Working Remotely: Connecting to Your Office Workstation

With so many people working from home amid the COVID-19 outbreak, staying productive can be challenging.

At NVIDIA, some of us have RTX laptops and remote-working capabilities powered by our virtual GPU software via on-prem servers and the cloud. To help support the many other businesses with GPUs in their servers, we recently made vGPU licenses free for up to 500 users for 90 days to explore their virtualization options.

But many still require access to physical Quadro desktop workstations due to specific hardware configurations or data requirements. And we know this situation is hardly unique.

Many designers, engineers, artists and architects have Quadro RTX mobile workstations that are on par with their desktop counterparts, which helps them stay productive anywhere. However, a vast number of professionals don’t have access to their office-based workstations — with multiple high-end GPUs, large memory and storage, as well as applications and data.

These workstations are critical for keeping  everything from family firms to multinational corporations going. And this has forced IT teams to explore different ways to address the challenges of working from home by connecting remotely to an office workstation.

Getting Started: Tools for Remote Connections

The list below shows several publicly available remote-working tools that are helpful to get going quickly. For details on features and licensing, contact the respective providers.

Managing Access, Drivers and Reboots

Once you’re up and running, keep these considerations in mind:

Give yourself a safety net when working on a remote system 

There are times that your tools can stop working, so it’s a good idea to have a safety net. Always install a VNC server on the machine (, or others) no matter what remote access tool you use. It’s also a good idea to enable Access to Microsoft Remote Desktop as another option. These run quietly in the background, but are ready if you need them in an emergency

Updating your driver remotely

We recommend you use a VNC connection to upgrade your drivers. Changing the driver often changes the parts the driver the remote access tools are using, so you often lose the connection. VNC doesn’t connect into the driver at a low level, so keeps working as the old driver is changed out to the new. Once the driver is updated, you can go back to your other remote access tools.

Rebooting your machine remotely

Normally you can reboot with the windows menus. Give the system a few minutes to restart and then log back in. If your main remote-working tools have stopped functioning, try a VNC connection. You can also restart from a PowerShell Window or command prompt from your local machine with the command: shutdown /r /t 0 /m \\[machine-name]

App-Specific Resources

Several software makers with applications for professionals working in the manufacturing, architecture, and media and entertainment industries have provided instructions on using their applications from home. Here are links to a few recent articles:

Where to Get Help

Given the inherent variability in working from home, there’s no one-size-fits-all solution. If you run into technical issues and have questions, feel free to contact us at We’ll do our best to help.

The post Working Remotely: Connecting to Your Office Workstation appeared first on The Official NVIDIA Blog.

NVIDIA Expands Free Access to GPU Virtualization Software to Support Remote Workers

In challenging times, our strength comes from working together. With many companies needing to quickly support employees now working remotely, NVIDIA is expanding our free, 90-day virtual GPU software evaluation from 128 to 500 licenses.

With vGPU software licenses, companies can use their on-premises NVIDIA GPUs to provide accelerated virtual infrastructure so people can work and collaborate from anywhere. Companies can also temporarily repurpose NVIDIA GPUs being used on other projects to support their remote workers.

Every organization is working hard to address these needs: Healthcare providers are supporting care from new locations. Schools are expanding their virtual classrooms. Agencies are coordinating critical services.

Whether supporting financial professionals working with data on multiple screens, scientists conducting research, or designers working in graphics-intensive applications, enterprises are faced with different workloads that have different requirements.

NVIDIA offers a variety of customized vGPU software to meet these diverse needs. All three tiers of the company’s specialized vGPU software are available through the expanded free licensing:

  • NVIDIA GRID software delivers responsive VDI by virtualizing systems and applications for knowledge workers.
  • NVIDIA Quadro Virtual Data Center Workstation software provides workstation-class performance for creators using high-end graphics applications.
  • NVIDIA Virtual Compute Server software accelerates server virtualization with GPUs to power the most compute-intensive workflows, such as AI, deep learning and data science on a virtual machine.

