NVIDIA’s (NASDAQ: NVDA) invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.
In 2006, the creation of the CUDA programming model and Tesla GPU platform opened up the parallel-processing capabilities of the GPU to general-purpose computing. A powerful new approach to computing was born.
NVIDIA Exerting Leadership in AI and Deep Learning
Deep Learning for Smart Cities: NVIDIA Metropolis is transforming the modern city.
Data is the lifeblood of the modern city. Today, it’s being captured by more than 500 million sensors worldwide, and that number is growing exponentially. Video represents one of the richest sensors used, generating massive streams of data that need analysis.
AI transforms how we capture, inspect, and analyze data to impact everything from traffic and parking management to law enforcement and city services. NVIDIA Metropolis is leading this AI revolution, giving you the tools, technologies, and expertise to meet every challenge with smarter, faster applications. It’s powered by proven NVIDIA technology—from NVIDIA® Tesla® in the data center and the cloud with NVIDIA Jetson™ at the edge.
The infographic below illustrates is also driving deeper insight in Intelligent Video Analytics (IVA).
Develop Smarter Solutions with NVIDIA DeepStream
The NVIDIA DeepStream SDK is ideal for developers who are creating and deploying AI-based solutions for video analytics applications at scale, offering a complete framework and all the essential building blocks. Applications of Intelligent Video Analytics (IVA) include understanding consumer behavior in retail, intelligent traffic systems, web content filtering, and ad injection.
DeepStream SDK offers the capability to gain rich insights through a heterogeneous concurrent neural network architecture. Developers can leverage multiple neural networks to process each video stream, giving them the flexibility to bring in different deep learning techniques to deliver more intelligent insights. DeepStream makes use of:
- NVIDIA® TensorRT™ and NVIDIA CUDA® for AI and other GPU computing tasks.
- Video CODEC SDK and multimedia APIs for accelerated encode and decode.
- Imaging APIs for capture and processing.
- Graph-based architecture and modular plug-ins to create configurable processing pipelines.
To learn more about the full extent of NVIDIA DeepStream capabilities, review this blog.
Healthcare: Improving Patient Care with AI
Artificial Intelligence is transforming the world of medicine. AI can help doctors make faster, more accurate diagnoses. It can predict the risk of a disease in time to prevent it. It can help researchers understand how genetic variations lead to disease.
Deep learning helps researchers analyze medical data and medical imaging. It’s advancing the future of personalized medicine. It even helps the blind “see.”
Three trends drive the deep learning revolution:
- More powerful GPUs.
- Sophisticated neural network algorithms modeled on the human brain.
- Access to the explosion of data from the Internet.
- Mining Medical Data for Better, Quicker Treatment. Using GPU-accelerated deep learning to process and study a patient’s condition over time and to compare one patient against a larger population could help doctors provide better treatments.
- Better, Faster Diagnoses. Medical images such as MRIs, CT scans, and X-rays are among the most important tools doctors use in diagnosing conditions ranging from spine injuries to heart disease to cancer. However, analyzing medical images can often be a difficult and time-consuming process.
- Genomics for Personalized Medicine. Genomics data is accumulating in unprecedented quantities, giving scientists the ability to study how genetic factors such as mutations lead to disease. Deep learning could one day lead to what’s known as personalized or “precision” medicine, with treatments tailored to a patient’s genomic makeup.
- Deep Learning to Aid Blind People. Nearly 300 million people worldwide struggle to manage such tasks as crossing the road, reading a product label, or identifying a face because they’re blind or visually impaired. Deep learning is beginning to change that.
Higher Education’s Impact on AI and Deep Learning
Partnerships with prestigious universities and research institutions around the globe are integral to NVIDIA and Advanced HPC. In fact, Advanced HPC customers include such global academic luminaries as Clemson University; Oregon State University; Stanford University; the University of Alabama; the University of California San Diego; and the University of Pennsylvania; among many others.
Numerous other partnerships with academia allow NVIDIA working in unison with Advanced HPC to collaborate with leading researchers as well as build connections with professors and research facilities that are working to solve complex scientific challenges.
Deep Learning Institute. AI is expected to generate two (2) million in net jobs gains versus losses by 2025, according to the analyst firm Gartner.
