# ix-feature-discovery

**Repository Path**: deep-spark/ix-feature-discovery

## Basic Information

- **Project Name**: ix-feature-discovery
- **Description**: IX Feature Discovery 能够自动为K8S集群节点上可用的天数智芯加速卡生成标签。
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 3
- **Forks**: 2
- **Created**: 2025-03-06
- **Last Updated**: 2025-07-22

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# IX Feature Discovery

IX Feature Discovery for Kubernetes is a software component that allows you to automatically generate labels for the set of IX GPUs available on a node.

## Prerequisites

The list of prerequisites for running the IX Featyre Discovery is described below:

- Kubernetes version >= 1.22
- All worker nodes must run the same operating system version.
- IX driver pre-installed.
- Make sure the IX GPUs have been installed if you want to see the labels for the set of IX GPUs.
- Node Feature Discovery (NFD) deployed on each node you want to label with the local source configured.

## Quick Start

### Build binary and image

1. Clone the repository and into the project directory

```bash
$ git clone https://gitee.com/deep-spark/ix-feature-discovery.git
$ cd ix-feature-discovery
```

2. Build the executable binary to the "build" directory

```bash
$ make binary
$ ls build/ix-feature-discovery 
build/ix-feature-discovery
```

3. Build the image

```bash
## build the image with default registry and version
$ make image
...
Successfully built d5db897cf230
Successfully tagged iluvatarcorex/ix-feature-discovery:v0.1.0
 
## build the image with customize registry and version 
$ REGISTRY=my-registry VERSION=v0.2.1 make image
...
Successfully built d5db897cf230
Successfully tagged my-registry/ix-feature-discovery:v0.2.1
```

***Note***: the image name is corresponding to the image in daemonset yaml, don't make it change at will.

### Node Feature Discovery (NFD)

The first step is to make sure that [Node Feature Discovery](https://github.com/kubernetes-sigs/node-feature-discovery) is running on every node you want to label. 

The following command will deploy NFD in your cluster by minimal steps. (see [Quick Start](https://kubernetes-sigs.github.io/node-feature-discovery/v0.14/get-started/quick-start.html))

```bash
$ sudo kubectl apply -k https://github.com/kubernetes-sigs/node-feature-discovery/deployment/overlays/default?ref=v0.14.2
```

**Note:** Please see the instructions below for [Deployment via `helm`](https://kubernetes-sigs.github.io/node-feature-discovery/v0.14/deployment/helm.html) when deploying in a production setting.

Check if node-feature-discovery is deployed successfully in kubernetes cluster.

```bash
$ sudo kubectl get pods -n node-feature-discovery
NAME                         READY   STATUS 
nfd-master-55b47d658-c64vf   1/1     Running
nfd-worker-thgdj             1/1     Running
```

### Deploy IX Feature Discovery

The next step is to run IX Feature Discovery on each node as a Daemonset.

```bash
$ sudo kubectl apply -f deployment/static/ix-feature-discovery.yaml
```

Check if ix-feature-discovery is deployed successfully in kubernetes cluster:

```bash
$ sudo kubectl get pods -n node-feature-discovery
NAME                         READY   STATUS 
ix-feature-discovery-stzt5   1/1     Running   
nfd-master-55b47d658-c64vf   1/1     Running
nfd-worker-thgdj             1/1     Running
```

### Verifying Everything Works

With both NFD and IX-Feature-Discovery deployed and running, you should now be able to see IX related labels appearing on any nodes that have IX GPUs installed on them.

```bash
$ kubectl get nodes -o yaml
apiVersion: v1
items:
- apiVersion: v1
  kind: Node
  metadata:
    ...

    labels:
      iluvatar.com/cuda.runtime-version.full=10.2
      iluvatar.com/cuda.runtime-version.major=10
      iluvatar.com/cuda.runtime-version.minor=2
      iluvatar.com/gpu.count=2
      iluvatar.com/gpu.machine=X580-G30
      iluvatar.com/gpu.memory=32768
      iluvatar.com/gpu.product=BI-V150S
      iluvatar.com/ix.driver-version.full=4.1.0
      iluvatar.com/ix.driver-version.major=4
      iluvatar.com/ix.driver-version.minor=1
      iluvatar.com/ix.driver-version.revision=0
      iluvatar.com/ix.timestamp=1731665058
      ...
...
```

## Generated Labels

Below is the list of the labels generated by IX Feature Discovery and their description.

| Label                                       | Description                                                         |
| ------------------------------------------- | ------------------------------------------------------------------- |
| iluvatar.com/ix.timestamp=1731548913        | Timestamp, the number of seconds elapsed since January 1, 1970 UTC. |
| iluvatar.com/ix.driver-version.full=4.2.0   | Full IX driver version                                              |
| iluvatar.com/ix.driver-version.major=4      | Major version of IX driver version                                  |
| iluvatar.com/ix.driver-version.minor=2      | Minor version of IX driver version                                  |
| iluvatar.com/ix.driver-version.revision=0   | Revision of IX driver version                                       |
| iluvatar.com/cuda.runtime-version.full=10.2 | Full CUDA runtime version                                           |
| iluvatar.com/cuda.runtime-version.major=10  | Major version of CUDA runtime version                               |
| iluvatar.com/cuda.runtime-version.minor=2   | Minor version of CUDA runtime version                               |
| iluvatar.com/gpu.present=true               | Node has GPU available                                              |
| iluvatar.com/gpu.machine=X580-G30           | Machine Type                                                        |
| iluvatar.com/gpu.product=BI-V150S           | GPU Model                                                           |
| iluvatar.com/gpu.count=2                    | GPU Count                                                           |
| iluvatar.com/gpu.memory=32768               | GPU Memory, Unit MB                                                 |

## License

Copyright (c) 2025 Iluvatar CoreX. All rights reserved. This project has an Apache-2.0 license, as
found in the [LICENSE](LICENSE) file.