Virtualized Performance, Enterprise Security and Broad Ecosystem Support

In addition to providing high performance and reducing latency for remote workers, NVIDIA vGPU software ensures protection for sensitive data and digital assets, which remain in the data center and aren’t saved to local client devices. This is an important security requirement for remote work across many industries, including visual effects and design, as well as for research and development.

NVIDIA vGPU software is certified on a broad ecosystem of hypervisors, platforms, user applications and management software to help IT teams quickly scale out support for remote workers.

Companies can deploy virtual workstations, compute and VDI from their on-prem data centers by installing the vGPU software licenses on all NVIDIA GPUs based on the Pascal, Volta and Turing architectures, including NVIDIA Quadro RTX 6000 and RTX 8000 GPUs, and NVIDIA M10 and M60 GPUs.

Get the Virtual GPU Evaluation.

NVIDIA is also providing genomics researchers studying COVID-19 free access to Parabricks software for 90 days. See our post on Parabricks to learn more.

Supporting links:

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Netherlands Cancer Institute Uses Virtualization to Enhance Patient Care, Advance Cancer Research

Cancer doesn’t take nights off. To help beat the disease, the Netherlands Cancer Institute, rated one of the top 10 comprehensive cancer centers in the world, is using virtualization to have its IT infrastructure work the late shift, as well.

The NKI, which consists of both research facilities and cancer clinics, has dual goals: to accelerate research, while also improving the efficiency and productivity of its physicians.

Whether analyzing images to diagnose breast cancer or running DNA computations with large datasets, the institute relies on innovative, flexible technology to drive new discoveries in cancer research.

To keep up with the increasing needs of doctors and researchers, NKI upgraded to a state-of-the-art, software-defined infrastructure using NVIDIA virtual GPU technology powered by NVIDIA T4 GPUs and Hewlett Packard Enterprise DL380 Gen10 servers.

During the day, this virtual desktop infrastructure provides healthcare professionals with fast, flexible and secure access to patient data. At night, researchers use the same VDI platform to run computationally intensive GPU workloads.

With this high-performance yet flexible IT infrastructure, healthcare professionals can spend more time focusing on patients, while researchers can advance breakthroughs in cancer treatment.

Virtual Desktops Enhances Security and Mobility

Before NKI moved to a virtualized platform, doctors would handle patient data the old-fashioned way: working on physical desktops that stored local apps and information. The doctors would need to go to computer labs, manually log into the system, and open applications up to 20 times a day, a tedious and time-consuming process.

Maintenance and security were challenging. A few times PCs had been stolen, so NKI wanted better security to protect sensitive patient information and research data.

With VDI, physicians can move around the hospital more freely. With workstations available in each room, they can log into a virtual desktop session in one part of the hospital, then easily move to another area and get right back into their session with a swipe of their badge.

This ability to quickly switch allows NKI’s healthcare professionals to work much faster and more efficiently, providing clinicians with greater flexibility to move from one patient to another.

The VDI platform also stores all data in a safe, central environment rather than individual devices. Doctors and nurses who can securely access apps and information on mobile phones, tablets, at home or on the road.

vGPUs Bring More Power, Speed to Research 

NKI’s new infrastructure is made up of 78 HPE servers, each with three NVIDIA T4 GPUs, to provide doctors and researchers with massive GPU power for computations like DNA or image analysis.

Its clinics are busiest during the day. But most users log off in the evening, freeing up a majority of the GPU resources for cancer research. With virtualization, researchers can repurpose the T4 GPUs that aren’t in use for running complex compute workloads at night.

“Before, it would take a week for researchers to get their photos analyzed at an imaging facility,” said Roel Sijstermans, IT manager at NKI. “With the new virtual GPU infrastructure, we can send the pictures in the evening and the images will be finished by the morning.”

With data being processed overnight, researchers can analyze breast cancer tumors or increase image quality at a faster rate than before, giving doctors more time to plan their care for patients.

Register now for GTC Digital to learn more about the Netherlands Cancer Institute and how virtualization is changing the future of healthcare.

