Posts in category: nVidia AI

Rendering is a critical part of the design workflow. But as audiences and clients expect ever higher-quality graphics, agencies and studios must tap into the latest technology to keep up with rendering needs.

SuperBlimp, a creative production studio based just outside of London, knew there had to be a better way to achieve the highest levels of quality in the least amount of time. They’re leaving CPU rendering behind and moving to NVIDIA RTX GPUs, bringing significant acceleration to the rendering workflows for their unique productions.

After migrating to full GPU rendering, SuperBlimp experienced accelerated render times, making it easier to complete more iterations on their projects and develop creative visuals faster than before.

Blimping Ahead of Rendering With RTX

Because SuperBlimp is a small production studio, they needed the best performance at a low cost, so they turned to NVIDIA GeForce RTX 2080 Ti GPUs.

SuperBlimp had been using NVIDIA GPUs for the past few years, so they were already familiar with the power and performance of GPU acceleration. But they always had one foot in the CPU camp and needed to constantly switch between CPU and GPU rendering.

However, CPU render farms required too much storage space and took too much time. When SuperBlimp finally embraced full GPU rendering, they found RTX GPUs delivered the level of computing power they needed to create 3D graphics and animations on their laptops at a much quicker rate.

Powered by NVIDIA Turing, the most advanced GPU architecture for creators, RTX GPUs provide dedicated ray-tracing cores to help users speed up rendering performance and produce stunning visuals with photorealistic details.

And with NVIDIA Studio Drivers, the artists at SuperBlimp are achieving the best performance on their creative applications. NVIDIA Studio Drivers undergo extensive testing against multi-app creator workflows and multiple revisions of top creative applications, including Adobe Creative Cloud, Autodesk and more.

For one of their recent projects, an award-winning short film titled Playgrounds, SuperBlimp used Autodesk Maya for 3D modeling and Chaos Group’s V-Ray GPU software for rendering. V-Ray enabled the artists to create details that helped produce realistic surfaces, from metallic finishes to plastic materials.

“With NVIDIA GPUs, we saw render times reduce from 3 hours to 15 minutes. This puts us a great position to create compelling work,” said Antonio Milo, director at SuperBlimp. “GPU rendering opened the door for a tiny studio like us to design and produce even more eye-catching content than before.”

Now, SuperBlimp renders their projects using NVIDIA GeForce RTX 2080 Ti and GTX 1080 Ti GPUs to bring incredible speeds for rendering, so their artists can complete creative projects with the powerful, flexible and high-quality performance they need.

Learn how NVIDIA GPUs are powering the future of creativity.

A month after it got FDA approval, a startup’s first product was saving lives on the front lines of the battle against COVID-19.

Caption Health develops software for ultrasound systems, called Caption AI. It uses deep learning to empower medical professionals, including those without prior ultrasound experience, to perform echocardiograms quickly and accurately. 

The results are images of the heart often worthy of an expert sonographer that help doctors diagnose and treat critically ill patients.

The coronavirus pandemic provided plenty of opportunities to try out the first dozen systems. Two doctors who used the new tool shared their stories on the condition that their patients remain anonymous.

In March, a 53-year-old diabetic woman with COVID-19 went into cardiac shock in a New York hospital. Without the images from Caption AI, it would have been difficult to clinch the diagnosis, said a doctor on the scene.

The system helped the physician identify heart problems in an 86-year-old man with the virus in the same hospital, helping doctors bring him back to health. It was another case among more than 200 in the facility that was effectively turned into a COVID-19 hospital this spring.

The Caption Health system made a tremendous impact for a staff spread thin, said the doctor. It would have been hard for a trained sonographer to keep up with the demand for heart exams, he added.

Heart Test Becomes Standard Procedure

Caption AI helped doctors in North Carolina determine that a 62-year-old man had COVID-19-related heart damage. Thanks, in part, to the ease of using the system, the hospital now performs echocardiograms for most patients with the virus.

