NVIDIA Unveils Omniverse Blueprint for Real-Time Physics Digital Twins

How digital twins physics get faster and more connected

The NVIDIA Omniverse was initially conceived to share 3D models useful for exploring how things look. The company recently released the Omniverse Blueprint framework that speeds up physics simulations, integrates this data across tools, and visualizes the results. A key advance is various libraries that make it easier for simulation vendors to take advantage of GPUs, map these to faster physics-informed AI surrogate models, and exchange this data via new APIs. Early adopters include leading simulation vendors such as Altair, Ansys, Beyond Math, Cadence, Hexagon, Luminary Cloud, Neural Concept, Siemens, SimScale, and Trane Technologies. These vendors are seeing significant improvements in various types of simulation using the new approach. Ansys reports shrinking a complex automotive simulation from nearly a month to six hours. Cadence has reported a 40X speedup in semiconductor design, 1000X speedup in molecular simulation and 20X speedup in data center design simulation. I caught up with Juan Alonso, CTO & Co-founder of Luminary Cloud, which has pioneered new simulation techniques to take advantage of GPUs from the ground up. Diginomica previously covered their work last March, where he argued that legacy simulation vendors have traditionally grown by cobbling together point solutions that would be hard to refactor to take advantage of new GPU architectures and cloud infrastructure. Alonso said the biggest change was the new APIs, such as NVIDIA Modulus for physics-based AI/ML, which can be used as building blocks to generate more complex, GPU-optimized workflows. He also expects additional modules in the future to broaden the Omniverse ecosystem. Luminary was already a pioneer in GPU-accelerated engineering analysis for uploading geometry, generating meshes for simulation, and visualization. Alonso is excited about the new GPU-accelerated libraries that will make building faster simulation models for digital twins, optimization, and real-time design exploration easier. Also, engineers will be able to take advantage of cloud services using a laptop that allows all of the data to be accessible to anyone at a company. This will also improve collaboration and workflows requiring data sets composed of ensembles of simulations for surrogate modeling and design optimization. Alonso says: We argue that, without the cloud-native nature of the simulation platform, collecting, curating, and storing all the data is impossible or cumbersome...thus impeding the deployment of advanced workflows that engineers need to do their jobs in the current environment. Extending this collaboration and integration across multiple tools will require different vendors to adopt or support standards like USD for data representation and visualization. Alonso cautions that it's more complex than simply adding a USD translation tier since improving interoperability will also depend on the level of maturity of support for the new approaches. To the extent that vendors succeed, it will make it easier for developers to integrate capabilities from various vendors into workflows that impact automotive, aerospace, industrial processes, consumer goods, renewable energy, and medical device applications using similar building blocks. Alonso predicts: As NVIDIA and multiple vendors make their capabilities available via the Blueprint (using NVIDIA-supported standards), not only will vendors be able to instantiate more complex workflows (and customize them to the users' needs), but GPU acceleration in all stages of the engineering workflows will become pervasive. Such a potential future supports the Luminary vision for real-time engineering, giving users actionable information to improve their designs in an interactive fashion. For example, the appropriate interfaces will make it easier to support loosely coupled multi-physics applications for exploring changes across two physical domains, such as fluid and structure, radiation and convection, or airflow and acoustics. However, Alonso believes that more tightly coupled models will require vendors to refactor their existing tools to take advantage of GPU acceleration. These enhancements also could improve various aspects of product lifecycle management (PLM) across the enterprise. These recent improvements are an important step for creating more competent digital twins that keep different stakeholders and types of experts on the same page. In this context, Alonso thinks of a digital twin as a bespoke combination of simulation models and field/experimental data that can be used to create improved models of a particular engineering system under operation, such as a jet engine on the wing of a plane. Alonso believes that the biggest bottleneck is the inability of most companies to appropriately collect, curate, and store the field/experimental data with all the associated metadata so that it can easily be incorporated into the digital twin workflow. Cloud native environments could help improve the technical infrastructure to generate, store, and curate the simulation data and combine it with the field data. He explains: The only work that needs to be done is to create the ability to ingest and store field/experimental data ... so that it can then be used to train and improve the training of existing models for a particular engineering system that would have normally been based on simulation data alone. In the short run, NVIDIA's new updates are an important step in applying physics simulations to develop more efficient, performant, and cost-effective products and physical infrastructure. Down the road, it will also simplify the development of new AI techniques, like active inference, that consider how a system interacts with the world rather than just the words people have written about the world, as with large language models. However, innovations on both fronts will face numerous challenges. For starters, legacy vendors may benefit from limiting integration that allows customers to mix and match tools from competitors with their own. Digital twin pioneers Dr. Michael Grieve and John Vickers have also argued that enterprises will need to overcome cultural barriers to integrate workflows across various teams. Enterprises will also need to improve their data management practices to take advantage of these innovations more broadly.