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New Year, New User Experience: NVIDIA vGPU Enhances Virtualization, Adds 8K VDI Display Support

Virtual workstations can now handle applications running at 8K resolution thanks to the latest release of NVIDIA virtual GPU (vGPU) technology.

NVIDIA vGPU software delivers an improved user experience and the performance of the latest GPUs needed to run the most demanding graphics, AI and high performance computing workloads in virtualized environments.

Whether you’re editing cinema-quality video in the field or designing a new product from a home office, vGPU delivers the resolution required to create your best work, even if you’re not at work.

The software now provides support for up to two 8K displays with the Quadro Virtual Data Center Workstation (Quadro vDWS) software license. Designers can see more details in context without the need to zoom in and out of images. Professionals can use multiple or widescreen displays to accelerate their workflows while optimizing GPU usage and maximizing efficiency through virtualization.

Additionally, GRID virtual PC (GRID vPC) software now includes support for 5K displays, bringing the benefits of better display performance to mainstream VDI users.

With Quadro vDWS and GRID vPC, those working with today’s highest-resolution graphics can access powerful GPU performance, even when using multiple 4K, 5K or 8K displays in a virtual environment.

Operations and Upgrades, Simplified

Powered by NVIDIA RTX 8000 and RTX 6000, NVIDIA vGPU software accelerates high-performance Quadro virtual workstations that enable artists to create 3D visualizations even faster with photorealistic quality. With the flexibility to provision virtual graphics workstations and compute-intensive workloads from a single RTX Server with NVIDIA Quadro vDWS or NVIDIA vComputeServer, respectively, vGPU software products extend the power of RTX to designers working on any device.

vGPU software also supports NVIDIA V100S GPUs, the most powerful processors for AI, to accelerate complex deep learning, data science and HPC workflows in a virtualized environment with NVIDIA vComputeServer.

To boost efficiency further,  vGPU software enables underused GPU resources to run other workloads, such as virtual desktops with NVIDIA GRID, or AI and HPC with NVIDIA vComputeServer.

The latest vGPU release will be available soon.

Lakeside Software Measures VDI User Experience with NVIDIA nVector

Measuring the quality of the virtualization user experience has been a challenge for the industry, and is often a contributor to slow user adoption and even failed VDI initiatives.

Lakeside Software, a global software company that provides performance data and analytics for physical and virtual desktops, is collaborating with NVIDIA to take user experience to the next level.

NVIDIA’s nVector benchmarking tool measures key aspects of the user experience, including end-user latency, framerate, image quality and server utilization. This delivers better insights and feedback on the actual end-user experience, enabling IT to architect and size the VDI infrastructure based on relevant utilization thresholds.

SysTrack, Lakeside’s digital experience monitoring platform, collects over 10,000 data points on the endpoint every 15 seconds. The granularity of collection makes it a perfect match for discovering the root cause of user experience problems discovered by nVector. With SysTrack, IT admins can pinpoint when the problem started, what’s causing it and the best path forward to resolution.

Learn more about NVIDIA nVector in our whitepaper.

Today’s Forecast: Increasing Virtual Clouds

NVIDIA vGPU in the cloud is expanding, with Tencent Cloud recently announcing the world’s first vGPU compute offering with support for NVIDIA T4 GPUs and NVIDIA vComputeServer on the public cloud. The new Tencent Cloud GN7 instances have been architected to help Tencent Cloud customers easily implement and scale data analytics, machine learning, AI and other enterprise workloads.

A number of sessions at GTC China this week will explore the power of NVIDIA vGPU software, including how NVIDIA virtualized GPUs power any AI workload, led by John Fanelli, vice president of NVIDIA GPU Virtualization, and Anne Hecht, senior product marketing director of NVIDIA GPU Virtualization.

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NVIDIA CloudXR Delivers Low-Latency AR/VR Streaming Over 5G Networks to Any Device

Enterprises can now deliver virtual and augmented reality experiences across 5G networks to any device with the introduction of NVIDIA CloudXR.

