The Driver Toolkit is a container image in the OpenShift Container Platform payload used as a base image on which you can build driver containers. The Driver Toolkit image includes the kernel packages commonly required as dependencies to build or install kernel modules, as well as a few tools needed in driver containers. The version of these packages will match the kernel version running on the Red Hat Enterprise Linux CoreOS (RHCOS) nodes in the corresponding OpenShift Container Platform release.
Driver containers are container images used for building and deploying out-of-tree kernel modules and drivers on container operating systems like RHCOS. Kernel modules and drivers are software libraries running with a high level of privilege in the operating system kernel. They extend the kernel functionalities or provide the hardware-specific code required to control new devices. Examples include hardware devices like Field Programmable Gate Arrays (FPGA) or GPUs, and software-defined storage (SDS) solutions, such as Lustre parallel file systems, which require kernel modules on client machines. Driver containers are the first layer of the software stack used to enable these technologies on Kubernetes.
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The Driver Toolkit is also used by the Kernel Module Management (KMM), which is currently available as a community Operator on OperatorHub. KMM supports out-of-tree and third-party kernel drivers and the support software for the underlying operating system. Users can create modules for KMM to build and deploy a driver container, as well as support software like a device plugin, or metrics. Modules can include a build config to build a driver container-based on the Driver Toolkit, or KMM can deploy a prebuilt driver container.
The driver-toolkit image is available from the Container images section of the Red Hat Ecosystem Catalog and in the OpenShift Container Platform release payload. The image corresponding to the most recent minor release of OpenShift Container Platform will be tagged with the version number in the catalog. The image URL for a specific release can be found using the oc adm CLI command.
Instructions for pulling the driver-toolkit image from registry.redhat.io with podman or in OpenShift Container Platform can be found on the Red Hat Ecosystem Catalog.The driver-toolkit image for the latest minor release are tagged with the minor release version on registry.redhat.io, for example: registry.redhat.io/openshift4/driver-toolkit-rhel8:v4.12.
The Driver Toolkit includes the necessary dependencies, openssl, mokutil, and keyutils, needed to sign a kernel module. However, in this example, the simple-kmod kernel module is not signed and therefore cannot be loaded on systems with Secure Boot enabled.
The driver container must run with the privileged security context in order to load the kernel modules on the host. The following YAML file contains the RBAC rules and the DaemonSet for running the driver container. Save this YAML as 1000-drivercontainer.yaml.
Details - C:\Program Files\National Instruments\LabVIEW 2011\vi.lib\DAQmx\create\channels.lib\DAQmx Create Channel (CO -Pulse Generation-Frequency).vi (DAQmx Create Channel (CO -Pulse Generation-Frequency).vi) This VI needs a driver or toolkit component that is not found. Missing resource file "daqmx.rc".
It sounds like this is due to an issue during installation (it can sometimes crop up when things aren't installed in the correct order). I would recommend uninstalling LabVIEW 2011 and DAQmx, reinstalling LabVIEW from your distribution DVDs, and then installing DAQmx 9.4 (the latest version) last. I'm a bit worried that the repair isn't recognizing your factory DVDs as a distribution source... Do you have another computer to try them on to make sure nothing has happened to the discs?
Complete uninstallation and reinstallation of LabVIEW and drivers did result in loading the subject VI without any error messages. That process takes about two hours. I hope I don't have to do it again.
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Do: Ensure vehicles are maintained, repaired and inspected. Holman and Motor Fleet Service Department will email you when services are required. If you do not receive such emails, or if you have questions, contact Motor Fleet at 919-733-6540 or Service.MFM@doa.nc.gov.
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The toolkit only includes the correct Harvester OS image, build utilities, and kernel headers that allow NVIDIA drivers to be compiled and loaded from the container. You must download the NVIDIA KVM drivers using a valid NVIDIA subscription. For guidance on identifying the correct driver for your NVIDIA GPU, see the NVIDIA documentation.
