USDAI
  • Introduction
  • Why Compute-Backed?
  • Vision & Purpose
  • GPU.NET Ecosystem
    • What is GPU.NET?
    • Key Components of GPU.NET
    • GPU.NET’s Mission
    • USDAI’s Role in the Ecosystem
  • USDAI Mechanics
    • How USDAI Works
    • Pegging Mechanism
    • Collateralization
    • Issuance and Redemption
    • Stability Mechanisms
    • Why It Works
  • USDAI Architecture
    • Architecture
    • Supported Blockchains
    • Interoperability
    • Smart Contracts
    • Security Features
  • Use Cases
    • USDAI Applications
    • AI/ML Workload Payments
    • DeFi Integrations
    • Compute Reservations
    • Broader Implications
  • Acquiring USDAI
    • How to Acquire USDAI
    • Using USDAI
    • Developer Integration
  • Governance and Community
    • Governance
    • Roadmap
    • FAQ
    • Support & Community
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  1. Acquiring USDAI

Developer Integration

For developers building applications on GPU.NET, USDAI offers powerful tools to integrate compute payments and resource access seamlessly.

API: Access GPU.NET’s Compute Marketplace

  • Overview: GPU.NET provides RESTful APIs to interact with its compute marketplace and USDAI payments programmatically.

  • Features:

    • Query available GPU resources (e.g., /api/v1/resources?type=A100).

    • Reserve compute with USDAI (e.g., POST /api/v1/reserve {amount: 10}).

    • Check USDAI balances and transaction status.

  • How to Use:

    1. Request an API key from GPU.NET (post-launch).

    2. Authenticate requests with your key (e.g., Authorization: Bearer <key>).

    3. Integrate endpoints into your app (e.g., Python requests library).

  • Example: A Python script queries /api/v1/resources, reserves 5 USDAI worth of compute, and monitors usage for an AI pipeline.

SDK: Streamlined Integration in Python and JavaScript

  • Overview: The GPU.NET SDK simplifies USDAI integration, available in Python and JavaScript, with more languages planned post-launch.

  • Features:

    • Wallet connection (e.g., connectWallet()).

    • USDAI transactions (e.g., payUSDAI(amount=10, task="training")).

    • Compute management (e.g., getComputeStatus()).

  • How to Install:

    • Python: pip install gpunet-sdk.

    • JavaScript: npm install gpunet-sdk.

  • Example: python WrapCopy from gpunet import GPUClient client = GPUClient(wallet="my_private_key") client.payUSDAI(amount=20, task="inference") print(client.getComputeStatus())

  • Benefits: Reduces development time, abstracts blockchain complexity, and ensures compatibility with GPU.NET’s infrastructure.

Next Steps

  • Pre-Launch: Experiment with USDAI on GPU.NET’s testnet (Q1 2025), minting test tokens and exploring Dapp.gpu.net.

  • Post-Launch: Join the ecosystem in March 2025—acquire USDAI, contribute compute, or integrate it into your projects.

  • Support: Visit gpu.net/support or join our Discord for help.

With these tools and steps, you’re ready to harness USDAI’s power. Whether you’re powering AI innovation, earning rewards, or building the next big app, USDAI and GPU.NET make it simple and effective.

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Last updated 3 months ago