WHITEPAPER
Software-Defined GPU
Making GPUaaS work for service providers and the mainstream AI hosting market
You’re not virtualizing GPU the wrong way – you’re just not doing it the optimal way for maximum utilization, flexibility and ROI from your hardware investments.
This high-level whitepaper explains the difference between GPU virtualization and true GPU as a Service (GPUaaS).
It explores the benefits and drawbacks of GPU passthrough, instancing and slicing, and explains why service provider GPUaaS requires a different approach – especially for AI inference workloads. To get your free copy, just fill out the form.
Contents
- Why GPU virtualization ≠ GPUaaS
- What does service provider GPUaaS need?
- Software-Defined GPU requirements
- hosted·ai GPUaaS architecture
- hosted·ai hyperconverged platform
- Standalone GPUaaS with hosted·ai
- More information