Ansys says simulations will close the gap with reality and make the world more sustainable

You may not have heard of Ansys, but it’s in the process of being acquired by chip design tool firm Synopsys for $35 billion.

That’s happening because Ansys, an engineering software company, specializes in the simulation of the world’s complex electronic systems, and the world of chip design is increasingly moving into the more complex world of system design, said Prith Banerjee, CTO of Ansys, in an interview with GamesBeat.

Ansys spans a lot of businesses. It works in the automotive space with carmakers (original equipment manufacturers, or OEMs). It works with the tier one suppliers in the car industry, and it works with chip companies that are making chips for the cars and more. Ansys makes tools for engineering simulations and more, said Banerjee. And he noted that companies all over the world are embracing AI and machine learning. He can see it in his customers’ simulations.

“With AI and ML, we are able to use simulation much easier as well as much faster. Something that takes a hundred hours to run can run in a matter of minutes, so we have got some techniques to aid us in that area,” Banerjee said. “AI was big in general at CES. I mean Jensen (Huang, CEO of Nvidia) talked about AI and all the GPUs and so on, but we are embracing AI like never before.”

A parade of partners

Ansys is working with a lot of companies. At CES 2025, it unveiled a collaboration with Sony Semiconductor Solutions to improve perception system validation in smart cars. Ansys’ solutions are used by more than 200 automotive and tech companies that show off stuff in Las Vegas each January. Every year, Ansys tries to close the gap between engineering design and reality using the power of simulation.

It creates virtual wind tunnel technology to optimize F1 racing car designs with Oracle Red Bull Racing, Porsche and Ferrari.

Increasingly, this simulation superpower also speeds time-to-market, lowers manufacturing costs, improves quality, and decreases risk.

LightSolver, another Ansys partner being announced today, says that the fourth industrial revolution, also known as Industry 4.0, is fully underway. Almost every industry — from automotive and aerospace to consumer goods and healthcare — is demonstrating a shift toward digitalization.

The industrial equipment and manufacturing industries are no exception. A global industrial robotics survey revealed that industrial companies are expected to invest 25% of their capital spending on automation from 2022 to 2027. The survey also found that automation is already being implemented or piloted for many popular industrial tasks, including palletization and packaging, material handling, goods receiving, unloading, and storage.

Digital twins are for real

Banerjee is excited about the tools like Nvidia’s Omniverse, which is enabling the creation of virtual designs known as digital twins. With such twins, companies like BMW are designing car factories in a virtual space of the Omniverse first. When the design is perfect, they build the factory in the real world. They outfit the factory with sensors that collect data and feed it back to the digital design. That makes the virtual design better and creates a feedback cycle of continuous improvement. That means that the simulations of everything from Microsoft Flight Simulator to the car factories are getting closer to real life.

“Digital twins as a topic is very big for us. Of all the conversations that I had with all customers, we talked most about our concept of hybrid digital twins the most,” Banerjee said. “The rest of the industry is doing digital twins by putting sensors on the actual assets, right? You’re making a digital model of the asset by just putting in sensors. And we’re using data analytics. What we do in terms of digital twins is physics-based, simulation-based digital twins.”

Hybrid digital twins

Banerjee added, “We combine it with data analytics to do what is called hybrid digital twins. Sustainability is big for us. So we are driving a lot of things around how to make the world more sustainable, lower carbon emissions using simulations.”

Asked about whether Ansys would like to see more of Nvidia’s digital twin technology as open source, Banerjee said he would like to see open standards in the ecosystem.

“The faster this whole thing comes, the bigger the opportunities for everyone,” he said. “It doesn’t help anyone to have four different standards.” No one wants to be tied to a single GPU or a single software stack.

Banerjee said the metaverse is real, as many companies are taking it seriously beyond Meta. He noted those include Amazon Web Services, Microsoft, Google and Nvidia.

“They all have some form of the metaverse. So we believe that the metaverse is real, that that is going to happen. And we, as the leading simulation company, need to integrate with the metaverse,” Banerjee said. “And what is it? The metaverse allows you to combine the physical world with the virtual world, which is the concept of digital. For example, what we bring to the Omniverse from Nvidia is that they have got a solution, a stack.

He added, “The are using their simulators like Isaac, simulating robots and so on, right? But their simulations are kind of at a high level, an approximate simulation. They say it’s a physics-based simulation, but it’s not the level of accuracy that we bring to the table.”

He said that Ansys is focused on physics-based simulations, and the company’s work revolves around core physics solvers. These cover mechanical structures, fluids and electromagnetic areas.

“These are the four core solvers. We are in discussions with Nvidia and we have an active partnership going on to take each of the solvers to visualize the output so the engineer will see the output on the desktop as it is happening,” Banerjee said.

He said the world is moving to the cloud the world and AI. In that new world of AI plus cloud plus GPUs, the metaverse is the right way to do the user interface and interact with the results of simulation.

