Learn how to adopt and evolve OpenUSD for the world��s physical and industrial AI data pipelines and workflows.
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What is the interest in trillion-parameter models? We know many of the use cases today and interest is growing due to the promise of an increased capacity for: The benefits are? great, but training and deploying large models can be computationally expensive and resource-intensive. Computationally efficient, cost-effective, and energy-efficient systems, architected to deliver real-time��
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Custom schemas in Universal Scene Description, known as OpenUSD or USD, are pivotal for developers seeking to represent and encode sophisticated virtual worlds. By formalizing data models, schemas enable the interpretation of raw data by USD-compliant runtimes. Whether underpinning physics simulations or expanding digital twins, custom schemas provide the foundation for creativity, fidelity��
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Next-generation AI pipelines have shown incredible success in generating high-fidelity 3D models, ranging from reconstructions that produce a scene matching given images to generative AI pipelines that produce assets for interactive experiences. These generated 3D models are often extracted as standard triangle meshes. Mesh representations offer many benefits, including support in existing��
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NVIDIA will present 19 research papers at SIGGRAPH, the year��s most important computer graphics conference.
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Many companies are embracing digital twins to improve their products and services. Digital twins can be used for complex simulations of factories and warehouses or to understand how products will look and behave in the real world. However, many businesses don��t know how to begin making their existing 3D art assets valuable within a simulation environment. The existing universe of 3D assets is��
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NVIDIA PhysicsNeMo is now available on NVIDIA LaunchPad. Sign-up for a free, hands-on lab that will teach you how to develop physics-informed machine-learning solutions.
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X-ray-powered research is aiming to target sneaky hazardous materials making their way through airport security. The study, recently published in Scientific Reports, proposes a new design for a fast and powerful X-ray diffraction (XRD) technology able to identify potential threats. The work could be a notable step toward more accurate luggage scanning in airports. ��The main goal of my��
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The latest version of the NVIDIA PhysX 5 SDK is now available under the same open source license terms as NVIDIA PhysX 4 to help expand simulation workflows and applications across global industries. You can find this much-anticipated update on the NVIDIA-Omniverse/PhysX GitHub repository. A longtime GameWorks technology, PhysX has become the primary physics engine and a key foundational��
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Learn the basics of physics-informed deep learning and how to use NVIDIA PhysicsNeMo, the physics machine learning platform, in this self-paced online course.
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The latest version of NVIDIA PhysicsNeMo, an AI framework that enables users to create customizable training pipelines for digital twins, climate models, and physics-based modeling and simulation, is now available for download. This release of the physics-ML framework, NVIDIA PhysicsNeMo v22.09, includes key enhancements to increase composition flexibility for neural operator architectures��
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A dozen tools and programs��including new releases NeuralVDB and Kaolin Wisp��make 3D content creation easy and fast for millions of designers and creators.
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Accelerate your AI-based simulations using NVIDIA PhysicsNeMo. The 22.07 release brings advancements with weather modeling, novel network architectures, geometry modeling, and more��plus performance improvements.
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NVIDIA PhysicsNeMo is a physics-machine learning platform that blends the power of physics with data to build high-fidelity, parameterized AI surrogate models that serve as digital twins to simulate with near real-time latency. This cutting-edge framework is expanding its interactive simulation capabilities by integrating with the NVIDIA Omniverse (OV) platform for real-time virtual-world��
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When a technology reaches the required level of maturity, adoption transitions from those considered visionaries to early majority adopters. Now is such a critical and transitional moment for the largest single segment of industrial high-performance computing (HPC). The end of 2021 and beginning of 2022 saw the two largest commercial computational fluid dynamics (CFD) tool vendors��
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From physics-informed neural networks (PINNs) to neural operators, developers have long sought after the ability to build real-time digital twins with true-to-form rendering, robust visualizations, and synchronization with the physical system in the real world by streaming live sensor data. The latest release of PhysicsNeMo brings us closer to this reality. PhysicsNeMo 22.03��
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Climate change mitigation is about reducing greenhouse gas (GHG) emissions. The worldwide goal is to reach net zero, which means balancing the amount of GHG emissions produced and the amount removed from the atmosphere. On the one hand, this implies reducing emissions by using low-carbon technologies and energy efficiency. On the other hand, it implies deploying negative emission technologies��
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NVIDIA PhysicsNeMo was previously known as NVIDIA SimNet. Simulations have been widely used to model a variety of real-world problems in the science and engineering domains. Recent developments in AI and machine learning have led to the use of data to build surrogates for simulations, but the latest efforts have focused on the infusion of scientific laws in neural networks.
