Synopsys Inc Q4 2021 Earnings Call Summary

The following is excerpted from the question-and-answer section of the transcript.

Question: Jackson Edmund Ader - JPMorgan Chase & Co, Research Division - Analyst : Trac, I don't know if anybody has offered congratulations yet from our side, so yes, congratulations on your retirement. You'll be missed, but at least you're sticking around for a little while.

Question: Jackson Edmund Ader - JPMorgan Chase & Co, Research Division - Analyst : I am actually going to do my best Jay Vleeschhouwer impersonation here with a multipart question. So on the double-digit growth in EDA, I'm just curious, what EDA market growth is assumed in that double digits? And are you planning on taking share? And then -- and second, what particular facets of the core EDA -- or whether you want to break it out of front end versus back end or Fusion or hardware or software, how do you want to break out, like what facets of core EDA do you expect to maybe outgrow others? REFINITIV STREETEVENTS | www.refinitiv.com | Contact Us consent of Refinitiv. 'Refinitiv' and the Refinitiv logo are registered trademarks of Refinitiv and its affiliated companies. DECEMBER 01, 2021 / 10:00PM, SNPS.OQ - Q4 2021 Synopsys Inc Earnings Call Aart J. de Geus - Synopsys, Inc. - Co-Founder, Chairman & Co-CEO Okay. Well, let's start with your overall question. It's hard to predict how well others will do, and in many ways, we do well when the entire industry does well. But we do have so many positions where many of our technologies are extremely competitive at this point in time. And it is a point in time where a number of customers are looking to line up with suppliers that they trust over a longer haul because they clearly see that the advances that are happening right now and coming demand a lot of technology and a lot of support. Now you mentioned Fusion, and I'm glad you did because as you well know, this is an area that we have invested in for many, many years with the concept being that instead of running successions of independent tools, having multiple tools essentially collaborate, if I can use that term, to get to a better result was the essence of Fusion. And Fusion is working very well and, as we mentioned in the preamble, growing very well. But it's doubly meaningful because Fusion is also a key ingredient in now layering on top of that this notion of artificially driving autonomous design flows. And the fact that we can access many, many different technologies inside of Fusion to have an AI algorithm learn and get better results has basically been just astoundingly exciting to see. And in many ways, to me, it feels like literally the early days of Synopsys where at that time synthesis was almost like a miracle. Well, it was not a miracle. It was a lot of hard work, but it was capabilities a computer had that exceeded what a human can do. And we see exactly the same here. So I expect that this will be an area that brings many of what -- the things that we have together to drive things forward. Now not to repeat too much what I said earlier, the other half of that equation is, what are the chips for? And the chips are fundamentally for executing tasks given by a system that runs software. And so the desire to make that software run faster is unstoppable. Well, one way to do that is to say, well, what if we designed the system, the hardware system just for certain types of software? And that is what everybody is doing right now. They're essentially creating new architectures for specific applications that then can run blindingly fast. And so the intersection between the application and the hardware is therefore a place where one needs to be able to predict how good the results will be. And that is what all these efforts have been in the prototyping, the emulation and so on. Now the third area I want to mention, and I understand it's slightly adjacent to EDA, although I would look at it as EDA surrounds it, is IP. And one of the great accelerators in the history of design has been to have more and more accomplished IP blocks that have enormous functionality in the most advanced silicon technologies, which are difficult to build. And so the combination of those things is what gives us a sense that for the coming years, we're in a very strong position. And by the way, we are applying that same AI that I mentioned before also to our IP blocks. So there's an integration of the whole solution space.