NVIDIA has reached tens of thousands of individuals seeking to extend their knowledge of AI into professional careers through the Deep Learning Institute (DLI). Offering free online courses and instructor-led workshops at conferences and onsite at businesses across the globe, the DLI provides remote and local access to education in deep learning and accelerated computing. DLI partnerships include an educator network that consists of experts from NVIDIA as well as the online educational providers Coursera and Udacity with its nanodegree programs.
Retail: AI from Supply Chain to Customer Sentiment
The landscape of traditional retail is experiencing a seismic shift. A rapidly evolving competitive environment, a global move towards digital shopping, and the ever-changing sentiments of highly informed buyers are forcing a new perspective in the industry. From this new perspective, we’re seeing the adoption of accelerated analytics, robotics, and deep learning.
The use of artificial intelligence in retail spans every aspect of the industry leading to the ever-increasing adoption of accelerated analytics, robotics, and deep learning. Whether your goal is to optimize your supply chain, use existing data to increase conversion, or customize shopping experiences with predictive modeling and micro-targeting/pricing, AI can help you meet your challenge.
Next-Gen Automation, Powered by Deep Learning
Today’s robots can learn, adapt, and evolve using capabilities like machine learning, computer vision, and navigation. NVIDIA® Jetson AGX™ systems uses the power of deep learning to drive this exciting new era of smart embedded robotics—from manufacturing and agriculture to security and home-based healthcare.
The AI Factory, Powered by NVIDIA
AI-enabled smart factories are changing the way manufacturing is done. AI computing powers industrial robots, big data analytics, and IIOT-managing, analyzing, and acting on tremendous amounts of data from a variety of sensors. With solutions like NVIDIA® Jetson® at the edge or near-edge and NVIDIA® Tesla® in the cloud, smart factories are increasing efficiency, improving quality, and reducing setup costs.
To see an illustration of the AI factory at work, review this infographic.
In June of 2018, NVIDIA launched NVIDIA® Isaac™, a new platform to power the next generation of autonomous machines, bringing artificial intelligence capabilities to robotics. Isaac SDK makes it easy to add AI into robots for perception, navigation and manipulation. It also provides a framework to manage communications and transfer data within the robot architecture. To learn more about the broad capabilities of Isaac, review this press release of its launch.
Part of the SDK is Isaac Sim, a simulation environment for developing, testing and training autonomous machines in the virtual world. Engineering iterations and testing can be done in minutes and because the system is completely virtual, there’s no risk of damage or injury. Isaac Sim is fully integrated with the Isaac SDK, which enables hardware-in-the-loop testing with NVIDIA Jetson AGX Xavier.
Artificial Intelligence (AI) gives cars the ability to see, think, learn and navigate a nearly infinite range of driving scenarios. NVIDIA uses the power of AI and deep learning to deliver a breakthrough end-to-end solution for autonomous driving — from data collection, model training, and testing in simulation to the deployment of smart, safe, self-driving cars.
The NVIDIA DRIVE™ platform can simultaneously process data from up to 16 sensors, constantly collecting vital data for building a robust training library for AI self-driving cars. Tapping into decades-long experience in AI, NVIDIA DRIVE hardware and software solutions deliver industry-leading performance to help automakers, truck makers, tier 1 suppliers, and startups make autonomous driving a reality.
NVIDIA DRIVE: Hardware
NVIDIA DRIVE AGX is a scalable, open autonomous vehicle computing platform that serves as the brain for autonomous vehicles. The only hardware platform of its kind, NVIDIA DRIVE AGX delivers high-performance, energy-efficient computing for functionally safe AI-powered self-driving.
NVIDIA DRIVE: Software
To augment and, eventually, replace the human driver, NVIDIA DRIVE software enables key self-driving functionalities such as sensor fusion and perception. The open, full-stack solution features libraries, toolkits, frameworks, source packages, and compilers for vehicle manufacturers and suppliers to develop applications for autonomous driving and user experience.
NVIDIA DRIVE: Simulation and Advanced Visualization with NVIDIA DRIVE Constellation™
NVIDIA DRIVE Constellation™ is a data center solution that integrates powerful GPUs and DRIVE AGX Pegasus™. Advanced visualization software running on GPUs simulate cameras, radar, and lidar as inputs to DRIVE AGX Pegasus, which processes the data as if it were actually driving on the road. This scalable system is capable of generating billions of miles of diverse autonomous vehicle testing scenarios to validate hardware- and software-in-the-loop prior to deployment.
