start
  • ๐Ÿ‘‹Welcome
  • ๐Ÿ“–Introduction
  • ๐Ÿ’กUse Cases
  • ๐Ÿง‘Personas
    • Film Production
    • Animation Studios
    • Game Developer
    • Industrial Design
    • Advertising
    • AI Image Generation / Text-to-Image
    • Speech-to-Text & Text-to-Speech
    • AI Video Enhancement & Processing
    • AI Object Detection & Image Analysis
    • Enterprise LLM API
    • Private Knowledge Base LLM (RAG - Retrieval-Augmented Generation)
    • Family Photographer
    • Indie Game Developer
    • Aspiring 3D Artist
    • Playstation Gamer
  • ๐Ÿš€Get Started
    • Janction Node Operation Graphic Tutorial
  • ๐Ÿ”—Related Work
  • ๐Ÿ—๏ธArchitecture
    • Actor Model
  • ๐Ÿ–ฅ๏ธPooling
  • ๐Ÿช™Token
  • โšกColocation of Idle Processor Computing Power
  • โœ…Proof of Contribution
  • ๐ŸŽฎGPU Marketplace
    • Pricing strategy based on pvcg
  • โ“HELP FAQ
    • FAQ
      • How Janction Efficiently Stores AI/ML Models for Different Users๏ผŸ
      • Compared to traditional cloud GPU platforms, how does Janction's distributed idle GPU computing powe
      • How does Janction ensure the efficiency and quality of data annotation for various data types with d
      • How does Janction's execution layer handle the various AI subdomain functionalities?
      • How does Janction select and use different DAs?
      • Is Janction considering adopting the security guarantees provided by Restaking?
      • What is the current progress of Janctionโ€™s product technology?
      • How will Janction consider airdropping to the community?
  • ๐Ÿ›ฃ๏ธRoadmap
  • ๐Ÿ“œPolicy
    • Terms
Powered by GitBook
On this page
  • Environmental Preparation
  • For GPU server instances
  • Node Operating Environment Preparation
  • Installation Environment
  • Run Janction node
  1. Get Started

Janction Node Operation Graphic Tutorial

PreviousGet StartedNextRelated Work

Last updated 2 months ago

is building a service network for the data and computing power sides of artificial intelligence, featuring a fair and efficient revenue distribution algorithm, a data verification layer specifically designed for AI, and an efficient distributed resource allocation system.

Environmental Preparation

You can use CPU or GPU servers to run the Janction Node. Using GPU server instances will earn higher points.GPU servers need to install Nvidia drivers, which makes the operation more complicated.The best practice for running a Janction node is to use the Linux operating system.

For GPU server instances

Create a CPU/GPU server instance and install the Nvidia driver. (If you are using a CPU, skip this step)

The above screenshot shows that the server has successfully installed the Nvidia driver.

You can use the nvidia-smi command to check whether the driver is installed successfully:

The above screenshot shows the current GPU usage. If you see this interface, the drive is normal.

Node Operating Environment Preparation

Installation Environment

Script installation

To run the Janction node, you need a docker environment.

First, you can use install.sh to install the required software (mainly docker):

The above screenshot shows the current system information, Docker version information, and Nvidia graphics driver version information.

Now you can run the node!

Custom Installation

If you don't have docker installed, the script will automatically install docker for you. Or you can usecurl https://get.docker.com/ | sh command to quickly install docker:

The above screenshot shows the docker installation process. Now you can type docker --version to view the docker version.The above screenshot shows that docker was successfully installed.

The above screenshot shows that docker was successfully installed.

Run Janction node

Macos x86 (eg. I7,I5,I3)

Macos Arm (eg. M1,M2,M3)

Download the start.sh script from the link below

https://janction-datas.s3.ap-northeast-1.amazonaws.com/mac-arm/start.sh

Linux Arm aarch64(eg. Graviton3)

Download the start.sh script from the link below

https://janction-datas.s3.ap-northeast-1.amazonaws.com/linux-arm64-v8/start.sh

Windows Arm (eg. M1,M2,M3)

bash ./start.sh

Enter the private key first according to the prompts, remember to add the 0x frontend.

If you do not have the Nvidia driver installed, you can only select the CPU task.

The above screenshot shows that the yolo_cpu task is selected to run. Please wait for a while.

After waiting for a while, you can see that the node has successfully started!

Open the Dashboard and you can see that the node has been successfully joined in Activity!

If you have any questions, please .

๐Ÿš€
contact us
Janction
Official website