Built on NVIDIA GPU technology, the new NVIDIA CloudXR software development kit helps businesses create and deliver high-quality, wireless AR and VR experiences from any application based on OpenVR, the broadly used VR hardware and software interface.

With NVIDIA CloudXR, users don’t need to be physically tethered to a high-performance computer to drive rich, immersive environments. The SDK runs on NVIDIA servers located in the cloud or on-premises, delivering the advanced graphics performance needed for wireless virtual, augmented or mixed reality environments — which collectively are known as XR.

Companies that have their own 5G networks can use NVIDIA CloudXR to stream immersive environments from their on-prem data centers. Telcos, software makers and device manufacturers can use the high bandwidth and low latency of 5G signals to provide high framerate, low-latency immersive XR experiences to millions of customers in more locations than previously possible.

From product designers who review 3D models at scale to first responders who practice rescue scenarios through simulations, anyone can benefit from CloudXR using Windows and Android devices, including handheld tablets, VR headsets and AR glasses.

NVIDIA CloudXR Takes Wireless Streaming to the Edge

NVIDIA CloudXR leverages VR-ready NVIDIA GPUs to provide enterprises with huge computational power, so they can deliver high-quality immersive environments for even the most graphics-intensive XR configurations.  The SDK includes:

  • Server driver that runs in the data center
  • Easy-to-use client library to enable VR/AR streaming for a multitude of OpenVR applications to Android and Windows devices
  • SDK for portable client devices that let application developers easily stream rendered content from the cloud

These components work in tandem to dynamically optimize streaming parameters and maximize image quality and frame rates, so XR experiences can maintain optimal quality under any network condition.

To learn more, sign up for early access to the NVIDIA CloudXR SDK.

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Intel, Lockheed Martin Collaborate with Systems Providers to Advance Security for Critical Workloads

capitol 2x1What’s New: Today at the Intel Federal Summit 2019 in Washington, D.C., Intel announced that it has collaborated with industry leaders including Hewlett Packard Enterprise (HPE), Mercury Systems and Supermicro (SMCI) as they ready solutions for market based on the Intel® Select Solutions for Hardened Security with Lockheed Martin. The solutions are built on a foundation of 2nd Generation Intel® Xeon® Scalable processors and provide protection across the entire computing stack, from hardware to software, including hypervisors, operating systems and applications.

“The devastation of cybercrime has rallied the smartest minds within the tech industry to find a new way to architect technology to protect an organization’s most critical data. Our work with Lockheed Martin is being used in production to secure the most sensitive workloads and marks the next level of hardware-based security that is essential for the future of cloud computing at scale, joining a rich set of solutions in the Intel portfolio.”
–William Giard, chief technology officer, Digital Transformation & Scale Solutions, Data Center Group at Intel

Why It Matters: Security remains the number one consideration in how enterprise and government entities evaluate their cloud workloads. Intel is working with industry leaders in the ecosystem like HPE, Mercury Systems and Supermicro to improve the security posture for enterprise and government customers. Infrastructure modernization has not been easy to address in conventional virtual machine (VM) environments due to security, performance, determinism, complexity and cost requirements.

What It Does: The Intel Select Solutions for Hardened Security with Lockheed Martin reference design helps protect high-value data at runtime through a hardened full-stack security solution. Isolation techniques create advanced runtime security domains within a trusted virtualization environment that are resistant to unauthorized modifications and help to mitigate information leakage outside of each isolated runtime security domain.