DRIVE Constellation and DRIVE Sim are coupled to create a digital feedback loop. Driving commands from Pegasus are sent in real-time to control the virtual vehicle traveling in the simulated environment and validate that the algorithms and software are operating correctly.
Dedicated Application AI Products
NVIDIA Jetson AGX Systems: The AI solution for autonomous machines.
Secure real-time Artificial Intelligence (AI) performance where you need it most with the high-performance, low-power NVIDIA Jetson AGX systems. Processing of complex data can now be done on-board edge devices. This means you can count on fast, accurate inference in everything from robots and drones to enterprise collaboration devices and intelligent cameras.
- Jetson AGX Xavier. Jetson AGX Xavier is the world’s first computer expressly designed for robotics. With more than nine billion transistors, it delivers 32 deep learning TOPS (i.e., trillion operations per second). is the world’s leading platform for high-performance, energy-efficient AI computing. Robots need to be able to understand the world around them using a wide range of sensors. Jetson AGX Xavier enables this with six high-performance processing units—a 512-core NVIDIA Volta architecture Tensor Core GPU, an eight-core Carmel ARM64 CPU, a dual NVDLA deep learning accelerator, and image, vision, and video processors.
- Jetson TX2 Module. This is an AI supercomputer on a module, powered by NVIDIA Pascal™ architecture. Best of all, it packs this performance into a small, power-efficient form factor that’s ideal for intelligent edge devices like robots, drones, smart cameras, and portable medical devices. Supports all the features of the Jetson TX1 module while enabling bigger, more complex deep neural networks.
- Jetson TX1 Module. This AI supercomputer features NVIDIA Maxwell™ architecture, 256 NVIDIA CUDA® cores, 64-bit CPUs, and a power-efficient design. Includes the latest technology for deep learning, computer vision, GPU computing, and graphics—making it ideal for embedded AI computing.
More on NVIDIA and Autonomous Machines . . .
Autonomous machines learn, evolve, and react to the world around them with the power of AI. NVIDIA provides leading-edge solutions and support for a vast array of autonomous machines, including:
- Drones & UAVs. An advanced new breed of drones uses deep learning and smart cameras to do everything from taking inventory in warehouses to leading search and rescue operations. To learn more, visit: NVIDIA Jetson Solutions for Drones & UAVs.
- Industrial Robots. AI-powered industrial robots are ushering in a new era of automation, making factories safer and smarter and transforming manufacturing. To learn more, visit: NVIDIA Jetson AGX Systems for Robotics.
- Intelligent Video Analytics (IVA). Municipalities utilize IVA to transform surveillance data into actionable insights, improving all facets of city life–from retail to safety. To learn more, visit: NVIDIA Metropolis, The Foundation for Smart Cities.
NVIDIA GPU Cloud: GPU-Accelerated Innovation
NVIDIA GPU Cloud (NGC) provides researchers and data scientists with simple access to a comprehensive catalog of GPU-optimized software tools for deep learning and high performance computing (HPC) that take full advantage of NVIDIA GPUs. The NGC container registry features NVIDIA tuned, tested, certified, and maintained containers for the top deep learning frameworks. It also offers third-party managed HPC application containers, NVIDIA HPC visualization containers, and partner applications.
NGC empowers AI researchers with performance-engineered AI containers featuring deep learning software like TensorFlow, PyTorch, MXNet, NVIDIA TensorRT ™, and more. These pre-integrated, GPU-accelerated containers include NVIDIA® CUDA® Toolkit, NVIDIA deep learning libraries, and an operating system. They are tuned, tested, and certified by NVIDIA to run on select NVIDIA TITAN and NVIDIA Quadro® GPUs, NVIDIA DGX™ Systems, and supported public cloud providers. NGC containers are available to users of supported NVIDIA GPUs on Amazon EC2, Google Cloud Platform, Microsoft Azure, and Oracle Cloud Infrastructure. This lets users tackle challenges that were once thought to be impossible while eliminating difficult, time-consuming DIY software integration.
