Discussion and demonstration of the potential with running HPC, and VDI workloads on common clusters for a modern a datacenter Dr. Jekyll and Mr. Hyde scenario. Explore the coexistence of CUDA based HPC or Deep Learning job engines in conjunction with both Linux and Windows machines used for virtual desktop infrastructure. The demonstration will focus on a very minimal VMware vSphere cluster deployment using VSAN storage or RedHat RHVM cluster deployment to host both the Linux HPC multi node cluster for CUDA workloads and a VMware Horizon view or Citrix XenDesktop deployment for Linux and Windows Virtual Desktops performing DirectX, OpenGL, OpenCL, and CUDA based visualization workloads as used by engineering and analysis power users.
Deploying PC-based Virtual Reality solutions in the Enterprise poses challenges over the typical consumer model of one room housing one PC driving one Head Mounted Display worn by one user. For Consumer VR inside the home, the primary user typically owns and maintains both PC and setup location. For some Enterprise VR use cases, the conventional 1:1:1:(Rooms:PCs:HMDs:Users) ratio is manageable however, as the number of simultaneous collocated VR users increases, these deployments become unwieldy and a 1:1:n:n ratio would be preferable. Enterprise requirements come into play such as multi-user collaboration, large dynamic data sets, limited physical space, mobility to temporary locations, limited setup/pack up time, concurrent users scalability, remote IT management, configuration control and system image replication. We'll introduce an experimental approach to Multi-User VR deployment based on virtualization techniques that aims to address these Enterprise Use-Case requirements.