Virtual GPU (vGPU) – what is it?

Virtual GPU (vGPU) is a technology that enables sharing the resources of a single physical GPU across multiple virtual machines or applications, providing isolated access to GPU compute and graphics capabilities. In this architecture, vGPU is implemented at the hypervisor level or via specialized drivers, allowing efficient utilization of hardware resources, performance control, and multi-tenant access to GPUs within a single server. The approach is based on GPU virtualization, which combines hardware and software mechanisms to partition resources with minimal performance overhead, including support for GPU profiles that define available video memory, number of compute cores, and resource access priority.

In practical scenarios, virtual GPU is used for virtual desktop infrastructure (VDI), engineering applications (CAD/CAE), 3D visualization, video processing, and AI/ML workloads where multiple users or services concurrently access GPU resources. This model enables optimization of expensive hardware utilization, centralized infrastructure management, flexible scaling, and integration with cloud or hybrid environments. Additionally, vGPU supports dynamic resource reallocation, integration with orchestration systems (e.g., Kubernetes via GPU operators), and performance monitoring, enabling consistent service quality, workload forecasting, and efficient resource management in high-density compute environments.