RAPIDS: NVIDIA GPU-Accelerated Data Science
Launched at GTC Europe (October, 2018), RAPIDS™ is a GPU-acceleration platform for data science and machine learning that enables even the largest companies to analyze massive amounts of data and make accurate business predictions at unprecedented speed. RAPIDS open-source software gives data scientists a giant performance boost as they address highly complex business challenges, such as predicting credit card fraud, forecasting retail inventory and understanding customer buying behavior.
To facilitate broad adoption, NVIDIA is integrating RAPIDS into Apache Spark, the leading open-source framework for analytics and data science. To obtain documentation and install information, click Rapids Documentation.
Data science pipeline with GPUs and RAPIDS.
Deep Learning AI and Inference
Inference Software and Accelerators for Cloud, Data Center, Edge, and Autonomous Machines
Demand for AI-enabled services such as image and speech recognition, natural language processing, visual search, and personalized recommendations continues to increase exponentially. At the same time, datasets are growing, networks are getting more complex, and latency requirements are tightening to meet user expectations.
The NVIDIA AI inference platform delivers the performance, efficiency, and responsiveness critical to powering the next generation of AI products and services — in the cloud, in the data center, at the network’s edge, and in vehicles.
- Unleash the Full Potential of NVIDIA GPUs with NVIDIA TensorRT. Using NVIDIA TensorRT, you can rapidly optimize, validate, and deploy trained neural networks for inference. TensorRT delivers up to 40X higher throughput in real-time latency when compared to CPU-only inference.
- Unified, End-to-End, Scalable Deep Learning Inference. With one unified architecture, neural networks on every deep learning framework can be trained, optimized with NVIDIA TensorRT, and then deployed for real-time inferencing at the edge. With NVIDIA DGX™ systems, NVIDIA Tesla®, NVIDIA Jetson™, and NVIDIA DRIVE™ PX, NVIDIA offers an end-to-end, fully scalable, deep learning platform.
- Cost Savings at a Massive Scale. A single NVIDIA Tesla P4 server can replace eleven commodity CPU servers for deep learning inference applications and services, reducing energy requirements and delivering cost savings of up to 80 percent.
High-level deep learning workflow showing training, then followed by inference.
NVIDIA and Advanced HPC deliver a wide spectrum of inference solutions for a multitude of applications and industries, including:
- Tesla supports all deep learning workloads and provides the optimal inference solution —combining the highest throughput, best efficiency, and best flexibility to power AI-driven experiences.
- TensorRT unlocks performance of Tesla GPUs across a variety of applications such as video-streaming, speech and recommender systems, while providing a foundation for the NVIDIA DeepStream SDK.
Self-Driving Cars: Autonomous driving demands safety, and that requires a high-performance AI computing solution that processes sensor data with the highest accuracy. The NVIDIA DRIVE™ Xavier and Pegasus platforms deliver proven inference solution for deep neural networks in real time.
- Deep learning-based perception, localization, and path planning enable the vehicle to understand its surroundings and operate safely.
- With support for every major framework, NVIDIA DRIVE continually grows smarter with over-the-air updates. Even after autonomous vehicles are in production, the platform accommodates new frameworks and models, enabling added capabilities and higher levels of autonomy.
Intelligent Video Analytics: A 2017 study released by LDV Capital projected that the total number of cameras in the world will reach nearly 45 billion. Those cameras are generating a massive amount of data every day. Deep learning is the best way to turn this raw video data into actionable insight, and GPU-based inference is the only way to do it in real time.
- End-to-End GPU Inference for Smart Cities: NVIDIA Metropolis uses the low power of NVIDIA® Jetson™ in cameras and appliances at the edge, the massive compute of NVIDIA Tesla® servers in the cloud, and the NVIDIA DeepStream SDK powered by NVIDIA TensorRT™ to deliver a complete IVA solution.
- AI for Embedded Devices: The NVIDIA Jetson platform offers the best throughput and performance per watt, the lowest latency, and the highest channel density, which translates into lower operating costs throughout a city’s network.
