endorsements".

6. COLLECTIONS OF DOCUMENTS#

You may make a collection consisting of the Document and other documents released under this License, and replace the individual copies of this License in the various documents with a single copy that is included in the collection, provided that you follow the rules of this License for verbatim copying of each of the documents in all other respects.

You may extract a single document from such a collection, and distribute it individually under this License, provided you insert a copy of this License into the extracted document, and follow this License in all other respects regarding verbatim copying of that document.

7. AGGREGATION WITH INDEPENDENT WORKS#

A compilation of the Document or its derivatives with other separate and independent documents or works, in or on a volume of a storage or distribution medium, is called an "aggregate" if the copyright resulting from the compilation is not used to limit the legal rights of the compilation’s users beyond what the individual works permit. When the Document is included in an aggregate, this License does not apply to the other works in the aggregate which are not themselves derivative works of the Document.

If the Cover Text requirement of section 3 is applicable to these copies of the Document, then if the Document is less than one half of the entire aggregate, the Document’s Cover Texts may be placed on covers that bracket the Document within the aggregate, or the electronic equivalent of covers if the Document is in electronic form. Otherwise they must appear on printed covers that bracket the whole aggregate.

8. TRANSLATION#

Translation is considered a kind of modification, so you may distribute translations of the Document under the terms of section 4. Replacing Invariant Sections with translations requires special permission from their copyright holders, but you may include translations of some or all Invariant Sections in addition to the original versions of these Invariant Sections. You may include a translation of this License, and all the license notices in the Document, and any Warranty Disclaimers, provided that you also include the original English version of this License and the original versions of those notices and disclaimers. In case of a disagreement between the translation and the original version of this License or a notice or disclaimer, the original version will prevail.

If a section in the Document is Entitled "Acknowledgements", "Dedications", or "History", the requirement (section 4) to Preserve its Title (section 1) will typically require changing the actual title.

9. TERMINATION#

You may not copy, modify, sublicense, or distribute the Document except as expressly provided for under this License. Any other attempt to copy, modify, sublicense or distribute the Document is void, and will automatically terminate your rights under this License. However, parties who have received copies, or rights, from you under this License will not have their licenses terminated so long as such parties remain in full compliance.

10. FUTURE REVISIONS OF THIS LICENSE#

The Free Software Foundation may publish new, revised versions of the GNU Free Documentation License from time to time. Such new versions will be similar in spirit to the present version, but may differ in detail to address new problems or concerns. See http://www.gnu.org/copyleft/.

Each version of the License is given a distinguishing version number. If the Document specifies that a particular numbered version of this License "or any later version" applies to it, you have the option of following the terms and conditions either of that specified version or of any later version that has been published (not as a draft) by the Free Software Foundation. If the Document does not specify a version number of this License, you may choose any version ever published (not as a draft) by the Free Software Foundation.

ADDENDUM: How to use this License for your documents#

Copyright (c) YEAR YOUR NAME.
   Permission is granted to copy, distribute and/or modify this document
   under the terms of the GNU Free Documentation License, Version 1.2
   or any later version published by the Free Software Foundation;
   with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts.
   A copy of the license is included in the section entitled “GNU
   Free Documentation License”.

If you have Invariant Sections, Front-Cover Texts and Back-Cover Texts, replace the “ with…Texts.” line with this:

with the Invariant Sections being LIST THEIR TITLES, with the
   Front-Cover Texts being LIST, and with the Back-Cover Texts being LIST.

If you have Invariant Sections without Cover Texts, or some other combination of the three, merge those two alternatives to suit the situation.

If your document contains nontrivial examples of program code, we recommend releasing these examples in parallel under your choice of free software license, such as the GNU General Public License, to permit their use in free software.