The Details: The Intel Select Solutions for Hardened Security with Lockheed Martin reference design represents a combination of Intel and Lockheed Martin technologies developed to improve security beginning when the system is powered on, through boot, BIOS load and runtime of applications in a VM environment. It delivers hardware-enforced firewalling that helps separate sensitive data from untrusted workloads, providing cross-domain protection against leakage, modification and privilege escalation. Partitioning and isolation of shared resources (such as cache, cores, memory and devices) in the virtualized environment support confidentiality, integrity and availability, with consistent application performance. Customer benefits include:

  • Boot protections and a chain of trust verify and maintain system integrity from power-on through the launching of critical applications.
  • User controls and security choices to isolate and protect virtualized workloads. Provides segmentation of shared resources such as cores, cache, memory, and devices.
  • More consistent and deterministic performance with isolated VMs through the segmentation and ideal allocation of compute resources.
  • Modernized infrastructure by consolidating multiple, complex and dedicated legacy servers into a simplified and partitioned solution with advanced performance, new security protections and QoS features. Minimizes time, cost and complexity of evaluating and integrating hardware and software.

More Context: Intel Security News

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Amazon Brings AI Performance to the Cloud with NVIDIA T4 GPUs

Automated yet human-like customer service. Professional workstation performance on any connected device. Cinematic-quality PC gaming.

These are a few of the diverse capabilities coming to cloud users with NVIDIA T4 Tensor Core GPUs now in general availability on AWS in North America, Europe and Asia via new Amazon EC2 G4 instances.

NVIDIA T4 GPUs, supported by an extensive software stack, provide G4 instance users with performance, versatility and efficiency.

The software platform is optimized for a rich set of applications, including NVIDIA cuDNN for deep learning, NVIDIA RAPIDS for data analytics and machine learning, NVIDIA Quadro Virtual Workstation for cloud workstation graphics, and NVIDIA GeForce for cloud gaming. The software stack also includes a wide selection of APIs, CUDA and domain-specific CUDA-X libraries such as TensorRT, NCCL, OptiX and Video Codec SDK.

AWS users can leverage a single instance to accelerate multiple types of production workloads seamlessly and cost-efficiently.

“We focus on solving the toughest challenges that hold our customers back from taking advantage of compute-intensive applications,” said Matt Garman, vice president of Compute Services at AWS. “AWS offers the most comprehensive portfolio to build, train and deploy machine learning models powered by Amazon EC2’s broad selection of instance types optimized for different machine learning use cases. With new G4 instances powered by T4 GPUs, we’re making it more affordable to put machine learning in the hands of every developer.”

Do More AI for Less

NVIDIA T4 is a second-generation Tensor Core GPU, a reinvention of the GPU that achieves the highest performance for AI applications while maintaining the programmability of CUDA.

With up to 130 TOPS of INT8 performance, NVIDIA T4 features mixed-precision tensor processing required to accelerate the constantly evolving innovation, diversity and complexity of AI-based applications like image classification, object detection, natural language understanding, automated speech recognition and recommender systems.

Amazon has been one of the fastest hyperscalers in the industry to provision NVIDIA GPUs with support for ready-to-use NVIDIA NGC containers for training and inference. EC2 P3 instances feature NVIDIA V100 Tensor Core GPUs, allowing customers to reduce machine learning training from days to hours using the Automatic Mixed Precision feature. With EC2 G4, customers can deploy AI services at scale while significantly reducing operational costs.

And through our recently announced partnership with VMware, VMware Cloud on AWS customers will soon gain access to a new, highly scalable and secure cloud service consisting of Amazon EC2 bare metal instances to be accelerated by NVIDIA T4 GPUs and our new NVIDIA Virtual Compute Server (vComputeServer) software.

Businesses will be able to use this enterprise-grade hybrid cloud platform to accelerate application modernization. They’ll be able to unify deployment, migration and operations across a consistent VMware infrastructure from data center to the AWS cloud in support of the most compute-intensive workloads, including AI, machine learning and data analytics.

Real-Time Ray Tracing and AI-Enhanced Graphics Anywhere, Anytime

The long-sought holy grail of computer graphics, real-time ray tracing delivers the most life-like scenes. Designers and artists can create content in a new way with real-time photorealistic rendering, AI-enhanced graphics, and video and image processing.

NVIDIA T4 is the first NVIDIA RTX ray tracing GPU in the cloud.T4 GPUs offer RT Cores, dedicated compute resources that perform ray-tracing operations with extraordinary efficiency, eliminating expensive ray-tracing approaches of the past.

