Inferix Decentralized GPU
  • Overview
  • Tokenomics
  • Introduction
    • Rendering network using crowdsourced GPU
    • Rendering verification problem
  • Decentralized visual computing
    • Client Apps plugin
    • Client API and SDK
    • Manager node
    • Worker node
    • Decentralized storage
      • Data categories
      • Multi-level 3D polygon data
      • Polygon digester
      • Decentralized storage
      • Decentralized cache
    • Data security with FHE and TEE
      • Verifier data security enhancement with FHE
      • Worker and Manager data security enhancement with FHE
    • Decentralized federated AI
      • Federated learning with TensorOpera
      • Meta LLaMA
      • Stable Diffusion
      • Other AI models
      • Inferix AI
  • Inferix Testnet 1
    • Inferix GPU Solutions
    • Adding GPUs to the Network
    • Renting GPU Devices
    • GPU Staking
  • Future development
    • PoR and NFT minting for graphics creative assets
    • ZKP and PoR communication
    • Inferix RemotePC
    • Rendering professional network
  • Terms of Service
    • Privacy Policy
    • Airdrop Terms of Service
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  1. Decentralized visual computing

Manager node

Manager Node(s) are computers that handle API load balancing and manage Inferix's services, including Rendering, AI Training/Inference, and Remote PC services.

A manager node consists of two components: Service Controller and Job Controller. The rendering cost calculations based on the PoR algorithm will be sent by the Service Controller to the end users, allowing them to decide whether to submit an order. The Job Controller is responsible for dividing rendering jobs into different tasks and assigning them to Worker Nodes for execution. For example, a 1000-frame video rendering job can be divided into 200 tasks, with each task rendering 5 frames. These tasks are pushed into TaskQueue. Available workers that meet the minimum hardware capability requirements, based on the Inferix Bench index, will be randomly assigned to perform the rendering tasks. The rendered results are then aggregated according to the process outlined in the rendering flow.

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Last updated 4 months ago