Scan vGPU Solutions

Virtualisation solutions powered by NVIDIA

Scan provides virtualisation solutions powered by NVIDIA for visualisation and compute, bringing the power of NVIDIA GPUs to virtual desktops, accelerating graphics and compute to make virtualised workspaces accessible to creative and technical professionals working from home offices, remote sites or anywhere in the world.

NVIDIA vGPU solutions deliver the ultimate user experience with the ability to support both compute and graphics workloads in hypervisor-based virtualisation environments.


NVIDIA Virtual Compute Server (vCS)

NVIDIA vCS provides the ability to virtualise GPUs and accelerate compute-intensive server workloads, including AI, Deep Learning, and HPC.


NVIDIA RTX Virtual Workstation (vWS)

Designers and engineers working with increasingly complex models can work more efficiently, collaborate across geographies, and bring their creations to market more quickly with NVIDIA vWS.


NVIDIA Omniverse

NVIDIA Omniverse is a powerful multi-GPU real-time simulation and collaboration platform for 3D production pipelines based on NVIDIA RTX technology and building on vWS capabilities.



Workers who use graphics intensive applications and often multitask across dual monitors can leverage NVIDIA vPC to scale VDI deployments with a consistently appealing user experience.



Our Cloud Rendering service, powered by NVIDIA GPU accelerators provides rapid remote rendering without having to invest in your own servers and infrastructure to support them.

Tech News, Partnerships and Case Studies


NVIDIA A40 now supported for vDWS The new NVIDIA A40 GPU is now supported on vDWS deployments offering huge performance for virtual workloads.

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Scan announces partnership with Run:AI Run:AI offers the ability to pool dissimilar GPU environments to create a pool that can be shared divided as combined workload changes.

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Tech Explained

NGC and containers supported in vCS NVIDIA GPU Cloud is fully supported for vCS environments offering frameworks and containers for your AI workloads.

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