The Harvester ISO does not include the nvidia-driver-toolkit container image. Because of its size, the image is pulled from Docker Hub by default. If you have an air-gapped environment, you can download and push the image to your private registry. The Image Repository and Image Tag fields on the nvidia-driver-toolkit screen provide information about the image that you must download.
This change affects the installation of NVIDIA GPU Operator.During installation, the Driver Toolkit daemon set checks for the existence of a build-dockercfg secret for the Driver Toolkit service account.When the secret does not exist, the installation stalls.
If the output from the preceding command is empty, {}, then your cluster is affected and you must configure your registry to use storage.Refer to Configuring the registry for bare metalfor information about configuring the registry with a PVC.For platforms other than bare metal, refer to the additional resources section of the Image Registry Operator in OpenShift Container Platform page.
After an upgrade a bug in OpenShift Cluster Version Operator (BZ#2014071) prevents the proper upgrade of the Driver Toolkit image stream.A fix for this issue has been merged in the following releases:
OpenShift 4.8.19, 4.8.21, 4.9.8 are known to have a broken Driver Toolkit image.The following messages are recorded in the driver pod containers.Follow the guidance in enabling a Cluster-wide entitlement.Afterward, the nvidia-driver-daemonset automatically uses an entitlement-based fallback.
To disable the use of Driver Toolkit image altogether, edit the cluster policy instance and set driver.use_ocp_driver_toolkit option to false.Also, we recommend maintaining entitlements for OpenShift versions < 4.9.9.
The NVIDIA CUDA Toolkit enables developers to build NVIDIA GPU accelerated compute applications for desktop computers, enterprise, and data centers to hyperscalers. It consists of the CUDA compiler toolchain including the CUDA runtime (cudart) and various CUDA libraries and tools. To build an application, a developer has to install only the CUDA Toolkit and necessary libraries required for linking.
In order to run a CUDA application, the system should have a CUDA enabled GPU and an NVIDIA display driver that is compatible with the CUDA Toolkit that was used to build the application itself. If the application relies on dynamic linking for libraries, then the system should have the right version of such libraries as well.
Every CUDA toolkit also ships with an NVIDIA display driver package for convenience. This driver supports all the features introduced in that version of the CUDA Toolkit. Please check the toolkit and driver version mapping in the release notes. The driver package includes both the user mode CUDA driver (libcuda.so) and kernel mode components necessary to run the application.
But this is not always required. CUDA Compatibility guarantees allow for upgrading only certain components and that will be the focus of the rest of this document. We will see how the upgrade to a new CUDA Toolkit can be simplified to not always require a full system upgrade.
From CUDA 11 onwards, applications compiled with a CUDA Toolkit release from within a CUDA major release family can run, with limited feature-set, on systems having at least the minimum required driver version as indicated below. This minimum required driver can be different from the driver packaged with the CUDA Toolkit but should belong to the same major release.
While applications built against any of the older CUDA Toolkits always continued to function on newer drivers due to binary backward compatibility, before CUDA 11, applications built against newer CUDA Toolkit releases were not supported on older drivers without forward compatibility package.
Minimum required driver version guidance can be found in the CUDA Toolkit Release Notes. Note that if the minimum required driver version is not installed in the system, applications will return an error as shown below.
Developers and system admins should note two important caveats when relying on minor version compatibility. If either of these caveats are limiting, then a new CUDA driver from the same minor version of the toolkit that the application was built with or later is required.
Sometimes features introduced in a CUDA Toolkit version may actually span both the toolkit and the driver. In such cases an application that relies on features introduced in a newer version of the toolkit and driver may return the following error on older drivers: cudaErrorCallRequiresNewerDriver. As mentioned earlier, admins should then upgrade the installed driver also.
Application developers can avoid running into this problem by having the application explicitly check for the availability of features. Refer to the CUDA Compatibility Developers Guide for more details. 152ee80cbc
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