The new G4 instances, combined with NVIDIA Quadro Virtual Workstation (Quadro vWS) Amazon Machine Images, support the latest ray-tracing APIs, including Microsoft DXR, NVIDIA OptiX and Vulkan. Technical and creative professionals in industries like media and entertainment, architecture, manufacturing, and oil and gas can run the latest graphics software applications from the AWS cloud.

Deploying a virtual workstation with AWS is easy and fast, taking less than five minutes. Just visit the AWS Marketplace and select the NVIDIA Quadro vWS machine image and the G4 instance, which is available on Windows Server 2016 and Windows Server 2019.

GPU-Powered Cloud Gaming

The Turing architecture that powers the T4 also brings NVIDIA’s gaming prowess to AWS, enabling the most demanding games to be rendered and streamed using the GPU’s hardware encoder engine, which is programmable with the Video Codec SDK.

Game publishers can build their own cloud-gaming instances based on the latest NVIDIA technology and make their entire catalog of PC titles available to gamers on nearly any device.

Gamers can enjoy all the latest titles at fast, fluid frame rates at high resolutions — without ever needing to worry about hardware upgrades or updating drivers or game patches.

The NVIDIA driver powering this capability is available in the AWS Marketplace and runs on the AWS G4 instance on Windows Server 2016, Windows Server 2019 and Linux OS.

Get Started with AWS EC2 G4 Instances

Clarifai, Electronic Arts, GumGum and PurWeb are among the initial customers using Amazon EC2 G4 instances to take advantage of the compute-versatility and performance of NVIDIA T4 for running a wide diversity of compute-intensive workloads at scale. As a result, both are providing powerful services while reducing costs to build and deploy these services to their own customers.

In coming weeks, G4 instances will also support Amazon Elastic Inference, which allows users to add GPU acceleration to any Amazon EC2 or Amazon SageMaker instance for faster inference at a much lower cost — up to 75 percent savings.

Visit the AWS G4 instances page to learn more and try out the NVIDIA T4 today.

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NVIDIA vComputeServer with NGC Containers Brings GPU Virtualization to AI, Deep Learning and Data Science 

NVIDIA’s virtual GPU (vGPU) technology, which has already transformed virtual client computing, now supports server virtualization for AI, deep learning and data science.

Previously limited to CPU-only, AI workloads can now be easily deployed on virtualized environments like VMware vSphere with new vComputeServer software and NVIDIA NGC. Through our partnership with VMware, this architecture will help organizations to seamlessly migrate AI workloads on GPUs between customer data centers and VMware Cloud on AWS.

vComputeServer gives data center administrators the option to run AI workloads on GPU servers in virtualized environments for improved security, utilization and manageability. IT administrators can use hypervisor virtualization tools like VMware vSphere, including vCenter and vMotion, to manage all their data center applications, including AI applications running on NVIDIA GPUs.

Many companies deploy GPUs in the data center, but GPU-accelerated workloads such as AI training and inferencing run on bare metal. These GPU servers are often isolated, with the need to be managed separately. This limits utilization and flexibility.

With vComputeServer, IT admins can better streamline management of GPU-accelerated virtualized servers while retaining existing workflows and lowering overall operational costs. Compared to CPU-only servers, vComputeServer with four NVIDIA V100 GPUs accelerates deep learning 50x faster, delivering performance near bare metal.


Today’s announcement brings support to VMware vSphere along with existing support for KVM-based hypervisors including Red Hat and Nutanix. This allows admins to use the same management tools for their GPU clusters as they do for the rest of their data center.

Virtual GPUs Boost Performance for Any Workload 

By expanding the vGPU portfolio with NVIDIA vComputeServer, NVIDIA is adding support for data analytics, machine learning, AI, deep learning, HPC and other server workloads. The vGPU portfolio also includes virtual desktop offerings — NVIDIA GRID Virtual PC and GRID Virtual Apps for knowledge workers and Quadro Virtual Data Center Workstation for professional graphics.

