Key Technologies

Dynamic Resource Allocation Engine

What it does:

• Uses reinforcement learning to optimize GPU resource distribution in real-time.

• Increases GPU efficiency by up to 170% by prioritizing workloads dynamically.

• Balances energy consumption vs. performance, ensuring GPUs are always running at peak efficiency.

Why it matters:

• Reduces wasted compute power and energy costs.

• Ensures time-sensitive AI tasks get priority access.

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GPU Virtualization & Containerization

What it does:

• Splits a single GPU into multiple, isolated environments using Docker/Kubernetes.

• Allows multiple AI jobs to run simultaneously without interference.

• Ensures optimal GPU utilization even during peak demand periods.

Why it matters:

• Enables seamless multi-tasking on decentralized hardware.

• AI companies no lo

• nger need dedicated GPUs, they can rent fractional power as needed.