- Video Processing for Real-World Applications: One NVIDIA partner, Verizon, is attaching smart cameras powered by NVIDIA to street lights and other urban vantage points. Verizon’s video nodes leverage Jetson TX1 to collect and analyze data, enabling Verizon to track and classify objects such as vehicles, cyclists, and pedestrians, and identify interactions in real time.
Embedded Devices: From portable medical devices to automated delivery drones, intelligent edge solutions demand advanced inference to solve complex problems. These devices need inference performance in a low-power, small form factor—onboard. The NVIDIA® Jetson™ platform delivers this performance in the world’s fastest, most power-efficient supercomputer for inference at the edge.
- A Supercomputer on a Module for Autonomous Machines: NVIDIA Jetson TX2 is the latest addition to the industry-leading Jetson embedded platform. It’s based on NVIDIA’s Pascal architecture and is run at more than twice the power efficiency of its predecessor. This allows Jetson TX2 to run larger, deeper neural networks on edge devices; ensuring higher accuracy and faster response times for tasks like image classification, navigation, and speech recognition.
- Robust Tools for Building AI Applications: The Jetson platform for AI at the edge is powered by NVIDIA GPU and supported by the NVIDIA JetPack SDK. The JetPack SDK includes NVIDIA TensorRT™ for optimizing deep learning models for inference and other libraries for AI, computer vision, and multimedia to take your ideas to production.
- AI Across Industries: Jetson’s embeddable supercomputing capability gives developers the power to bring AI to applications that were once unimaginable. Blue River Technology, for example, is helping farmers grow more food with fewer chemicals. Blue River uses tractor-mounted, Jetson-powered smart cameras to identify crops and weeds in real time, and trigger precisely metered sprays that kill the weeds and nurture the lettuce.
Led by famed researcher Ian Buck, NVIDIA launched CUDA® – the world’s first solution for general-computing on GPUs – in 2006. CUDA is a parallel computing platform and programming model enabling developers to dramatically accelerate computing applications by harnessing the power of GPUs. When using CUDA, developers program in popular languages such as C, C++, Fortran, Python and MATLAB and express parallelism through extensions via basic keywords.
CUDA accelerates applications across a wide range of domains, including:
- Computational Chemistry
- Machine Learning
- Data Science & GPU-Accelerated Analytics
- Bioinformatics and Life Sciences
- Computational Fluid Dynamics
- Weather, Atmospheric, Ocean Modeling and Space Sciences
To learn more about CUDA application development, visit: CUDA Toolkit 10.0 Download.
Data Center Products and Solutions
Accelerating Data Center Workloads with GPUs
From scientific discoveries to artificial intelligence, modern data centers are key to solving some of the world’s most important challenges. The NVIDIA Volta accelerated computing platform gives these data centers the power to accelerate both artificial intelligence and high performance computing workloads.
Data Center Products
- NVIDIA® Tesla®
- NVIDIA HGX-2
- NVIDIA GPU Cloud
NVIDIA® Tesla®: The world’s leading platform for the accelerated data center
Accelerating scientific discovery, visualizing big data for insights, and providing smart AI-based services to the enterprise are everyday challenges for researchers and engineers. Solving these challenges takes increasingly complex and precise simulations, the processing of tremendous amounts of data, or training and running sophisticated deep learning networks. These workloads also require accelerating data centers to meet the growing demand for exponential computing.
NVIDIA® Tesla® is the world’s leading platform for the accelerated data center, deployed by the largest supercomputing centers and enterprises. It enables breakthrough performance with fewer, more powerful servers, resulting in faster scientific discoveries and insights while saving money.
NVIDIA Tesla is also the world’s fastest, most efficient data center platform for inference. Tesla provides the optimal inference solution—combining the highest throughput, best efficiency, and best flexibility to power AI-driven experiences.
With over 550 HPC applications GPU-optimized in a broad range of domains, including 15 of the top 15 HPC applications, and all deep learning frameworks, every modern data center can save money with the Tesla platform.
Given the increasingly broad spectrum of data center applications, NVIDIA has gone to great lengths to provide you with the data center products most appropriate for you. As such, the NVIDIA Tesla data center platform features products to account for virtually every data center need, including:
- NVIDIA Tesla V100 for NVIDIA® NVLink™
- NVIDIA Tesla V100 for PCIe
- NVIDIA Tesla P4
- NVIDIA Tesla P40
Tesla V100 GPU
At the 2018 GPU Technology Conference (GTC18), it was announced that the memory capacity of the NVIDIA® Tesla® V100 GPU – widely adopted by the world’s leading researchers – was doubled to handle the most memory-intensive deep learning and high performance computing workloads.