NVIDIA vComputerServer provides features like GPU sharing, so multiple virtual machines can be powered by a single GPU, and GPU aggregation, so one or multiple GPUs can power a virtual machine. This results in maximized utilization and affordability.

Features of vComputeServer include:

  • GPU Performance: Up to 50x faster deep learning training than CPU-only, similar performance to running GPU on bare metal.
  • Advanced compute: Error correcting code and dynamic page retirement prevent against data corruption for high-accuracy workloads.
  • Live migration: GPU-enabled virtual machines can be migrated with minimal disruption or downtime.
  • Increased security: Enterprises can extend security benefits of server virtualization to GPU clusters.
  • Multi-tenant isolation: Workloads can be isolated to securely support multiple users on a single infrastructure.
  • Management and monitoring: Admins can use the same hypervisor virtualization tools to manage GPU servers, with visibility at the host, virtual machine and app level.
  • Broad Range of Supported GPUs: vComputeServer is supported on NVIDIA T4 or V100 GPUs, as well as Quadro RTX 8000 and 6000 GPUs, and prior generations of Pascal-architecture P40, P100 and P60 GPUs.

NVIDIA NGC Adds Support for VMware vSphere

NVIDIA NGC, our hub for GPU-optimized software for deep learning, machine learning and HPC, offers over 150 containers, pre-trained models, training scripts and workflows to accelerate AI from concept to production, including RAPIDS, our CUDA-accelerated data science software.

RAPIDS offers a range of open-source libraries to accelerate the entire data science pipeline, including data loading, ETL, model training and inference. This enables data scientists to get their work done more quickly and significantly expands the type of models they’re able to create.

All NGC software can be deployed on virtualized environments like VMware vSphere with vComputeServer.

IT administrators can use hypervisor virtualization tools like VMware vSphere to manage all their NGC containers in VMs running on NVIDIA GPUs.

In addition, NVIDIA helps IT roll out GPU servers faster in production with validated NGC-Ready servers. And enterprise-grade support provides users and administrators with direct access to NVIDIA’s experts for NGC software, minimizing risk and improving productivity.

Industry Support

Leading industry partners have shown support for NVIDIA vComputeServer, including Dell, Cisco and VMware, among others. Read what they have to say.


NVIDIA vComputeServer is available starting in August.

To learn more, visit NVIDIA vComputeServer.

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It’s Only Logical: Animal Logic Steps Up Production Workflows with NVIDIA vGPU Technology


One of the creative studios behind The Matrix’s virtual world is entering a new kind of virtual environment: GPU-powered virtual workstations.

Animal Logic — one of the world’s leading independent creative digital studios —  has had a hand in films including The Matrix, Moulin Rouge! and, more recently, The LEGO Movie 2: The Second Part. To accelerate their visual effects and animation workflows, the shop turned to NVIDIA virtual GPU technology.

When opening a second creative studio in Vancouver, Canada, the Australia-based firm faced a challenge: Their creative staff mainly uses physical workstations running on Linux, but sometimes they need Windows systems to use apps like Adobe Photoshop and Pixologic ZBrush that are essential to production.

To fill this need, studios typically rely on secondary machines — usually older systems they’ve hung onto. But Animal Logic didn’t have any on hand.

Instead of purchasing $10,000 workstations to get the secondary machines, Animal Logic turned to NVIDIA Quadro Virtual Data Center Workstations (Quadro vDWS). This flexible, cost-effective offering allowed them to provide high-performance virtual machines for their artists and designers.

Quadro vDWS Delivers Workstation-Class Performance

Animal Logic began the project by setting up a server running NVIDIA Tesla M60 GPUs and NVIDIA Quadro vDWS software. After a few tests, the team saw that Quadro vDWS delivered powerful virtual machine performance on par with a physical machine.

Using the virtual workstation, it took creators just 4 seconds to open a Photoshop document, 7 seconds to save one, and 20 seconds to export a large file.

From running apps to streaming videos, GPU-powered virtual desktops provided the speed and flexible, high performance the team needed to execute projects smoothly — whether in Linux or Windows.