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NVIDIA PhysicsNeMo was previously known as NVIDIA SimNet. Simulations are pervasive in every domain of science and engineering, but they often have constraints such as large computational times, limited compute resources, tedious manual setup efforts, and the need for technical expertise. Neural networks not only accelerate simulations done by traditional solvers, but also simplify simulation��
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��Meet the Researcher�� is a series in which we spotlight different researchers in academia who use NVIDIA technologies to accelerate their work. This month we spotlight Dr. Emanuel Gull, Associate Professor of Physics at University of Michigan, whose research focuses on the development of theoretical and computational methods for strongly correlated quantum systems.
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NVIDIA PhysicsNeMo was previously known as NVIDIA SimNet. Simulations are pervasive in every domain of science and engineering, but they are often constrained by large computational times, limited compute resources, tedious manual setup efforts, and the need for technical expertise. NVIDIA PhysicsNeMo is a simulation toolkit that addresses these challenges with a combination of AI and physics.
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NVIDIA PhysicsNeMo was previously known as NVIDIA SimNet. Today, NVIDIA announces the release of PhysicsNeMo v21.06 for general availability, enabling physics simulations across a variety of use cases. NVIDIA PhysicsNeMo is a Physics-Informed Neural Networks (PINNs) toolkit for engineers, scientists, students, and researchers who either want to get started with AI-driven physics��
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Join the NVIDIA Triton and NVIDIA TensorRT community to stay current on the latest product updates, bug fixes, content, best practices, and more. High-energy physics research aims to understand the mysteries of the universe by describing the fundamental constituents of matter and the interactions between them. Diverse experiments exist on Earth to re-create the first instants of the universe.
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NVIDIA recently announced the release of PhysicsNeMo v20.12 with support for new physics such as fluid mechanics, linear elasticity and conductive as well as convective heat transfer. Systems governed by ordinary differential equations (ODEs) as well as partial differential equations (PDEs) can now be solved. Previously announced in September, NVIDIA PhysicsNeMo is a physics-informed neural��
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NVIDIA PhysicsNeMo was previously known as NVIDIA SimNet. NVIDIA PhysicsNeMo is a GPU-accelerated simulation toolkit based on physics-informed neural networks (PINNs). At SC19, we showed how PhysicsNeMo could interactively explore the pressure drop and temperature variations in different heatsink designs to quickly converge on an optimal design. Since then��
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Are you an experienced Minecraft content creator, but new to physically based materials? Or someone who just wants to learn the basics behind physically based rendering to create your own PBR resource packs? Great! This talk is for you. In ��Creating Physically Based Materials for Minecraft with RTX,�� we introduce you to the new look and possibilities that were launched with Minecraft using��
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NVIDIA PhysicsNeMo was previously known as NVIDIA SimNet. Today, NVIDIA announced the availability of NVIDIA PhysicsNeMo, a simulation toolkit intended to address the challenges of using AI and physics. Simulations are pervasive in every domain of science and engineering, but they��re constrained by long computational times, limited compute resources, tedious manual setup efforts��
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NVIDIA PhysicsNeMo was previously known as NVIDIA SimNet. A new demo introduces the recently announced NVIDIA PhysicsNeMo Toolkit, the first multiphysics (CFD and Heat Transfer) analysis using physics-informed neural networks (PINNs). Simulations form an integral part of product design to reduce significant iterations in physical prototyping and testing to improve quality��
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Driving is a part of everyday life. We know exactly how cars handle, so we are highly sensitive to the shortcomings of vehicle simulations in video games. The engineers behind NVIDIA PhysX 4.1 sought to address this by delivering a best-in-class vehicle simulation. They wound up building a solution that is so realistic, it��s now used as part of the foundation of NVIDIA��s self-driving car��
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Researchers from Google, Princeton, Columbia and MIT developed a picking robot using physics and deep learning that can accurately toss random objects into bins two times faster than previous systems. ��This robot, like many others, is designed to tolerate the dynamics of the unstructured world,�� mentioned Andy Zeng, Student Researcher of Robotics at Google. ��But instead of just tolerating��
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Participants in the Neural Information Processing Systems (NIPS) conference ��Learning to Run�� competition are vying for the chance to win an NVIDIA DGX Station, the fastest personal supercomputer for researchers and data scientists. Using Deep Reinforcement Learning and open-source tools, competitors are tasked to see who can develop a controller to enable a physiologically-based human model to��
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Phil Maechling, a computer scientist at USC��s Southern California Earthquake Center shares how they are using the Tesla GPU-accelerated Titan and Blue Waters supercomputers with CUDA to analyze the impact of earthquakes and why and when they occur. ��Instead of waiting for earthquakes to happen, we do physics-based simulations of ��scenario�� earthquakes,�� said Maechling. ��We use the results to��
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Shahab Fatemi, PhD Fellow at the University of California Berkeley Space Sciences Laboratory, shares how his team is using CUDA, TITAN X and Tesla K80 GPUs to develop a three-dimensional plasma model that can provide a better understanding of how solar wind could affect Earth. ��GPUs have been revolutionary in space and plasma physics modeling,�� said Fatemi. ��You can today��
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Russian scientists from Lomonosov Moscow State University used an ordinary GPU-accelerated desktop computer to solve complex quantum mechanics equations in just 15 minutes that would typically take two to three days on a large CPU-only supercomputer. Senior researchers Vladimir Pomerantcev and Olga Rubtsova and professor Vladimir Kukulin used a GeForce GTX 670 with CUDA and the PGI CUDA Fortran��
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In February 2016, scientists from the Laser Interferometry Gravitational-Wave Observatory (LIGO) announced the first ever observation of gravitational waves��ripples in the fabric of spacetime. This detection directly confirms for the first time the existence of gravitational radiation, a cornerstone prediction of Albert Einstein��s general theory of relativity. Furthermore, it suggests that black��
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Oak Ridge National Lab, NVIDIA and PGI launched the OpenACC Hackathon initiative last year to help scientists accelerate applications on GPUs. OpenACC was selected as a primary tool since it offers acceleration without significant programming effort and works great with existing application codes. University of Delaware (UDEL) hosted a five-day Hackathon last week. Selected teams of scientific��
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Scientists from University of Washington, Warsaw University of Technology in Poland, Pacific Northwest National Laboratory, and Los Alamos National Laboratory, have developed a model that provides a detailed look at what happens during the last stages of the fission process. According to their research paper, nuclear fission has almost reached the venerable age of 80 years and yet we still lack��
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James McClure, a Computational Scientist with Advanced Research Computing at Virginia Tech describes how they are using the NVIDIA Tesla GPU-accelerated Titan Supercomputer at Oak Ridge National Laboratory. Their project involves mathematical models combined with 3D visualization to provide insight on how fluids move below the surface of the earth. This can ultimately be used to extract oil or to��
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James McClure, a Computational Scientist with Advanced Research Computing at Virginia Tech shares how his group uses the NVIDIA Tesla GPU-accelerated Titan Supercomputer at Oak Ridge National Laboratory to combine mathematical models with 3D visualization to provide insight on how fluids move below the surface of the earth. McClure spoke with us about his research at the 2015 Supercomputing��
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A team of researchers from the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) research lab in Germany are using the Titan Supercomputer at Oak Ridge National Laboratory to advance laser-driven radiation treatment of cancerous tumors. Recently, doctors have been using beams of heavy particles, such as protons or ions, to treat cancer tumors. These beams can deposit most of their energy inside the��
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Stony Brook University researchers are exploring the physics of Type Ia supernovas using the Tesla-accelerated Titan Supercomputer at Oak Ridge National Laboratory. It��s been estimated that Type Ia supernovas can be used to calculate distances to within 10 percent accuracy, good enough to help scientists determine that the expansion of the universe is accelerating, a discovery that garnered��
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Mauro Calderara, PhD student at ETH Zurich and 2015 Gordon Bell Finalist talks about his GPU-accelerated work on ��Pushing Back the Limit of Ab-initio Quantum Transport Simulations on Hybrid Supercomputers.�� Share your GPU-accelerated science with us: http://nvda.ly/Vpjxr Watch more scientists and researchers share how accelerated computing is #thepathforward at http://nvda.ly/
]]>What is dark matter? We can neither see it nor detect it with any instrument. CERN is upgrading the LHC (Large Hadron Collider), which is the world��s largest and most powerful particle accelerator ever built, to explore the new high-energy frontier. The most technically challenging aspects of the upgrade cannot be done by CERN alone and requires collaboration and external expertise. There are 7��
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CERN is upgrading the LHC (Large Hadron Collider), which is the world��s largest and most powerful particle accelerator ever built, to explore the new high-energy frontier. A researcher describes how his team is working to increase the luminosity of beam dynamics with GPUs. The most technically challenging aspects of the upgrade cannot be done by CERN alone and require collaboration and external��
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This week��s Spotlight is on Valerie Halyo, assistant professor of physics at Princeton University. Researchers in the field of high energy physics, such as Valerie, are exploring the most fundamental questions about the nature of the universe, looking for the elementary particles that constitute matter and its interactions. One of Valerie��s goals is to extend the physics accessible at the��
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