Now equipped with 32GB of memory, Tesla V100 GPUs will help data scientists train deeper and larger deep learning models that are more accurate than ever. They can also improve the performance of memory-constrained HPC applications by up to 50 percent compared with the previous 16GB version.
NVIDIA Tesla V100 for NVLink
NVIDIA Tesla V100 for PCIe
NVIDIA Tesla P4
The Tesla P4 is powered by the NVIDIA Pascal™ architecture and purpose-built to boost efficiency for scale-out servers running deep learning workloads, enabling smart responsive AI-based services. It reduces inference latency by 15X in any hyperscale infrastructure and provides a remarkable 60X better energy efficiency than traditional CPUs. This unlocks a new wave of AI services previous impossible due to latency limitations.
NVIDIA Tesla P40
The NVIDIA Tesla P40 is purpose-built to deliver maximum throughput for deep learning deployment. With 47 TOPS of inference performance and INT8 operations per GPU, a single server with 8 Tesla P40s delivers the performance of over 140 traditional CPU servers. As models increase in accuracy and complexity, CPUs are no longer capable of delivering interactive user experience. The Tesla P40 delivers over 30X lower latency than a CPU for real-time responsiveness in even the most complex models. Plus, the Tesla P40 offers great inference performance, INT8 precision and 24GB of onboard memory for an outstanding user experience.
The Accelerated Data Center: Boost Throughput While Lowering Costs
From autonomous vehicles to global climate simulations, new challenges are emerging that demand enormous computing resources to solve. NVIDIA HGX-2 is designed for multi-precision computing to provide a single flexible and powerful platform to solve these massive challenges.
The HGX-2 multi-precision computing platform allows high-precision calculations for scientific computing and simulations, while facilitating fast calculations for AI training and inference.
- Enables “The World’s Largest GPU.” Accelerated by 16 NVIDIA® Tesla® V100 GPUs and NVIDIA NVSwitch™, HGX-2 has the unprecedented compute power, bandwidth, and memory topology to train these models faster and more efficiently. The 16 Tesla V100 GPUs work as a single unified 2-petaFLOP accelerator with half a terabyte (TB) of total GPU memory, allowing it to handle the most computationally intensive workloads and enable “the world’s largest GPU.”
- Driving Next-Generation AI to Faster Performance. A single HGX-2 replaces 300 CPU-powered servers, saving significant cost, space, and energy in the data center.
- The Highest-Performing HPC Supernode. HPC applications require strong server nodes with the computing power to perform a massive number of calculations per second. Increasing the compute density of each node dramatically reduces the number of servers required, resulting in huge savings in cost, power, and space consumed in the data center.
- NVSwitch for Full Bandwidth Computing. NVSwitch enables every GPU to communicate with every other GPU at full bandwidth of 2.4TB/sec to solve the largest of AI and HPC problems. To learn more about HGX-2, download the NVIDIA HGX-2 Data Sheet.
NVIDIA GPU Cloud & GPU-Accelerated Software Containers
NVIDIA GPU Cloud provides easy access to a comprehensive catalog of GPU-accelerated containers, featuring NVIDIA tuned, tested, and certified deep learning framework containers. It also offers third-party managed HPC application containers, and NVIDIA HPC visualization containers.
Data Center Solutions: AI and Deep Learning.
- High Performance Computing. NVIDIA Tesla GPUs are the engine of the modern HPC data center, delivering breakthrough performance with fewer servers resulting in faster insights and dramatically lower costs. Over 550 HPC applications in a broad range of domains are optimized for GPUs, including all 15 of the top 15 HPC applications and every major deep learning framework.
- GPU Cloud Computing. Cloud computing has revolutionized every industry by democratizing the data center and completely changing the way businesses operate. However, to fully pull insight from that data they need the right HPC solution and NVIDIA is partnered with every major cloud service provider.