Nvidia unveils Omniverse real-time physics digital twins

Nvidia announced its Nvidia Omniverse Blueprint, a technology that enables industry software developers to build digital twins with realistic real-time physics. It enables computer-aided engineering (CAE) customers in aerospace, automotive, manufacturing, energy and other industries create digital twins with real-time interactivity. One example of that is the virtual wind tunnel that car designers can use to simulate wind moving over a simulated car. Nvidia made the announcements at the SC24 supercomputer event. Software developers such as Altair, Ansys, Cadence and Siemens can use the reference workflow, which includes Nvidia acceleration libraries, physics-AI frameworks and interactive physically based rendering, to achieve 1,200x faster simulations and real-time visualization. This helps their customers drive down development costs and energy usage while getting to market faster. "We built Omniverse so that everything can have a digital twin," said Jensen Huang, CEO of Nvidia, in a statement. "Omniverse Blueprints are reference pipelines that connect NVIDIA Omniverse with AI technologies, enabling leading CAE software developers to build groundbreaking digital twin workflows that will transform industrial digitalization, from design and manufacturing to operations, for the world's largest industries." One of the first applications of the blueprint is computational fluid dynamics (CFD) simulations, a critical step to virtually explore, test and refine the designs of cars, airplanes, ships and many other products. Traditional engineering workflows -- from physics simulation to visualization and design optimization -- can take weeks or even months to complete. In an industry first, Nvidia and Luminary Cloud are demonstrating at SC24 a virtual wind tunnel that allows users to simulate and visualize fluid dynamics at real-time, interactive speeds, even when changing the vehicle model inside the tunnel. Unifying three pillars of Nvidia dev tech Building a real-time physics digital twin requires two fundamental capabilities: real time physics solver performance and real-time visualization of large-scale datasets. The Omniverse Blueprint achieves these by bringing together Nvidia CUDA-X libraries to accelerate the solvers, the Nvidia Modulus physics-AI framework to train and deploy models to generate flow fields, and Nvidia Omniverse application programming interfaces for 3D data interoperability and real-time RTX-enabled visualization. Developers can integrate the blueprint as individual elements or in its entirety into their existing tools. Ansys is the first customer to adopt the Omniverse Blueprint, applying it to Ansys Fluent fluid simulation software to enable accelerated computational fluid dynamics simulation. Ansys ran Fluent at the Texas Advanced Computing Center on 320 Nvidia GH200 Grace Hopper superchips. A 2.5-billion-cell automotive simulation was completed in just over six hours. That would have taken nearly a month running on 2,048 x86 CPU cores, significantly enhancing the feasibility of overnight high-fidelity CFD analyses and establishing a new industry benchmark. "By integrating NVIDIA Omniverse Blueprint with Ansys software, we're enabling our customers to tackle increasingly complex and detailed simulations more quickly and accurately," said Ajei Gopal, CEO of Ansys, in a statement. "Our collaboration is pushing the boundaries of engineering and design across multiple industries." Luminary Cloud is also adopting the blueprint. The company's new simulation AI model, built on Nvidia Modulus, learned the relationships between airflow fields and car geometry based on training data generated from its GPU-accelerated CFD solver. The model runs simulations orders of magnitude faster than the solver itself, enabling real-time aerodynamic flow simulation that is visualized using Omniverse APIs. Altair, Beyond Math, Cadence, Hexagon, Neural Concept, Siemens, SimScale and Trane Technologies are also exploring adoption of the Omniverse Blueprint into their own applications. The Omniverse Blueprint can be run on all leading cloud platforms, including Amazon Web Services, Google Cloud and Microsoft Azure. It is also available on Nvidia DGX Cloud. Rescale, a cloud-based platform that helps organizations accelerate scientific and engineering breakthroughs, is using the Nvidia Omniverse Blueprint to enable organizations to train and deploy custom AI models in just a few clicks. The Rescale platform automates the full application-to-hardware stack and can be run across any cloud service provider. Organizations can generate training data using any simulation solver; prepare, train and deploy the AI models; run inference predictions; and visualize and optimize models. Companies interested in learning more about the Nvidia Omniverse Blueprint for real-time computer-aided engineering digital twins can sign up for early access.