At the height of the pandemic’s first wave, the hospital stationed ultrasound systems with Caption AI in COVID-19 wards. Rather than sending sonographers from unit to unit, which is the usual practice, staff stationed at the wards used the systems. The change reduced staff exposure to the virus and conserved precious protective gear. 

Beyond the pandemic, the system will help hospitals provide urgent services while keeping a lid on rising costs, said a doctor at that hospital.

“AI-enabled machines will be the next big wave in taking care of patients wherever they are,” said Randy Martin, chief medical officer of Caption Health and emeritus professor of cardiology at Emory University, in Atlanta.

Martin joined the startup about four years ago after meeting its founders, who shared expertise and passion for medicine and AI. Today their software “takes a user through 10 standard views of the heart, coaching them through some 90 fine movements experts make,” he said.

“We don’t intend to replace sonographers; we’re just expanding the use of portable ultrasound systems to the periphery for more early detection,” he added.

Coping with Unexpected Demand Spike

In the early days of the pandemic, that expansion couldn’t come fast enough.

In late March, the startup exhausted supplies that included NVIDIA Quadro P3000 GPUs that ran its AI software. In the early days of the global shutdown, the startup reached out to its supply chain.

“We are experiencing overwhelming demand for our product,” the company’s CEO wrote, after placing orders for 100 GPUs with a distributor.

Caption Health has systems currently in use at 11 hospitals. It expects to deploy Caption AI at several additional sites in the coming weeks. 

GPUs at the Heart of Automated Heart Tests

The startup currently integrates its software in a portable ultrasound from Terason. It intends to partner with more ultrasound makers in the future. And it advises partners to embed GPUs in their future ultrasound equipment.

The Quadro P3000 in Caption AI runs real-time inference tasks using deep convolutional neural networks. They provide operators guidance in positioning a probe that captures images. Then they automatically choose the highest-quality heart images and interpret them to help doctors make informed decisions.

The NVIDIA GPU also freed up four CPU cores, making space to process other tasks on the system, such as providing a smooth user experience.

The startup trained its AI models on a database of 1 million echocardiograms from clinical partners. An early study in partnership with Northwestern Medicine and the Minneapolis Heart Institute showed Caption AI helped eight registered nurses with no prior ultrasound experience capture highly accurate images on a wide variety of patients.

Inception Program Gives Startup Momentum

Caption Heath, formerly called Bay Labs, was founded in 2015 in Brisbane, Calif. It received a $125,000 prize at a 2017 GTC competition for members of NVIDIA’s Inception program, which gives startups access to technology, expertise and markets.

“Being part of the Inception program has provided us with increased recognition in the field of deep learning, a platform to share our AI innovations with healthcare and deep learning communities, and phenomenal support getting NVIDIA GPUs into our supply chain so we could deliver Caption AI,” said Charles Cadieu, co-founder and president of Caption Health.

Now that its tool has been tested in a pandemic, Caption Health looks forward to opportunities to help save lives across many ailments. The company aims to ride a trend toward more portable systems that extend availability and lower costs of diagnostic imaging.

“We hope to see our technology used everywhere from big hospitals to rural villages to examine people for a wide range of medical conditions,” said Cadieu.

To learn more about Caption Health and other companies like it, watch this webinar on healthcare startups working against COVID-19.

For many organizations, the coronavirus pandemic has created a permanent shift in how their employees work. From now on, they’ll have the option to collaborate at home or in the office.

NVIDIA is giving these millions of professionals around the world a boost with a new version of our virtual GPU software, vGPU July 2020. The software adds support for more workloads and is loaded with features that improve operational efficiencies for IT administrators.

GPU virtualization is key to offering everyone from designers to data scientists a flexible way to collaborate on projects that require advanced graphics and computing power, wherever they are.

Employee productivity was the primary concern among organizations addressing remote work due to the COVID-19 pandemic, according to recent research by IDC. When the market intelligence firm interviewed NVIDIA customers using GPU-accelerated virtual desktops, it found organizations with 500-1,000 users experienced a 13 percent increase in productivity, resulting in approximately more than $1 million in annual savings.

