Generic CDI Plugin

Written to use gpu pods with k3s on NixOS.

This PR implemented CDI for NVIDIA GPUs. This plugin can be installed in kubernetes to enable gpu pods.

Usage

Create a daemonset for the plugin

apiVersion: v1
kind: Namespace
metadata:
  name: generic-cdi-plugin
---
apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: generic-cdi-plugin-daemonset
  namespace: generic-cdi-plugin
spec:
  selector:
    matchLabels:
      name: generic-cdi-plugin
  template:
    metadata:
      labels:
        name: generic-cdi-plugin
        app.kubernetes.io/component: generic-cdi-plugin
        app.kubernetes.io/name: generic-cdi-plugin
    spec:
      containers:
      - image: ghcr.io/olfillasodikno/generic-cdi-plugin:main
        name: generic-cdi-plugin
        command: 
          - /generic-cdi-plugin
          - /var/run/cdi/nvidia-container-toolkit.json
        imagePullPolicy: Always
        securityContext:
          privileged: true
        tty: true
        volumeMounts:
        - name: kubelet
          mountPath: /var/lib/kubelet
        - name: nvidia-container-toolkit
          mountPath: /var/run/cdi/nvidia-container-toolkit.json
      volumes:
      - name: kubelet
        hostPath:
          path: /var/lib/kubelet
      - name: nvidia-container-toolkit
        hostPath:
          path: /var/run/cdi/nvidia-container-toolkit.json
      affinity:
        nodeAffinity:
          requiredDuringSchedulingIgnoredDuringExecution:
            nodeSelectorTerms:
            - matchExpressions:
              - key: "nixos-nvidia-cdi"
                operator: In
                values:
                - "enabled"

create NixOS configuration to enable cdi in containerd

services.k3s = {
  role = "server";
  clusterInit = true;

  extraFlags = (toString [
    "--container-runtime-endpoint unix:///run/containerd/containerd.sock"
  ]);

  label = {
    "nixos-nvidia-cdi" = "enabled";
  };
};
hardware.nvidia-container-toolkit.enable = true;
virtualisation.containerd = {
  enable = true;
  settings = {
      plugins."io.containerd.grpc.v1.cri" = {
        enable_cdi = true;
        cdi_spec_dirs = [ "/var/run/cdi" ];
      };
    };
};

Create gpu pod

apiVersion: v1
kind: Pod
metadata:
  name: hashcat-benchmark-pod
spec:
  containers:
  - name: hashcat-benchmark-container
    image: dizcza/docker-hashcat
    command: ["hashcat", "-d", "2" , "-b"]
    resources:
      requests:
        nvidia.com/gpu-all: "1"
      limits:
        nvidia.com/gpu-all: "1"

The container should output somethign similar to this:

hashcat (v6.2.6) starting in benchmark mode

Benchmarking uses hand-optimized kernel code by default.
You can use it in your cracking session by setting the -O option.
Note: Using optimized kernel code limits the maximum supported password length.
To disable the optimized kernel code in benchmark mode, use the -w option.

CUDA API (CUDA 12.4)
====================
* Device #1: NVIDIA GeForce RTX 3060, skipped

OpenCL API (OpenCL 3.0 CUDA 12.4.131) - Platform #1 [NVIDIA Corporation]
========================================================================
* Device #2: NVIDIA GeForce RTX 3060, 11904/12037 MB (3009 MB allocatable), 28MCU

Benchmark relevant options:
===========================
* --backend-devices=2
* --optimized-kernel-enable

-------------------
* Hash-Mode 0 (MD5)
-------------------

Speed.#2.........: 24545.3 MH/s (38.12ms) @ Accel:128 Loops:1024 Thr:256 Vec:8

NVIDIA smi on the host should now display the hashcat process

$ nvidia-smi
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 550.78                 Driver Version: 550.78         CUDA Version: 12.4     |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA GeForce RTX 3060        Off |   00000000:07:00.0 Off |                  N/A |
| 32%   42C    P2            132W /  170W |    2992MiB /  12288MiB |    100%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
                                                                                         
+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI        PID   Type   Process name                              GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|    0   N/A  N/A   1572566      C   hashcat                                      2986MiB |
+-----------------------------------------------------------------------------------------+