Distributed Computation

-Transforming latency into computational synergy.

Distributed Computation involves breaking down a task into smaller sub-tasks that can be processed concurrently across multiple nodes within a network. This is especially relevant when larger tasks, demanding substantial processing power, can be divided and distributed among the processing capacities of multiple users.

How GNUS.AI Utilizes Distributed Computation:

  1. Task Division:

    • GNUS.AI identifies tasks that require computational power, such as complex AI computations, blockchain transactions, or data processing.

  2. Task Distribution:

    • The identified tasks are divided into smaller sub-tasks and distributed among the nodes. Each node independently processes its assigned sub-task.

  3. Parallel Processing:

    • Nodes work simultaneously on their allocated sub-tasks, leveraging parallel processing capabilities. This significantly accelerates the overall task completion time.

Managing computational resources highlights the flexibility of GNUS.AI to operate opportunistically during periods of device inactivity.

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