“We are working hand-in-hand with Nvidia to make sure our four core solvers are integrated with the Omniverse. So that’s one very core area of collaboration,” he said.

Asked what he means by hybrid digital twins, Banerjee said he used to be the CTO at a couple of other large industrial companies. He was CTO at ABB, a power and automation company in Switzerland. And he was also CTO at Schneider Electric, a power and automation company based in France.

In those roles, he saw that large industrial companies have lots of large assets. The assets can be transformers, robots or switch gears. And these assets are there for a long time.

“What you try to do is to see to see when that asset fails. Say a million dollar transformer fails, and when it does, you lose power and that’s bad for the environment and customers. So what you try to do is put sensors on these assets to see if my transformer working or not,” he said. “And so before the transformer fails, it starts giving signals. So just like the human body, we have the normal things like our temperature. But before we fall sick, the temperature goes to 99. 100, 101 and then you get the fever and then it’s really pulsing. So before you really fall sick, you start giving signals. The same analogy works for digital twins.”

Reducing the cost of failure

He added, “So you put sensors, collect data and before that asset fails, it starts giving different signals. So if you monitor the changes, you can predict that it’s going to fail. This is how when I was at ABB and Schneider Electric and again all the other companies like Caterpillar or GE and everybody, all these companies, they use digital twins using data analytics. So if they pull the data and they look at here’s the normal behavior and notice the abnormal behavior. And then based on the abnormal behavior, you see it’s going to fail.”

He continued, “Now, what I found out when I was at ABB and Schneider is the accuracy of that prediction is based on pure data analytics at about 70%. And you say, oh, 70% is pretty good. Well, if you have a million-dollar part and you are 70% accurate, that means you made a 30% error. So you made an error to replace a part with a 30% probability. You just made a $300,000 mistake. You made a decision which was wrong because your accuracy was only 70%. So this was the problem I was facing when I was at Ansys.”

Banerjee said he always knew that if you could tie that to physics-based simulation, the accuracy would go up.

“I joined Ansys about six, seven years ago and I told my CEO, I said, this is the problem that we need to solve. If you could solve it through physics-based simulation, that would be absolutely amazing. So physics-based simulation says, “Here is a transformer, here is a robot, here is whatever, right? And you go back to the basic physics. This is how the transformer works, right? It is electrical, it signals going through the coils and is generating this and if there is a cut in the coil, right, those electrical signals, the mechanical signals will not come. That’s why the failure happens. Let’s go back to the first principles of the physics. So at Ansys, we did physics-based digital twins and simulation. The accuracy went from 70% to 90%.”

He said, “You say, ‘Wow, 90% is great.’ But with that million-dollar part and 90% accuracy, you’re still making a $100,000 mistake. So then we said, what if you could combine the two? Combine the data analytics-based digital twins with the physics, and that is what we did called fusion technology, or a hybrid digital twin, which is now called a product called Twin AI.”

“The accuracy of that combination is 99%. So on that million-dollar part, I will only make a $1,000 mistake. So our customers are super excited,” he said.

“At CES, I talked to many customers about our Twin AI technology, digital twin technology that works at the system level. We could build a digital twin of an entire car or a subsystem. You can take an EV car, break it down into different components of power electronics — the battery the drive train or inside the battery. We can keep going down and down now and build digital twins of the system, the subsystem, the components. But at every level, if there are sensors, we can actually build this fusion-based digital twin, this sort of hybrid digital twin. That is an absolutely amazing technology, and this is something I’ve been proud of.”

The intersection of simulation, game worlds and the real world

I noted how there’s an intersection of simulated worlds and game worlds and the real world with products like the game, Microsoft Flight Simulator 2024. The 2024 game had 4,000 times more detail on the ground than the 2020 version. It enabled them to do amazing simulations like using a helicopter to herd a flock of sheep on the ground.

They added gliders to the game and that meant you could land anywhere, so they needed well-simulated places where you could land just about anywhere on the planet. They enlisted aircraft manufacturers to give them CAD models of the designs for aircraft in the game, and they pulled camera video footage from the planes after they flew over parts of the planet. My question was whether we would ever get to one-to-one accuracy between simulation and reality.

“So that’s a great question. So let me take a step back and give you the approach to simulation that we use. In our world of computer-aided engineering simulation, CAE simulation, we take the world around us which is governed by the laws of physics. Physics doesn’t lie, right? When in the world of fluids, there’s an equation called Navier Stokes equation. These are second order partial differential equations. That is the equation that is the way nature works. So we take those equations, and we solve them numerically.”

He added, “Now when you solve it numerically you can take a particular type. You can break it up into four quadrants or more. Four or 16 or 32. The more elements I have, the more accuracy I get.”

