DataBloomBill Dally — one of the world’s foremost computer scientists and head of NVIDIA’s research efforts — will deliver the keynote address during GTC China, the latest event in the world’s premier conference series focused on AI, deep learning and high performance computing. Registration is not required to view the keynote, which will take place Read article >
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AI is the largest technology force of our time, with the most potential to transform industries. It will bring new intelligence to healthcare, education, automotive, retail and finance, creating trillions of dollars in a new AI economy. As businesses look ahead to 2021 priorities, now’s a great time to look back at where the world Read article >
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What are the fundamental laws that govern our universe? How did the matter in the universe today get there? What exactly is dark matter? The questions may be eternal, but no human scientist has an eternity to answer them. Now, thanks to NVIDIA technology and cutting-edge AI, the more than 1,000 collaborators from 26 countries Read article >
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NVIDIA Research’s latest AI model is a prodigy among generative adversarial networks. Using a fraction of the study material needed by a typical GAN, it can learn skills as complex as emulating renowned painters and recreating images of cancer tissue. By applying a breakthrough neural network training technique to the popular NVIDIA StyleGAN2 model, NVIDIA Read article >
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Learn more about breakthrough NVIDIA technologies and dive into our expansive selection of graphics and simulation sessions.
Our GTC Fall 2020 virtual event featured a record breaking number of sessions, podcasts, demos, research posters, and more. We are now opening access to all the great content shared at the conference through the new NVIDIA On-Demand catalog. Learn more about breakthrough NVIDIA technologies and dive into our expansive selection of graphics and simulation sessions.
The launch of our new Ampere architecture was a long anticipated event of this year. Designed for the age of elastic computing, it delivers the next giant leap by providing unmatched acceleration at every scale, enabling these innovators to do their life’s work. Learn about the architecture and its benefits with these sessions:
NVIDIA Ampere for Professional Workflows: Learn about these new GPUs for professional visual computing and how they provide the power of the next generation of RTX from the desktop to the data center.
Rendering at the Speed of Light on NVIDIA Ampere GPUs: Explore hardware improvements over the previous generation, best practices for application developers, and tooling improvements that will help you write high-performance graphics code.
See more Ampere architecture talks >
Discover new pipelines and tools that are emerging in the graphics industry, and learn how professionals are using the newest technologies to enhance content creation.
Rendering Games With Millions of Ray-Traced Lights: Hear from NVIDIA experts to learn about the latest research in the area of many-light sampling, plus implications of many-light rendering on game content creation pipelines.
Bringing Ray-Traced Visualization to Collaborative Workflows: Omniverse XR: See how augmented reality is integrated within the Omniverse rendering pipeline, and how Omniverse AR is applied across a range of use cases. Plus, get an inside look at the different strategies created in Omniverse Kit to bring its ray tracing engine to virtual reality.
What’s New in Optix 7.2: Learn strategies to achieve optimal ray tracing performance with OptiX 7.2.
See more graphics and simulation talks >
Learn about the advanced tools that help create high-quality immersive environments, and see why virtual and augmented reality are one of the most anticipated forms of content to arrive over 5G networks.
AR and VR Graphics Technologies at NVIDIA: Get an overview of XR graphics technologies from NVIDIA, including our latest tools and SDKs.
Streaming XR Over 5G Changing the Way We Learn, Work, and Play: Explore current VR and AR hardware limitations, and see some of The Grid Factory’s achievements leveraging NVIDIA CloudXR and 5G.
Photorealistic Mixed-reality Solutions that Merge Virtual Content with Their Real-world Challenges: Learn how to create a new kind of immersive design, simulation, or training experience with the power of NVIDIA Quadro GPUs, Varjo virtual- and mixed-reality headsets, and Lenovo workstations.
See more XR talks >
From asset creation to RTX acceleration, check out the innovative techniques that are transforming the future of graphic workflows across all industries.
Virtual Production with Cine Tracer: Hear how live action cinematographer Matt Workman has created a previsualization and virtual production app for the film industry using Unreal Engine.
Unreal Engine + RTX from a Filmmaker’s Perspective: See how today’s real-time tools with RTX power can enable indie filmmakers to tell high-concept stories without huge budgets, resources, and a big rendering farm.
Real-Time and Production Ray Tracing with V-Ray: Learn about advances in real-time ray tracing and production rendering for V-Ray workflows, including RTX acceleration and the use of CUDA, DXR, and OptiX.
