At GTC Munich: The Power of Virtualization Multiplied with Enhanced vGPU Solutions
10/10/2018
Quadro vDWS with multi-GPU performance enables professionals to work remotely on any device, while their designs and intellectual property are secured in the data center.
Creative professionals working on remote, virtual workstations can render compelling, photoreal visualizations 94 percent faster with the added power of two Tesla V100 Tensor Core GPUs instead of a single Tesla V100. Engineers and designers can complete simulations nearly 7x faster with two Tesla V100 GPUs compared to a CPU-only system.
The newest edition of NVIDIA virtual GPU software ensures reliability and ease of management with features like live migration. New capabilities in the NVIDIA vGPU October 2018 release (Quadro vDWS and GRID software) include:
Run Multi-GPU Workloads with NVIDIA Quadro vDWS - Experience monumental improvement in virtual GPU performance by aggregating the power of up to four NVIDIA Tesla GPUs in a single virtual machine (VM) for the most graphics- and compute-intensive rendering, simulation and design workflows. With this release, NVIDIA virtual GPU products now support aggregation of multiple Tesla GPUs and GPU sharing across multiple VMs. Red Hat will be the first virtualization platform to include this capability with its Red Hat Enterprise Linux 7.5 and Red Hat Virtualization 4.2 KVM release.
Live Migration with VMware vMotion - IT can migrate live, NVIDIA GPU-accelerated VMs without impacting users or requiring scheduled downtime, saving valuable time and resources. IT teams are freed up to focus on more strategic projects and drive business transformation. This new feature is now supported on the Quadro vDWS and GRID vPC and GRID vApps software products with VMware vMotion, vSphere 6.7 u1.
Support for NVIDIA Tesla T4 GPUs - Get 2x the framebuffer in the same low-profile, single-slot form factor as the previous generation Tesla P4. When combined with multi-GPU support, the new 70W Tesla T4 enables ever more demanding workflows in a virtual desktop infrastructure environment, including advanced rendering, simulation and design.
AI workloads on VMs with NVIDIA GPU Cloud - NGC empowers AI researchers with GPU-accelerated deep learning containers for TensorFlow, PyTorch, MXNet, TensorRT and more. The ready-to-run deep learning containers from NGC are now tested with the latest release of Quadro vDWS. These pre-integrated, GPU-accelerated containers include NVIDIA CUDA Toolkit, NVIDIA deep learning libraries and an operating system.
Broad Ecosystem Support from ISVs and OEMs Simulation-driven product development takes engineering simulation to another level and the ability to scale multiple GPUs really kicks it up a notch. With the latest NVIDIA vGPU (Quadro vDWS), our users can work faster, more smoothly and more securely from just about anywhere - and in some cases, for significantly less cost than a vCPU only solution. - Sunil Sathe, lead software developer at ANSYS
Inspiration can strike anywhere. Autodesk Maya users are now able to utilize up to four NVIDIA Tesla GPUs in a single virtual machine, so the workstation can create and render faster photorealistic scenes regardless of when or where our customers are. - Chris Vienneau, senior director of Media & Entertainment at Autodesk
Cisco UCS and HyperFlex provide users with a proven, flexible and scalable platform for running GPU-accelerated virtual desktops and applications. The new NVIDIA capabilities for multiple GPUs support on a single VM will give customers a significantly enhanced experience for their GPU-enabled high-performance graphics applications, while support for VMware vGPU vMotion will insure seamless maintenance windows for the IT staff. - Siva Sivakumar, senior director of UCS Solutions in the Cisco Data Center Group
In the past, GPU virtualization was limited to developers on remote sites and automated testing, where a little planned downtime is acceptable. With vMotion technology support on NVIDIA virtual GPU, we can now expand virtualization to our production environments, where failure and downtime is not an option. Patching, load balancing and upgrades of hardware and software have become a breeze, and end-users don't notice a thing. - Ouissame Bekada, system, virtualization and storage engineer at Dassault Syst mes
With the latest release of the NVIDIA vGPU software that supports up to four GPUs per virtual machine that can be accessed remotely, we are enabling our customers, no matter where they are, to deliver best-in-class performance for the most challenging workloads across simulation, modeling and design. - Bill Mannel, vice president and general manager of HPC and AI at HPE
Through our close collaboration with NVIDIA, Red Hat Virtualization will soon be the first virtualization platform to enable multi-GPU workflows in support of NVIDIA's Quadro Virtual Data Center Workstation software. Customers will soon be able to use NVIDIA's newest GPUs on a fully open, enterprise-ready virtual foundation built on the backbone of the world's leading enterprise Linux platform in Red Hat Enterprise Linux. - Joe Fernandes, vice president, Products, Cloud Platforms Business Unit, Red Hat
The flexibility of the new multi-GPU feature available with the NVIDIA Quadro Virtual Data Center Workstation opens up powerful new rendering workflows to SOLIDWORKS Visualize users. The near-linear performance scaling means they can iterate on their designs at lightning speed on professional virtual workstations, allowing our customers to arrive at their best design in the shortest amount of time. - Brian Hillner, product portfolio
LINK: | https://blogs.nvidia.com/blog/2018/10/09/the-power-of-virtualization-m... |
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