And he said, “The trouble is, as you add more elements, more accuracy, your runtime goes out the window. Because runtime is sort of N cubed, right? So the number of elements, it’s N cubed. So this has been the challenge in our industry. With CAE simulation, you can absolutely get more accuracy, but your runtime increases. So how do you get more accuracy faster?”

Technology pillars

As CTO at Ansys, Banerjee has multiple technology pillars. There are advanced numerical methods where you’re looking at just the algorithm itself on a single processor, making it go faster, more accurate, and so on. The second thing is using HPC, high-performance computing.

“You have a thousand hours of work to do. I have a hundred processors, and I’ll give them to you to run much faster just by adding parallelism to it,” he said. “That’s why GPUs come in the partnership with Nvidia, helping us to take a fixed amount of work using GPUs to make it run much faster right with the same accuracy.”

The third focus is AI, where the company is training those its four core simulators. Once trained, the AI model runs 100 times faster.

“In the world of digital twins, we have actually taken all those technologies, GPU, HPC technology and AI technology, and we call that reduced order models, ROMs, and it’s because of Ansys’ leading position in the area of reduced order models and AI cost simulation.

The simulation market

The simulation market is around $10 billion today and it’s growing around 12% a year.

If you look at the entire R&D budget across all industries in the world, it’s about $1.2 trillion dollars, Banerjee said. In the automotive industry, the R&D is about $250 billion. About 75% of that cost is banging up cars in “physical validation” of the vehicles. It’s physical prototyping, he said.

“What we believe is that the simulation becomes so accurate and so fast that companies will stop doing physical programming,” Banerjee said. “In fact, the CEO of GM has said that by 2035, GM will stop doing physical programming if everything will be virtual. So simulation is growing at 12% today. But once those use cases come in, there will be a hockey stick event.”

The complexity of chip design and the coming of systems design

Banerjee noted that one reason that Synopsys is acquiring Ansys for $35 billion in cash and stock is that the world is moving from chips to systems when it comes to design.

“You have electronic chips that were designed with tools from Cadence and Synopsys and Mentor Graphics, but they’re only building the chip inside a system. So it’s going inside a car, right? But now you are going from chips to systems and the opportunity for simulation to design these really complicated chips to systems is enormous. It’s powered by GPUs, powered by the Omniverse, powered by AI. I am very excited about the future of simulation and synthesis for the vision of chips to systems across industries like automotive, aerospace, energy, high tech and healthcare. These are the five verticals that I we look at in terms of the opportunity to move from chips to systems.”

Banerjee has worked in the electronic design automation (EDA, or using software to automate chip design) for more than 20 years. He spent his first 20 years in academia, building EDA tools. Forty years ago, he had to teach VLSI design by drawing rectangles on the screen, which is now called Custom IC. Then the whole design industry moved. Chips had perhaps 10,000 transistors, which was pretty hard for engineers to process. Then each progressive improvement, from standard cells to Synopsys’ synthesis, the level of complexity of the designs improved. Now chip designers can create 200-billion transistor chips.

“My projection is that we could do a similar thing with synthesis tools for systems. Can you have a synthesis tool for a system as complicated as an automobile or an airplane? Today, it is done. You look at a specification and a human designer goes and does the CAD of the airplane engine,” he said.

He added, “I am saying at some point in the future you will not have to do the CAD. It will be synthesized, right? Just like we use synthesis tools for chip design, there will be system level synthesis tools. Now this is like I’m talking five to ten years out. We have got things going on at Ansys, but that’s the opportunity. Once that happens, the design of the systems will be accelerated by many factors.” So you could do a thing like a 200 billion transistor chip, right? It’s something much more complicated than what you can do. And as the automotive companies are struggling to reduce that design time from four years to two years to whatever, could you imagine a new car design coming out in a matter of a month? Yeah. that can be enabled by synthesis.”

Simulating the human body

I asked Banerjee what was the most complicated design possible. Is it the human brain? The human heart?

“I’m glad you mentioned the human heart. I will tell you, at Ansys, I am really passionate about the healthcare area and we in the CTO office are working on simulating the human body, the heart, the brain, the lungs and so on,” her said. “That is just such a complicated thing that we live and breathe every day. Simulation of a human body accurately will enable us to come up with solutions to heart disease. When you have arrhythmia, you have irregular heartbeat. That can be treated through either you take a drug, AstraZeneca, and it will treat your [condition]. Or you take a pacemaker from Medtronic and that will take it. Or you do more jogging, right? Changing your behavior.”

He said, “Each of these things. or you can do actually an operation, right? You go in and you insert a stent. We are imagining a future where each of these things can be simulated. Here is this cardiovascular drug. If I take that medication, will it interact with the molecules in the human body? If I put a stent in, what is going to happen? So imagine in the future you will not require what is called clinical trials. Everything will be done through simulation of a human body, right? Virtual humans. And that will accelerate the use of the discovery of drugs and discovery of medical devices.”