Nvidia unveils the next generation of digital twins with real-time data updates

Nvidia has lifted the wraps off its new Omniverse Blueprint tool - a digital twin software to support computer-aided engineering in industries like manufacturing, aerospace, automotive and energy. The chipmaker hopes its blueprint tool will enable developers to create simulations faster, therefore reducing their energy consumption and helping them to hit sustainability goals. Omniverse Blueprint's efficiency also promises to accelerate product development cycles, allowing companies to react to trends more quickly and stay ahead of the curve and competition. In an announcement, the company said Blueprint uses Nvidia CUDA-X acceleration libraries, Nvidia Modulus physics-AI framework and Nvidia Omniverse application programming interfaces for 3D data interoperability and real-time RTX-enabled visualization to achieve 1,200x faster simulations and real-time visualization. "Omniverse Blueprints are reference pipelines that connect NVIDIA Omniverse with AI technologies, enabling leading CAE software developers to build groundbreaking digital twin workflows that will transform industrial digitalization, from design and manufacturing to operations, for the world's largest industries," noted Nvidia CEO Jensen Huang. One of Omniverse Blueprint's first applications is computational fluid dynamics (CFD), an important step for refining vehicle, ship and airplane designs that previously tool weeks or even months to complete. Altair, Beyond Math, Cadence, Hexagon, Neural Concept, Siemens, SimScale and Trane Technologies are also said to be exploring how they can adopt the technology, too.

NVIDIA Announces Omniverse Real-Time Physics Digital Twins With Industry Software Leaders - NVIDIA (NASDAQ:NVDA)

ATLANTA, Nov. 18, 2024 (GLOBE NEWSWIRE) -- SC24 -- NVIDIA today announced an NVIDIA Omniverse™ Blueprint that enables industry software developers to help their computer-aided engineering (CAE) customers in aerospace, automotive, manufacturing, energy and other industries create digital twins with real-time interactivity. Software developers such as Altair, Ansys, Cadence and Siemens can use the NVIDIA Omniverse Blueprint for real-time computer-aided engineering digital twins to help their customers drive down development costs and energy usage while getting to market faster. The blueprint is a reference workflow that includes NVIDIA acceleration libraries, physics-AI frameworks and interactive physically based rendering to achieve 1,200x faster simulations and real-time visualization. "We built Omniverse so that everything can have a digital twin," said Jensen Huang, founder and CEO of NVIDIA. "Omniverse Blueprints are reference pipelines that connect NVIDIA Omniverse with AI technologies, enabling leading CAE software developers to build groundbreaking digital twin workflows that will transform industrial digitalization, from design and manufacturing to operations, for the world's largest industries." One of the first applications of the blueprint is computational fluid dynamics (CFD) simulations, a critical step to virtually explore, test and refine the designs of cars, airplanes, ships and many other products. Traditional engineering workflows -- from physics simulation to visualization and design optimization -- can take weeks or even months to complete. In an industry first, NVIDIA and Luminary Cloud are demonstrating at SC24 a virtual wind tunnel that allows users to simulate and visualize fluid dynamics at real-time, interactive speeds, even when changing the vehicle model inside the tunnel. Unifying Three Pillars of NVIDIA Technology for Developers Building a real-time physics digital twin requires two fundamental capabilities: real-time physics solver performance and real-time visualization of large-scale datasets. The Omniverse Blueprint achieves these by bringing together NVIDIA CUDA-X™ libraries to accelerate the solvers, the NVIDIA Modulus physics-AI framework to train and deploy models to generate flow fields, and NVIDIA Omniverse application programming interfaces for 3D data interoperability and real-time RTX-enabled visualization. Developers can integrate the blueprint as individual elements or in its entirety into their existing tools. Ecosystem Uses NVIDIA Blueprint to Advance Simulations Ansys is the first to adopt the Omniverse Blueprint, applying it to Ansys Fluent