- GPU Virtualization. NVIDIA virtual GPU (vGPU) is the industry’s most advanced technology for sharing the power of NVIDIA GPUs across virtual machines (VMs) and virtual applications. NVIDIA virtual GPU software products include:
To learn more about NVIDIA GRID, download the NVIDIA GRID Data Sheet
- Analyze Faster. Accelerate data analysis, collection, clean-up, correlation, and modeling by 10-100X over traditional compute–now possible with NVIDIA GPU-accelerated databases.
- Visualize More Data. Interactive visualization solutions allow users to visualize 100X more data, using 40X less infrastructure with sub-second response and instant results for business validation.
- AI Accelerate. Deep learning, advanced machine learning algorithms, big data, and the computational power of GPUs delivers analytics knowledge with speed, scale, and accuracy.
Design & Pro Visualization
Architecture, Engineering & Construction. NVIDIA plays a key role in the architecture, engineering, and construction (AEC) industries. GPUs are now a part of everything from building design and digital construction rehearsals, to powering autonomous vehicles on construction sites and deep learning enabled on-site safety compliance monitoring.
- In addition to relying on NVIDIA® Quadro® professional GPUs for smooth design and visualization workflows, AEC firms use Quadro VR Ready GPUs for immersive virtual reality experiences. They are also rapidly adopting NVIDIA Quadro Virtual Data Center Workstation (Quadro vDWS) software for accelerated 3D graphics.
- As a world leader in Artificial Intelligence computing, NVIDIA is also powering advances in leading edge CAD technology like generative design software.
Education. With more schools employing online collaboration, digital lectures, and interactive digital content, technologies like 3D design software, virtual and augmented reality, and streamed applications are in high demand.
- NVIDIA professional visualization solutions are used by education and industry leaders around the world. NVIDIA solutions are manifest inf the classroom in workstations, laptops, and remotely from the data center.
- To broaden access and support new ways of learning with NVIDIA Virtual GPU Solutions, click on this informative brochure: Empowering Every Student in Education.
Manufacturing. From AI and virtual reality to physically based rendering, graphics virtualization, and real-time engineering simulation, traditional product development workflows are being disrupted — empowering manufacturers to radically improve how design teams collaborate and how products are designed and sold.
Leading-edge technologies can radically transform the product development process while reducing costs and speed time to market. Those technologies include:
- Virtual GPUs: NVIDIA virtual GPUs drive productivity, manageability, and security across manufacturing enterprises. To learn more about how NVIDIA Virtual GPU technology boosts collaboration, productivity and security, visit: NVIDIA Quadro Virtual Data Center Workstation Solutions.
- Virtual Reality: Virtual Reality is revolutionizing professional workflows with immersive product design experiences. To learn more, visit: NVIDIA Quadro VR.
- GPU Rendering: GPU accelerated physically based rendering helps designers and engineers predictably visualize products. To learn more, visit: Experience a New Era of Ray Tracing.
- Simulation: NVIDIA GPUs enhance a broad range of engineering simulation tools. To learn more visit: GPU Applications – Transforming computational research and engineering.
Media & Entertainment. NVIDIA technologies have powered the most advanced, visually-rich feature films ever created, from box office record-breakers to Academy Award-winning productions. Advancements in deep learning, simulation, rendering, and virtual production continue to propel the future of storytelling, reinventing how content is created, delivered, and consumed.
For 10 consecutive years through 2018, every film nominated for Best Visual Effects at the Academy Awards was created using NVIDIA Quadro GPUs. One of the latest on that long list is War for the Planet of the Apes; excerpt above. (Courtesy of Twentieth Century Fox.)
NVIDIA RTX & GeForce: Putting Gaming in an All New Light
NVIDIA® GeForce RTX™ delivers the ultimate gaming experience. Powered by the new NVIDIA Turing™ GPU architecture and the revolutionary RTX platform, RTX graphics cards fuse together real-time ray tracing, artificial intelligence, and programmable shading. In fact, GeForce RTX graphics cards are the first graphics cards built to deliver AI-enhanced gaming and real-time ray-tracing effects. Furthermore, they provide up to 6X faster ray-tracing performance than previous-generation Pascal-architecture cards.
“Games will never be the same,” said NVIDA CEO Jensen Huang. “Computer graphics has been reinvented.”
