Short answer: Hardik Kabaria says simulation tools from Cadence, Siemens and Synopsys exist, but industry still prototypes and tests in labs, and a semiconductor tape-out can cost millions of dollars and take months. Vinci answers thermal questions in minutes or seconds.
Watch this answer from Episode 50 (starts at 5:59) · Episode 50 notes and transcript
From Episode 50: Physics Simulation for Chip Design Used to Take Days. This AI Does It in Seconds., starting at 5:59.
Jordan Metzner [5:58]: Well, awesome company, and great to chat with you today. Obviously, a lot to learn, and I've I've worked in some simulation environments, especially around robotics and things like that, which were, simulation has probably been around for probably a pretty long time, especially, like, using video game engines and things like that. So just tell us a little bit more about how, simulation is entering the hardware space and, kind of what impact it's having there.
Hardik Kabaria [6:19]: Yeah. So let's start with some basics. Like, the moment you wanna design and develop a hardware, you care about its physical performance. And for several decades, how has the industry attacked that problem? There are physics simulation software, there are physics simulation methods that have been around since the sixties, and there are tools that have been developed by Cadence, Siemens, and Synopsys that has been used by industry. But ultimately, the industry performs physical experiments. Whether it's robotics, whether it's consumer electronics or semiconductor, you design a part, you prototype, you take it to the lab, and you do perform experiments and figure out whether your hypotheses are correct or not, and if not, you kind of go back to the basics. Right? That's the physical world of experiments and then there is the digital world of experiments. There are tools across the board to do both the things.
Hardik Kabaria [7:11]: So the need of understanding physics in the digital world as well as physical world is absolutely there and you care about it across the life cycle of the product. And what we bring to the table is to do that faster, at a higher capacity, so it should be limited by how many computers you are deploying the software to, not limited by the number of people who can use those complex software or number of people who can perform those expensive experiments, right? That's a real choke hold. Like, many prototypes can you do? A tape out in semiconductor industry could cost millions of dollars and months. So you want to do these iterations really fast, accurate, so you can make design decisions about materials, your layout and the same goes for robotics like you want to make choices about actuators, the loads, is it going to be able to do the cooling itself or do you have to design some additional cooling mechanism for the electronics and the edge inference you are putting in there. So that is a different way of saying the faster you can have a digital physical physics infrastructure in your design loop, the better decisions the engineering organizations will make. And that's nothing new, we have needed it. Now that is the place where we are deploying our software. So the users and customers who are using our software, they are getting answers on their physics questions, specifically thermal questions like how is my semiconductor part going to heat up?
Hardik Kabaria [8:41]: Or if I make small changes here, will it will I be able to increase the data rate transfer? Will I be able to increase the power load in matter of minutes, matter of seconds versus waiting a day. Or most importantly, not needing an expert who can perform those analysis versus just you ask your question, get your answer in a manner that you can trust the answers.
