ShardGPU’s virtualization technology allows a single GPU to be split into multiple secure environments, making GPU usage more efficient and scalable.
GPU Partitioning: Using Docker & Kubernetes, GPUs are divided into isolated workloads.
Multi-Tasking Efficiency: Multiple users can run AI models, render graphics, or compute simulations at the same time without interference.
Smart Resource Management: AI algorithms predict GPU demand and adjust capacity on-the-fly.
Enables more users to rent GPUs without conflicts.
Maximizes earnings for GPU owners by handling multiple tasks at once.
AI companies get seamless compute scaling, even during peak demand.
ShardGPU transforms individual GPUs into highly flexible, multi-purpose compute units, revolutionizing decentralized AI model training and rendering.
Last updated 11 months ago