According to Alex Herrera, an analyst with Jon Peddie Research/Cadalyst, “In a centralized computing environment with virtualized GPU technology, users no longer have to be tied to their physical workstations. As proven recently through remote work companies can turn on a dime, enabling anywhere/anytime access to big data without compromising on performance.”

Expanded Support in the Data Center and Cloud with SUSE

NVIDIA has expanded hypervisor support by partnering with SUSE on its Linux Enterprise Server, providing vGPU support on its kernel-based virtual machine platform.

Initial offerings will be supported with NVIDIA vComputeServer software, enabling GPU virtualization for AI and data science workloads. This will expand hypervisor platform options for enterprises and cloud service providers that are seeing an increased need to support GPUs.

“Demand for accelerated computing has grown beyond specialized HPC environments into virtualized data centers,” said Brent Schroeder, global chief technology officer at SUSE. “To ensure the needs of business leaders are met, SUSE and NVIDIA have worked to simplify the use of NVIDIA virtual GPUs in SUSE Linux Enterprise Server. These efforts modernize the IT infrastructure and accelerate AI and ML workloads to enhance high-performance and time-sensitive workloads for SUSE customers everywhere.”

Added Support for Immersive Collaboration

NVIDIA CloudXR technology uses NVIDIA RTX and vGPU software to deliver VR and augmented reality across 5G and Wi-Fi networks. vGPU July 2020 adds 120Hz VSync support at resolutions up to 4K, giving CloudXR users an even smoother immersive experience on untethered devices. It creates a level of fidelity that’s indistinguishable from native tethered configurations.

“Streaming AR/VR over Wi-Fi or 5G enables organizations to truly take advantage of its benefits, enabling immersive training, product design and architecture and construction,” said Matt Coppinger, director of AR/VR at VMware. “We’re partnering with NVIDIA to more securely deliver AR and VR applications running on VMware vSphere and NVIDIA Quadro Virtual Workstation, streamed using NVIDIA CloudXR to VMware’s Project VXR client application running on standalone headsets.”

The latest release of vGPU enables a better user experience and manageability needed for demanding workloads like the recently debuted Omniverse AEC Experience, which combines Omniverse, a real-time collaboration platform, with RTX Server and NVIDIA Quadro Virtual Workstation software for the data center. The reference design supports up to two virtual workstations on an NVIDIA Quadro RTX GPU, running multiple workloads such as collaborative, computer-aided design while also providing real-time photorealistic rendering of the model.

With Quadro vWS, an Omniverse-enabled virtual workstation can be provisioned in minutes to new users, anywhere in the world. Users don’t need specialized client hardware, just an internet-connected device, laptop or tablet, and data remains highly secured in the data center.

Improved Operational Efficiency for IT Administrators

New features in vGPU July 2020 help enterprise IT admins and cloud service providers streamline management, boosting their operational efficiency.

This includes cross-branch support, where the host and guest vGPU software can be on different versions, easing upgrades and large deployments.

IT admins can move quicker to the latest hypervisor versions to pick up fixes, security patches and new features, while staggering deployments for end-user images.

Enterprise data centers running VMware vSphere will see improved operational efficiency by having the ability to manage vGPU powered VMs with the latest release of VMware vRealize Operations.

As well, VMware recently added Distributed Resource Scheduler support for GPU-enabled VMs into vSphere. Now, vSphere 7 introduces a new feature called “Assignable Hardware,” which enhances initial placement so that a VM can be automatically “placed” on a host that has exactly the right GPU and  profile available before powering it on.

For IT managing large deployments, this means reducing deployment time of new VMs to a few minutes, as opposed to a manual process that can take hours. As well, this feature works with VMware’s vSphere High Availability, so if a host fails for any reason, a GPU-enabled VM can be automatically restarted on another host with the right GPU resources.

Availability

NVIDIA vGPU July 2020 release is coming soon. Learn more at nvidia.com/virtualization and watch this video.