See more media and entertainment talks >
Now available to all NVIDIA Developers, NVIDIA On-Demand is a catalog of technical sessions, podcasts, past keynotes, demos, research posters and more from NVIDIA GPU Technology Conferences across the global, as well as leading industry events.
Now available to all NVIDIA developers, NVIDIA On-Demand is a catalog of technical sessions, podcasts, past keynotes, demos, research posters, and more from NVIDIA GPU Technology Conferences across the global, as well as leading industry events. This will enable developers to learn at their own time, at their own pace, anywhere.
Through NVIDIA On-Demand, developers can also create playlists of their favorite content, which they can share digitally.
To access NVIDIA On-Demand, log in to your developer account. If you’re not already a member of the NVIDIA Developer Program, join for free here. In addition to on-demand content, NVIDIA Developer Program members have access to all the tools and training needed to build on NVIDIA’s technology platforms.
Watch part 1 of our popular NVIDIA On-Demand session, Rendering Game With Millions of Ray Traced Lights, where NVIDIA’s Chris Wyman provides an overview on reservoir spatiotemporal importance resampling (ReSTIR).
In this video, NVIDIA’s Chris Wyman provides an overview on reservoir spatiotemporal importance resampling (ReSTIR). This algorithm makes it possible to effectively sample from millions of area lights with just a few rays per pixel and produce results that can be easily denoised.
He also explains why now is the right time for game developers to move on from traditional lighting techniques to real-time ray tracing. The incredible visuals on display in the Marbles at Night demo show what’s possible with real-time ray tracing today. “If there’s one thing you take from this talk, I hope it is that ray tracing enables new lighting that exceeds the limits imposed by rasterization,” says Wyman.
This is a segment from a two-part video available on NVIDIA On-Demand, entitled “Rendering Game With Millions of Ray Traced Lights”. We encourage you to check out the remainder of the talk, in which NVIDIA’s Alexey Panteleev describes light resampling in practice, and details the roadmap for RTXDI, our new direct illumination SDK.
To learn more about NVIDIA’s real-time ray tracing technologies, as well as other great tools and SDKs for game developers, please visit https://developer.nvidia.com/industries/gamedev.
Researchers, developers, and engineers from all over the world are gathering virtually this year for the 2020 Neural Information Processing Systems (NeurlPS). NVIDIA Research will present its research through spotlight and posters.
Researchers, developers, and engineers from all over the world are gathering virtually this year for the 2020 Neural Information Processing Systems (NeurlPS). NVIDIA Research will present its research through spotlight and posters.
NVIDIA’s accepted papers at this year’s online NeurIPS feature a range of groundbreaking research in the field of neural information processing systems.
From Tetrahedral Meshes for 3D Reconstruction, Deep Hierarchical Variational Autoencoders, to an AI training breakthrough using limited datasets.
At the conference NVIDIA announced the upcoming availability of the Omniverse Kaolin App that allows high fidelity rendering and interactive visualization of 3D data and training results.
Explore the work NVIDIA is bringing to the NeurIPS community. You can find the full event overview of NVIDIA’s activities here.
Data augmentation technique enables AI model to emulate artwork from a small dataset from the Metropolitan Museum of Art — and opens up new potential applications in fields like healthcare.
The CMake package and build system for both libraries continue to improve with add_subdirectory support, installation rules, status messages, and other features that make these libraries easier to use from CMake projects.
Thrust 1.11.0 is a major release providing bug fixes and performance enhancements. It includes a new sort algorithm that provides up to 2x more performance from thrust::sort when used with certain key types and hardware. The new thrust::shuffle algorithm has been tweaked to improve the randomness of the output.
CUB 1.11.0 is a major release providing bug fixes and performance enhancements. It includes a new DeviceRadixSort backend that improves performance by up to 2x on supported keys and hardware.
The CMake package and build system for both libraries continue to improve with add_subdirectory support, installation rules, status messages, and other features that make these libraries easier to use from CMake projects.
About Thrust and CUB
Thrust provides STL-like templated interfaces to several algorithms and data structures designed for high performance heterogeneous parallel computing. Thrust abstractions are agnostic of any particular parallel framework. CUB is a library of collective primitives and utilities. CUB is specific to CUDA C++ and its interfaces explicitly accommodate CUDA-specific features.
Thrust and CUB are complementary and are often used together.
Learn more: