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  • Find the ID of the specific GPU
  • GPU assignment using Docker Compose
  • GPU assignment using command line
  • Start multiple containers for each of the GPUs on the same computer
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  1. Node Hosting

Assign GPU to the Node

How to run multiple nodes on a single device with multiple GPUs

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Last updated 1 year ago

If you have multiple GPUs in a single computer, you can optimize performance by starting multiple nodes on the computer and assigning each GPU to a different node.

To enable GPU assignment, use the Docker version of Crynux Node. For a guide on the basics of starting a Crynux Node as a Docker container, please refer to the tutorial below:

Find the ID of the specific GPU

If you want to assign a specific GPU to a node, you must find the ID of the GPU first. This can be done using the nvidia-smi toolkit. Start a terminal and run the following command:

$ nvidia-smi

And you will get the output similar to the following:

Find the ID as highlighted in the image above. In this case, we have a single GPU installed in the computer, the ID of the GPU is 0.

GPU assignment using Docker Compose

In the docker-compose.yml file, find the following section:

deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              capabilities: [gpu]

And add another line below:

deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              capabilities: [gpu]
              device_ids: ["0"]

GPU assignment using command line

The GPU id could also be given to the container in the starting command. If you are starting the container using the following command before:

docker run -p 7412:7412 --name crynux_node --gpus all ghcr.io/crynux-ai/crynux-node:latest

You could change it to:

docker run -p 7412:7412 --name crynux_node --gpus '"device=0"' ghcr.io/crynux-ai/crynux-node:latest

The change is on the --gpus argument, from all, which provides all the GPUs to the container, to '"device=0"', which provides only the GPU with id 0.

Start multiple containers for each of the GPUs on the same computer

For each of the GPUs, follow the tutorial to clone the docker compose project:

For example, if you have 3 GPUs on the same computer, just clone the docker compose project 3 times, after renaming the folders, you have 3 working folders locally:

$ ls
crynux_node_docker_compose_1  crynux_node_docker_compose_2  crynux_node_docker_compose_3

In each of the working folders, find the docker-compose.yml file, and edit the content:

1. Change the name, service name and the container name, so that every container is using a different one:

from:

name: "crynux_node"
services:
  crynux_node:
    container_name: crynux_node

to:

name: "crynux_node_2"
services:
  crynux_node_2:
    container_name: crynux_node_2

2. Add a line to specify the GPU id as mentioned above:

deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              capabilities: [gpu]
              device_ids: ["0"]

3. Change the exposing port. So that every container is using a different port:

from:

ports:
  - "127.0.0.1:7412:7412"

to:

ports:
  - "127.0.0.1:7413:7412"

for the second container. And use 7414 for the third one.

The complete docker-compose.yml files for each of the 3 containers is shown below:

Node 1

crynux_node_docker_compose_1/docker-compose.yml

---
version: "3.8"
name: "crynux_node"

services:
  crynux_node:
    image: ghcr.io/crynux-ai/crynux-node:latest
    container_name: crynux_node
    restart: unless-stopped
    ports:
      - "127.0.0.1:7412:7412"
    volumes:
      - "./data:/app/data"
      - "./config:/app/config"
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              capabilities: [gpu]
              device_ids: ["0"]

Node 2

crynux_node_docker_compose_2/docker-compose.yml

---
version: "3.8"
name: "crynux_node_2"

services:
  crynux_node_2:
    image: ghcr.io/crynux-ai/crynux-node:latest
    container_name: crynux_node_2
    restart: unless-stopped
    ports:
      - "127.0.0.1:7413:7412"
    volumes:
      - "./data:/app/data"
      - "./config:/app/config"
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              capabilities: [gpu]
              device_ids: ["1"]

Node 3

crynux_node_docker_compose_3/docker-compose.yml

---
version: "3.8"
name: "crynux_node_3"

services:
  crynux_node_3:
    image: ghcr.io/crynux-ai/crynux-node:latest
    container_name: crynux_node_3
    restart: unless-stopped
    ports:
      - "127.0.0.1:7414:7412"
    volumes:
      - "./data:/app/data"
      - "./config:/app/config"
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              capabilities: [gpu]
              device_ids: ["2"]

Finally, in each of the folders, run the docker compose up command to start the container:

$ cd crynux_node_docker_compose_1
$ docker compose up -d
$ cd ../crynux_node_docker_compose_2
$ docker compose up -d
$ cd ../crynux_node_docker_compose_3
$ docker compose up -d
Start a Node - Docker
Start a Node - Docker