Real-Time Ray Tracing Realized
Ray tracing is the definitive solution for lifelike lighting, reflections, and shadows, offering a level of realism far beyond what is possible using traditional rendering techniques. Turing is the first GPU capable of rendering real-time ray tracing.
Simulating the path of a single light ray as it would be absorbed or reflected by various objects in the image, ray tracing is a technique for presenting three-dimensional (3D) images on a two-dimensional (2D) display by tracing a path of light through pixels on an image plane. In order to bring RTX to fruition, NVIDIA developed new graphical compute subsystems inside their GPUs called “RT Cores” which spur the ray tracing process.
Integrating the Power and Performance of Tensor Cores
To heighten the rendering quality of RTX, NVIDIA went one step better by integrating Tensor Cores – initially produced for deep learning – into the new RTX boards. The result is an accelerated, more efficient rendering process that leverages AI-fueled techniques like “denoising” and “inpainting.”
GeForce RTX graphics cards are also the world’s first graphics cards to feature GDDR6 memory, a new DisplayPort 1.4 output that can drive up to 8K HDR at 60Hz on future-generation monitors with a single cable, and a VirtualLink USB Type-C output for next-generation Virtual Reality headsets.
Programmable shaders defined modern graphics. Turing GPUs feature new advanced shading technologies that are more powerful, flexible, and efficient than ever before. Combined with GDDR6 —the world’s fastest memory — this performance lets customers experience games with maxed-out settings and exceptionally high frame rates.
Supported by the Biggest Names and Best Games
The NVIDIA RTX platform benefits from support in Microsoft’s new DirectX Raytracing (DXR) API as well as adoption by a rapidly growing list of premier video game titles.
The following select game titles will feature real-time ray tracing:
- Assetto Corsa Competizione; Kunos Simulazioni/505 Games
- Battlefield V; EA/DICE
- Justice; NetEase
- MechWarrior 5: Mercenaries; Piranha Games
- Shadow of the Tomb Raider; Square Enix/Eidos-Montréal/Crystal Dynamics/Nixxes
For a complete list, please see our related blog.
The following select game titles will utilize Deep Learning Super-Sampling (DLSS), a technology that applies deep learning and AI to rendering techniques:
For a complete list, please see our related blog.
GeForce RTX: New Family of Gaming GPUs
The new GeForce RTX 2080 Ti, 2080 and 2070 GPUs (SEE BELOW) showcase a long list of unprecedented gaming GPU features, including:
- New RT Cores to enable real-time ray tracing of objects and environments with physically accurate shadows, reflections, refractions and global illumination.
- Turing Tensor Cores to perform lightning-fast deep neural network processing.
- New NGX neural graphics framework to integrate AI into the overall graphics pipeline, enabling AI algorithms to perform unprecedented image enhancement and generation.
- New Turing shader architecture with Variable Rate Shading to enable shaders to focus processing power on areas of rich detail, boosting overall performance.
- New memory system featuring ultra-fast GDDR6 with over 600GB/s of memory bandwidth for high-speed, high-resolution gaming.
- NVIDIA NVLink®, a high-speed interconnect to provide higher bandwidth (up to 100 GB/s) and improved scalability for multi-GPU configurations (SLI).
- Hardware support for USB Type-C™ and VirtualLink™, a new open industry standard being developed to meet the power, display and bandwidth demands of next-generation
- VR headsets through a single USB-C™ connector.
- New and enhanced technologies to improve performance of VR applications, including Variable Rate Shading, Multi-View Rendering and VRWorks Audio.
GeForce RTX™ Product Line
GeForce RTX 2080 Ti
NVIDIA’s newest flagship graphics card is a revolution in gaming realism and performance. Its powerful NVIDIA Turing GPU architecture, breakthrough technologies, and 11 GB of next-gen, ultra-fast GDDR6 memory make it the world’s ultimate gaming GPU.
GeForce RTX 2080
The GeForce RTX 2080 is powered by the all-new NVIDIA Turing architecture to deliver altogether new levels of gaming realism, speed, power efficiency, and immersion.
GeForce RTX 2070
The powerful new GeForce RTX™ 2070 takes advantage of the cutting-edge NVIDIA Turing™ architecture to immerse game players in breakthrough levels of realism and performance.