“Users were surprised at how efficient the virtual machines were when loading certain scenes,” said Matt Braunstein, systems engineer at Animal Logic. “Both Windows and Linux users found that they could rely on the NVIDIA vGPU performance when working with more intense applications such as ZBrush, Maya and XSI.”

NVIDIA Quadro vDWS allowed the IT team to set up two vGPU profiles: one for users who needed access to Microsoft Office and Photoshop, and a second profile for Linux users. Virtual machines were provided to about 50 staff members in the new studio.

The virtualized secondary machines made it easy for users to switch between environments, even while on the go. When traveling or working remotely, staffers could quickly access apps in Linux or Windows by simply logging in — with no need for a second physical machine.

To learn more about Animal Logic, see NVIDIA’s recent customer story.

Experience the Future of Digital Design at SIGGRAPH

See how other content creators and designers are using NVIDIA technology at the annual SIGGRAPH event in Los Angeles, taking place July 28 – Aug. 1. Stop by the NVIDIA booth to see demos of the latest advances and techniques, including RTX-powered ray tracing and rendering.

Check out our SIGGRAPH schedule for a list of talks.


Image courtesy of Warner Bros. Pictures – scene from The LEGO Movie 2: The Second Part.

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Bolshoi Theater Produces En Pointe Performances Using NVIDIA Technology

When it comes to theater productions, the devil is in the details.

Dancers, musicians and actors push themselves to the limit to deliver extraordinary performances. And behind the curtain, orchestra pit and tutus, multitudes of artists and technicians work on bringing art to life.

Much of their effort is defining the stage with set pieces, lighting, props and more. But before the curtain opens, production teams map it all out using digital 3D models. This process takes months and the collaboration of numerous teams.

To enhance the set design process, Moscow’s famed Bolshoi Theater developed an internal cloud service, based on NVIDIA Quadro Virtual Data Center Workstation (Quadro vDWS). This enables teams from multiple locations to work together on stage plans without meeting face to face.

The cloud service also allows the Bolshoi to deliver breathtaking performances when they are touring the globe. Every stage, lighting rig and theater set-up is unique to each location, so the set design needs to be adjusted accordingly. Thanks to the cloud, touring teams can work hand-in-hand with those based in Moscow and save valuable time.

Setting the Scene

As Act I begins, the first impression audiences get is shaped by the stage design. It sets the tone for the performance, creating multiple environments, sightlines, and entrance and exit points for the performers.

To get this right, the Bolshoi creates 3D models of the stage, using CAD applications. Designers and technicians use these to map lighting, props and block positions. They also can play with  configurations and adapt quickly to directorial changes.

“Plans can change at the very last moment,” said Roman Ulizko, the Bolshoi’s chief information officer. “That’s why it’s important for us to provide a flexible and reliable IT infrastructure to back up the creative process.”

Creating these models requires the collaboration of multiple expert teams. For the Bolshoi, they’re centered in Moscow, with support from teams across Russia. Previously, supervisors, carrying miniservers, had to travel between locations to coordinate these teams. Today, the internal cloud services eliminates the need for travel, providing access to the digital projects from any place, at any time.

“We work with multiple teams of experts, so we wanted them to be able to work collaboratively on projects from any location, at any time, with an excellent user experience,” said Ulizko. “NVIDIA Quadro Virtual Data Center Workstation technology lets us set up a single, flexible IT infrastructure with dynamic resource distribution.”

Based on a combination of NVIDIA P40 GPUs, Quadro vDWS software and VMware Horizon, the service supports 44 virtualized desktops for professional applications.

In the future, the team hopes to expand this number to up to 200 users, enabling even more efficient set design workflows.

From Stage to Silver Screen

Graphics virtualization isn’t the only NVIDIA technology that the Bolshoi has used.

Since 2011, the theater has broadcast ballet performances to movie theaters around the globe. To ensure these are of the highest quality, the Bolshoi uses NVIDIA-based hardware encoding to support the graphically intense streams.

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