This provides support for 32-bit ARM cpuid capabilities based on
the HWCAP flags, and enables the build of NFD on the 32-bit ARM
userland - notably, this also applies to ARM64 systems that are
running userspace in Aarch32 mode, which is where this problem
was first encountered.
Signed-off-by: Paul Mundt <paul.mundt@adaptant.io>
This builds on the PCI support to enable the discovery of USB devices.
This is primarily intended to be used for the discovery of Edge-based
heterogeneous accelerators that are connected via USB, such as the Coral
USB Accelerator and the Intel NCS2 - our main motivation for adding this
capability to NFD, and as part of our work in the SODALITE H2020
project.
USB devices may define their base class at either the device or
interface levels. In the case where no device class is set, the
per-device interfaces are enumerated instead. USB devices may
furthermore have multiple interfaces, which may or may not use the
identical class across each interface. We therefore report device
existence for each unique class definition to enable more fine-grained
labelling and node selection.
The default labelling format includes the class, vendor and device
(product) IDs, as follows:
feature.node.kubernetes.io/usb-fe_1a6e_089a.present=true
As with PCI, a subset of device classes are whitelisted for matching.
By default, there are only a subset of device classes under which
accelerators tend to be mapped, which is used as the basis for
the whitelist. These are:
- Video
- Miscellaneous
- Application Specific
- Vendor Specific
For those interested in matching other classes, this may be extended
by using the UsbId rule provided through the custom source. A full
list of class codes is provided by the USB-IF at:
https://www.usb.org/defined-class-codes
For the moment, owing to a lack of a demonstrable use case, neither
the subclass nor the protocol information are exposed. If this
becomes necessary, support for these attributes can be trivially
added.
Signed-off-by: Paul Mundt <paul.mundt@adaptant.io>
This adds support for making selected labels extended resources.
Labels which have integer values, can be promoted to Kubernetes extended
resources by listing them to the added command line flag
`--resource-labels`. These labels won't then show in the node label
section, they will appear only as extended resources.
Signed-off-by: Ukri Niemimuukko <ukri.niemimuukko@intel.com>
SR-IOV is a PCI attribute and also non-NIC PCI devices can have it. Therefore,
it is useful to label all PCI devices with that capability.
After this commit the following labels for Intel NICs are overlapping:
feature.node.kubernetes.io/pci-0200_8086.sriov.capable=true
feature.node.kubernetes.io/network-sriov.capable=true
Signed-off-by: Mikko Ylinen <mikko.ylinen@intel.com>
Some workloads may benefit from Intel Turbo Boost technology being
disabled. This patch sets the
'feature.node.kubernetes.io/cpu-pstate.turbo' label to 'false' if we can
detect that it has been disabled. If detection fails no label is
published.
For running end-to-end tests it is required to explicitly specify in the
command line the kubeconfig to be used, e.g.:
$ make e2e-test KUBECONFIG=$HOME/.kube/config
Extend NVDIMM (non-volatile DIMM) discovery by adding detection of DAX
mode, i.e. detection of regions in DAX/AppDirect mode.
The new label is:
feature.node.kubernetes.io/memory-nv.dax: true
- Create default yamls for deploying master and worker.
- Use kube-system namespace by default.
- Configurable namespace:
make IMAGE_REGISTRY=myhost:5000 K8S_NAMESPACE=my-nfd-devel
Also, slightly adjust the deployment instructions in README to point out
that the templates should now be usable as is to run the latest released
version of NFD.
Add 'cpuid/attributeBlacklist' and 'cpuid/attributeWhitelist' config
options for the cpu feature source. These can be used to filter the set
of cpuid capabilities that get published. The intention is to reduce
clutter in the NFD label space, getting rid of "obvious" or misleading
cpuid labels. Whitelisting has higher priority, i.e. only whitelist
takes effect if both attributeWhitelist and attributeBlacklist are
specified.
Point to the latest release in the README, and, point out that a
user-built custom image is required to run the latest development
version. Update the deployment instructions to reflect the need to
specify the container image when using the deployment spec template(s).
Also, update the Job deployment script to set a user-defined container
image.
Remove 'cpuid', 'pstate' and 'rdt' feature sources and move their
functionality under the 'cpu' source. The goal is to have a more
systematic organization of feature sources and labels. After this change
we now basically have one source per type of hw, one for kernel and one
for userspace sw.
Related feature labels are changed, correspondingly, new labels being:
feature.node.k8s.io/cpu-cpuid.<cpuid flag>
feature.node.k8s.io/cpu-pstate.turbo
feature.node.k8s.io/cpu-rdt.<rdt feature>
Change the structure and naming of the make variables that control the
container image name/tag that gets created. Default values and behavior
stay the same, but, this change tries to make it easier to customize the
build from command line.
Also, document all the relevant make variables in readme.
Move the documentation of the feature detection hooks (i.e. 'local'
feature source) after all other feature sources. It is a more logical
place to document custom user-specific functionality after the built-in
features. Also, adjust the title a bit.
Detect of the Intel SST-BF (Speed Select Technology - Base Frequency)
has been enabled.
Adds one new feature label:
feature.node.kubernetes.io/cpu-power.sst_bf.enabled=true
Based on a patch from kuralamudhan.ramakrishnan@intel.com
The aim here is to add another way to specify labels using the local
source by reading files in a specific directory. That avoids us to
execute a hook when we just need to get the content of a file.
See https://github.com/kubernetes-sigs/node-feature-discovery/issues/226
Signed-off-by: Jordan Jacobelli <jjacobelli@nvidia.com>
