GNUS.AI
  • 🧠About GNUS.AI
    • GNUS.AI
    • Introduction
    • Features and Benefits
      • Scale and cost-efficiency
      • GNUS.ai Network vs. Centralized xAI 100k Cluster
        • 1. Executive Summary
        • 2. Introduction
        • 3. Understanding the GNUS.ai Decentralized Network
        • 4. The Centralized xAI 100k Cluster Explained
        • 5. Comparing CAPEX and OPEX
        • 6. Payout Structure and Profitability
        • 7. The Deflationary Token Mechanism
        • 8. Projected Token Price Appreciation
        • 9. Summary Comparison Tables
        • 10. Conclusion and Next Steps
        • Final Thoughts
      • Tokenomics
    • Public Roadmap
    • Whitepaper
    • Meet the Team
    • Why GNUS.AI
      • Works Everywhere
      • Customizable
      • Fast
      • Secure
        • Secure 2FA with TOTP and zk-SNARKs
    • How Does It Work?
      • Idle Central Processing (GPU)
      • Distributed Computation
      • Dynamically Adjusted Resource Allocation
  • 🖥️Technical Information
    • Super Genius Blockchain Technical Details
      • SuperGenius DB Layout
      • AI Data Blocks
      • Slicing Data for Macro MicroJobs
      • Verification and Hash Results from Processing
      • Diagram of the internal blockchain, blocks and processing functionality
      • IPFS Pub Sub
      • SG Consensus Algorithm Implementation
      • Account creation with ECSDA and El Gamal
      • Key Derivation Function
      • El Gamal encryption
      • Prover specification
      • C++ Coding Standards
      • SuperGenius processing component information
        • Processing worker app workflow
        • Job Processing Flow
      • Super Genius DAG Blockchain
      • Minimal MMR Proof System with UTXOs
      • Cross-chain Bridging through SuperGenius
        • Overview of Technical Details for Cross-Chain Bridging Flow
        • Message Creation and Leader Election
        • Leader Ownership and Verification Channel Creation
        • Node Verification and Voting
        • Signature Collection and Aggregation
        • Destination Chain Submission and Validation
    • Hybrid Smart Contract
      • GNUS.ai Ecosystem: A Unified Network of Intelligence
      • Structure
        • Structure Details
      • Encoded IDs
    • Our Smart Contract Testing Philosophy
    • AI Systems
      • Overview
      • Query Workflow
      • Data Storage
      • Pub/Sub Communication
      • Retraining Mechanism
    • Zero Knowledge Proofs
      • Proof schemes and Elliptical Curves
  • Resources
    • Contact Us
    • Contracts
    • FAQS
    • Multisig Wallets
    • Glossary
    • Official Links
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  1. About GNUS.AI
  2. How Does It Work?

Dynamically Adjusted Resource Allocation

-Empowering systems to adapt and thrive in the face of dynamic challenges

Dynamically adjusted resource allocation refers to a system or mechanism that allocates resources based on changing demands or conditions. In the context of GNUS.AI, it involves the intelligent distribution of resources such as processing power and memory to optimize performance and responsiveness. This concept works synergistically with distributed computation. Think of one as monitoring the demand for resources, while the other breaks down the available resources to efficiently complete the tasks.

The result ensures efficient utilization of resources, scalability, and responsiveness to varying requirements. This approach helps in preventing resource bottlenecks, improving overall system performance, and enhancing the user experience.

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Last updated 1 year ago

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