fluid simulation software to enable accelerated CFD simulation. Ansys ran Fluent at the Texas Advanced Computing Center on 320 NVIDIA GH200 Grace Hopper Superchips. A 2.5-billion-cell automotive simulation was completed in just over six hours, which would have taken nearly a month running on 2,048 x86 CPU cores, significantly enhancing the feasibility of overnight high-fidelity CFD analyses and establishing a new industry benchmark. "By integrating NVIDIA Omniverse Blueprint with Ansys software, we're enabling our customers to tackle increasingly complex and detailed simulations more quickly and accurately," said Ajei Gopal, president and CEO of Ansys. "Our collaboration is pushing the boundaries of engineering and design across multiple industries." Luminary Cloud is also adopting the blueprint. The company's new simulation AI model, built on NVIDIA Modulus, learned the relationships between airflow fields and car geometry based on training data generated from its GPU-accelerated CFD solver. The model runs simulations orders of magnitude faster than the solver itself, enabling real-time aerodynamic flow simulation that is visualized using Omniverse APIs. Altair, Beyond Math, Cadence, Hexagon, Neural Concept, Siemens, SimScale and Trane Technologies are also exploring adoption of the Omniverse Blueprint into their own applications. The Omniverse Blueprint can be run on all leading cloud platforms, including Amazon Web Services, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure. It is also available on NVIDIA DGX™ Cloud. Rescale, a cloud-based platform that helps organizations accelerate scientific and engineering breakthroughs, is using the NVIDIA Omniverse Blueprint to enable organizations to train and deploy custom AI models in just a few clicks. The Rescale platform automates the full application-to-hardware stack and can be run across any cloud service provider. Organizations can generate training data using any simulation solver; prepare, train and deploy the AI models; run inference predictions; and visualize and optimize models. Availability Companies interested in learning more about the NVIDIA Omniverse Blueprint for real-time computer-aided engineering digital twins can sign up for early access. About NVIDIA NVIDIA NVDA is the world leader in accelerated computing. For further information, contact: Kristin Uchiyama NVIDIA Corporation +1-408-313-0448 kuchiyama@nvidia.com Certain statements in this press release including, but not limited to, statements as to: the benefits, impact, and performance of NVIDIA's products, services, and technologies, including NVIDIA Omniverse Blueprint, NVIDIA CUDA-X libraries, NVIDIA Modulus physics-AI framework, NVIDIA NIM microservice, NVIDIA GH200 Grace Hopper Superchip, and NVIDIA DGX Cloud; NVIDIA's collaborations with third parties and the benefits and impact thereof; third parties using or adopting our products and technologies, the benefits and impact thereof, and the features and performance of their offerings; and Omniverse Blueprints enabling leading CAE software developers to build groundbreaking digital twin workflows that will transform industrial digitalization, from design and manufacturing to operations, for the world's largest industries are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners' products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company's website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances. Many of the products and features described herein remain in various stages and will be offered on a when-and-if-available basis. The statements above are not intended to be, and should not be interpreted as a commitment, promise, or legal obligation, and the development, release, and timing of any features or functionalities described for our products is subject to change and remains at the sole discretion of NVIDIA. NVIDIA will have no liability for failure to deliver or delay in the delivery of any of the products, features or functions set forth herein. © 2024 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, CUDA-X, NVIDIA DGX, and NVIDIA Omniverse are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and/or other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability, and specifications are subject to change without notice. A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/ad7e8173-9e60-4c08-a76d-e9fe246ae146 Market News and Data brought to you by Benzinga APIs

NVIDIA Announces Omniverse Real-Time Physics Digital Twins With Industry Software Leaders

, (GLOBE NEWSWIRE) -- SC24 -- NVIDIA today announced an Omniverse™ Blueprint that enables industry software developers to help their computer-aided engineering (CAE) customers in aerospace, automotive, manufacturing, energy and other industries create digital twins with real-time interactivity. Software developers such as Altair, Ansys, Cadence and Siemens can use the Omniverse Blueprint for real-time computer-aided engineering digital twins to help their customers drive down development costs and energy usage while getting to market faster. The blueprint is a reference workflow that includes acceleration libraries, physics-AI frameworks and interactive physically based rendering to achieve 1,200x faster simulations and real-time visualization. "We built Omniverse so that everything can have a digital twin," said , founder and CEO of . "Omniverse Blueprints are reference pipelines that connect Omniverse with AI technologies, enabling leading CAE software developers to build groundbreaking digital twin workflows that will transform industrial digitalization, from design and manufacturing to operations, for the world's largest industries." One of the first applications of the blueprint is computational fluid dynamics (CFD) simulations, a critical step to virtually explore, test and refine the designs of cars, airplanes, ships and many other products. Traditional engineering workflows -- from physics simulation to visualization and design optimization -- can take weeks or even months to complete. In an industry first, and Luminary Cloud are demonstrating at SC24 a virtual wind tunnel that allows users to simulate and visualize fluid dynamics at real-time, interactive speeds, even when changing the vehicle model inside the tunnel. Unifying Three Pillars of Technology for Developers Building a real-time physics digital twin requires two fundamental capabilities: real-time physics solver performance and real-time visualization of large-scale datasets. The Omniverse Blueprint achieves these by bringing together CUDA-X™ libraries to accelerate the solvers, the Modulus physics-AI framework to train and deploy models to generate flow fields, and Omniverse application programming interfaces for 3D data interoperability and real-time RTX-enabled visualization. Developers can integrate the blueprint as individual elements or in its entirety into their existing tools. Ecosystem Uses Blueprint to Advance Simulations Ansys is the first to adopt the Omniverse Blueprint, applying it to Ansys Fluent fluid simulation software to enable accelerated CFD simulation. Ansys ran Fluent at the Texas Advanced Computing Center on 320 GH200 Grace Hopper Superchips. A 2.5-billion-cell automotive simulation was completed in just over six hours, which would have taken nearly a month running on 2,048 x86 CPU cores, significantly enhancing the feasibility of overnight high-fidelity CFD analyses and establishing a new industry benchmark. "By integrating Omniverse Blueprint with Ansys software, we're enabling our customers to tackle increasingly complex and detailed simulations more quickly and accurately," said , president and CEO of Ansys. "Our collaboration is pushing the boundaries of engineering and design across multiple industries." Luminary Cloud is also adopting the blueprint. The company's new simulation AI model, built on Modulus, learned the relationships between airflow fields and car geometry based on training data generated from its GPU-accelerated CFD solver. The model runs simulations orders of magnitude faster than the solver itself, enabling real-time aerodynamic flow simulation that is visualized using Omniverse APIs. Altair, Beyond Math, Cadence, Hexagon, Neural Concept, Siemens, SimScale and Trane Technologies are also exploring adoption of the Omniverse Blueprint into their own applications. The Omniverse Blueprint can be run on all leading cloud platforms, including , Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure. It is also available on DGX™ Cloud. Rescale, a cloud-based platform that helps organizations accelerate scientific and engineering breakthroughs, is using the Omniverse Blueprint to enable organizations to train and deploy custom AI models in just a few clicks. The Rescale platform automates the full application-to-hardware