Partner Content GPU workloads are no longer the exclusive territory of research labs and hyperscalers. Engineering teams, data science groups, healthcare organizations, and financial services businesses are all deploying GPU-accelerated infrastructure for AI inference, simulation, visualization, and virtual desktops. For many IT teams, this is new ground. The hardware is familiar, because NVIDIA GPUs fit in standard server slots. But the software isn't. GPU virtualization has three distinct models.