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Does your HPC/AI environment need virtual GPU (vGPU) capability?
The NVIDIA® Virtual GPU (vGPU) and Virtual Compute Server (vCS) Software enables the NVIDIA GPU to be virtualized to accelerate compute-intensive server workloads such as AI, deep learning (DL), machine learning, and HPC. Grid provides graphics at scale across the enterprise with GPUs for exceptional productivity, security, and IT manageability by delivering powerful virtual experience from the data center or cloud to any device. vCS provides accelerated GPU virtualization and GPU sharing/segmentation for multiple virtual machines (VMs) by a single GPU, maximizing allocation for AI/DL intensive workloads. vCS provides bare metal performance with operational savings, costs, and improved manageability of VMs. By making GPU performance possible for every virtual machine (VM), vGPU technology enables users to work more efficiently and productively from the data center to the cloud.
NVIDIA Virtual GPU (vGPU) and Virtual Compute Server (vCS) software features GPU-accelerated performance for the virtual enterprise.
NVIDIA Virtual GPU (vGPU) software improves virtual desktops and applications for every user with proven performance built on NVIDIA GPUs for exceptional productivity, security, and IT manageability.
Significant Operations Savings
The NVIDIA Virtual GPU (vGPU) and Virtual Compute Server (vCS) software virtual GPU technology provides our customers with significant operations savings in downtime, IT staff costs (IDC estimates 49% operations savings over non vGPU).1
Replace high-cost workstations for end users with a complete virtualized solution. Help optimize capital and operating expenses involved in providing access to applications to globally distributed users.
NVIDIA Virtual Compute Server Provides GPU Acceleration and Segmentation for Server Virtualization
NVIDIA Virtual GPU (vGPU) and Virtual Compute Server (vCS) software provides GPU segmentation increasing allocation for AI workloads.
NVIDIA Virtual Compute Server (vCS) enables data centers to accelerate server virtualization with GPUs so that the most compute-intensive workloads, such as AI, DL, and data science can be run in a virtual machine.
[1] Per IDC whitepaper "NVIDIA Is Helping Organizations Provide Optimized Virtual Client Computing for Graphics and End-User Computing": https://www.nvidia.com/content/dam/en-zz/Solutions/data-center/gated-resources/idc-business-impact-study.pdf
