NVIDIA® Virtual GPU (vGPU) software is a technology designed to virtualize NVIDIA's powerful GPU capabilities across multiple virtual machines (VMs) or virtual desktops. This technology allows for efficient sharing of GPU resources among multiple users and applications, enabling enhanced graphics and compute performance in virtualized environments. It's particularly beneficial in data centers, enterprise environments, and for cloud-based applications where hardware resources such as GPUs must be maximized across several users or tasks. ### Key Features of NVIDIA® Virtual GPU Software: 1. **GPU Virtualization**: NVIDIA® vGPU software enables the GPU to be virtualized to provide accelerated graphics and computing to multiple virtual machines. This allows each VM to have access to GPU resources tailored to its specific needs without requiring a dedicated physical GPU for each VM. 2. **Scalability and Efficiency**: By allowing multiple VMs to share a single physical GPU, NVIDIA vGPU can significantly increase the efficiency of resource utilization in data centers, reducing both hardware costs and power consumption. 3. **Broad Compatibility**: NVIDIA vGPU supports a wide range of NVIDIA GPUs and is compatible with various hypervisors including VMware vSphere, Citrix Hypervisor, and Red Hat Virtualization. 4. **Enhanced User Experience**: NVIDIA vGPU provides a rich, user-responsive experience similar to that of a native PC or workstation. It supports high-resolution displays, and extensive 3D applications, and provides a seamless experience for tasks requiring substantial graphical power such as video editing, 3D rendering, and professional design. 5. **Management and Monitoring Tools**: Comes with a management platform that allows IT administrators to allocate GPU resources, monitor performance, and optimize the deployment of the virtual GPUs across the network. ### Use Cases: 1. **Virtual Desktop Infrastructure (VDI)**: In VDI setups, NVIDIA vGPU can deliver rich graphics and computing power to virtual desktops, providing users with a performance that mirrors that of a local desktop, even when running GPU-intensive applications. 2. **AI and Machine Learning**: For environments focused on AI and ML, NVIDIA vGPU can allocate GPU resources to various virtual machines running simulations, training models, or processing large datasets, optimizing the GPU utilization. 3. **3D Rendering and Video Processing**: Media and entertainment industries, as well as architectural and engineering firms, benefit from NVIDIA vGPU for performing complex 3D rendering and video processing tasks in a virtualized environment. 4. **Gaming and Simulation**: Cloud gaming platforms and simulation-based training programs can utilize NVIDIA vGPU to provide high-quality, low-latency experiences to users across various devices. ### Licensing: NVIDIA vGPU software requires a license to operate, which can be obtained through NVIDIA's licensing portal. The licensing model depends on the specific type and number of GPUs used, as well as the desired features and the number of concurrent users. ### Conclusion: NVIDIA® Virtual GPU software represents a significant advancement in the ability to efficiently utilize GPU resources in virtualized environments. It extends the power of NVIDIA GPUs to a broader range of applications and users, enabling businesses and enterprises to maximize their hardware investment while delivering high-performance computing and graphics capabilities to virtual machines. # References ```dataview Table title as Title, authors as Authors where contains(subject, "NVIDIA virtual GPU Software") or contains(subject, "vGPU") or contains(subject, "Proxmox") or contains(subject, "GPU virtualization") sort title, authors, modified, desc ```