GPU-as-a-Service with Red Hat AI: Getting the most out of your AI accelerators

The most expensive GPU is the one that’s sitting idle. As organizations race to secure AI compute capacity, fragmented hardware allocation across teams often leads to low utilization and stalled ROI. 

In this demo, our experts will show how Red Hat^® AI enables a shift from dedicated GPU allocation to a shared, high-utilization GPU-as-a-Service (GPUaaS) model. 

We’ll explore orchestration strategies—including fractional GPU sharing and intelligent scheduling—that maximize cluster efficiency and help your AI infrastructure scale sustainably and cost-effectively.