stack and can be run across any cloud service provider. Organizations can generate training data using any simulation solver; prepare, train and deploy the AI models; run inference predictions; and visualize and optimize models. Availability Companies interested in learning more about the Omniverse Blueprint for real-time computer-aided engineering digital twins can sign up for early access. Certain statements in this press release including, but not limited to, statements as to: the benefits, impact, and performance of NVIDIA's products, services, and technologies, including Omniverse Blueprint, CUDA-X libraries, Modulus physics-AI framework, NIM microservice, GH200 Grace Hopper Superchip, and DGX Cloud; NVIDIA's collaborations with third parties and the benefits and impact thereof; third parties using or adopting our products and technologies, the benefits and impact thereof, and the features and performance of their offerings; and Omniverse Blueprints enabling leading CAE software developers to build groundbreaking digital twin workflows that will transform industrial digitalization, from design and manufacturing to operations, for the world's largest industries are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners' products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports files with the , or , including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the are posted on the company's website and are available from without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, disclaims any obligation to update these forward-looking statements to reflect future events or circumstances. Many of the products and features described herein remain in various stages and will be offered on a when-and-if-available basis. The statements above are not intended to be, and should not be interpreted as a commitment, promise, or legal obligation, and the development, release, and timing of any features or functionalities described for our products is subject to change and remains at the sole discretion of . will have no liability for failure to deliver or delay in the delivery of any of the products, features or functions set forth herein. © 2024 . All rights reserved. , the logo, CUDA-X, DGX, and Omniverse are trademarks and/or registered trademarks of in the and/or other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability, and specifications are subject to change without notice. A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/ad7e8173-9e60-4c08-a76d-e9fe246ae146

NVIDIA introduces real-time CAE digital twin blueprint By Investing.com

ATLANTA - NVIDIA Corporation (NASDAQ: NASDAQ:NVDA) has unveiled a new blueprint for real-time computer-aided engineering (CAE (NYSE:CAE)) digital twins, aimed at aiding developers in various industries such as aerospace, automotive, manufacturing, and energy. The NVIDIA Omniverse™ Blueprint is designed to help software developers, including Altair, Ansys (NASDAQ:ANSS), Cadence, and Siemens (ETR:SIEGn), to enable their customers to reduce development costs, lower energy usage, and accelerate market entry. The blueprint provides a reference workflow that incorporates NVIDIA's acceleration libraries, physics-AI frameworks, and interactive physically based rendering, which can result in simulations that are up to 1,200 times faster and offer real-time visualization. NVIDIA's CEO, Jensen Huang, emphasized that the Omniverse Blueprints are intended to connect NVIDIA Omniverse with AI technologies, allowing CAE software developers to create advanced digital twin workflows. One of the first uses of the blueprint is for computational fluid dynamics (CFD) simulations, which are essential for virtually testing and refining designs in various products. NVIDIA, in collaboration with Luminary Cloud, showcased at SC24 a virtual wind tunnel that enables real-time simulation and visualization of fluid dynamics, even when altering the vehicle model inside the tunnel. The Omniverse Blueprint combines NVIDIA CUDA-X™ libraries, the NVIDIA Modulus physics-AI framework, and NVIDIA Omniverse application programming interfaces to deliver both real-time physics solver performance and visualization of large-scale datasets. Developers have the flexibility to integrate the blueprint either in parts or as a whole into their existing tools. Ansys is the first company to adopt the Omniverse Blueprint, applying it to their Ansys Fluent (NASDAQ:FLNT) fluid simulation software. This integration has allowed Ansys to complete a 2.5-billion-cell automotive simulation in just over six hours using 320 NVIDIA GH200 Grace Hopper Superchips, a task that previously would have taken nearly a month on traditional CPU cores. This breakthrough has the potential to make high-fidelity CFD analyses more feasible on an overnight basis. Other companies like Altair, Beyond Math, Cadence, Hexagon, Neural Concept, Siemens, SimScale, and Trane Technologies (NYSE:TT) are also considering the adoption of the Omniverse Blueprint. The blueprint is compatible with major cloud platforms, including Amazon (NASDAQ:AMZN) Web Services, Google (NASDAQ:GOOGL) Cloud, Microsoft (NASDAQ:MSFT) Azure, and Oracle (NYSE:ORCL) Cloud Infrastructure, and is available on NVIDIA DGX™ Cloud. Additionally, Rescale is utilizing the NVIDIA Omniverse Blueprint on its cloud-based platform to streamline the process for organizations to train and deploy custom AI models. For companies interested in exploring the NVIDIA Omniverse Blueprint for real-time CAE digital twins, early access sign-up is available. This announcement is based on a press release statement from NVIDIA. In other recent news, NVIDIA has been the subject of significant attention from various analyst firms. Bank of America (NYSE:BAC) reiterated a positive outlook on NVIDIA's shares, despite concerns surrounding the high power consumption of certain configurations of the company's next-generation Blackwell platform. The firm remains optimistic about NVIDIA's solid positioning for the calendar year 2025. Rosenblatt Securities, Morgan Stanley (NYSE:MS), and Evercore ISI have all maintained positive stances on NVIDIA, with Rosenblatt setting a price target of $200 and expecting a positive earnings report. The sell-side consensus projects NVIDIA's FQ3 and FQ4 sales to reach $33.2 billion and $37 billion, respectively, with more optimistic investor expectations set higher. HSBC (LON:HSBA) forecasts NVIDIA's third-quarter sales to reach $35.3 billion, surpassing both management's guidance and consensus estimates. The firm's sales forecasts for the fourth quarter of fiscal year 2025 and the first quarter of fiscal year 2026 are $38.0 billion and $42.7 billion, respectively. In terms of product developments, NVIDIA, in collaboration with SoftBank (TYO:9984) Corp, has launched the world's first combined artificial intelligence and 5G telecommunications network, known as an artificial intelligence radio access network (AI-RAN). This development has potential applications in various sectors, including autonomous vehicles and robotics control. These are the recent developments surrounding NVIDIA. NVIDIA's latest innovation in computer-aided engineering aligns well with its strong market position and financial performance. According to InvestingPro data, NVIDIA boasts a substantial market capitalization of $3.43 trillion, reflecting its dominance in the semiconductor industry. The company's impressive revenue growth of 194.69% over the last twelve months as of Q2 2025 underscores its ability to capitalize on emerging technologies like AI and digital twins. InvestingPro Tips highlight NVIDIA's financial strength and market leadership. The company has maintained dividend payments for 13 consecutive years, demonstrating financial stability. Additionally, NVIDIA's gross profit margins are described as "impressive," which is evident in the 75.98% gross profit margin reported for the last twelve months as of Q2 2025. The introduction of the Omniverse Blueprint could further boost NVIDIA's already strong performance. With a return on assets of 78.66% for the same period, NVIDIA shows efficient use of its resources in generating profit. This efficiency may be enhanced by the new blueprint's potential to reduce development costs and accelerate market entry for its customers. Investors should note that NVIDIA is trading at a high earnings multiple, with a P/E ratio of 65.01. However, this could be justified by the company's strong growth prospects, as analysts anticipate sales growth in the current year. The PEG ratio of 0.16 suggests that the stock may be undervalued relative to its growth potential. For those interested in a deeper analysis, InvestingPro offers 21 additional tips for NVIDIA, providing a comprehensive view of the company's financial health and market position.