Cadence Design at Needham Conference: Resilience Amid Uncertainty

On Monday, 12 May 2025, Cadence Design Systems (NASDAQ:CDNS) presented at the 20th Annual Needham Technology, Media & Consumer 1x1 Conference, highlighting its strategic resilience amid global economic challenges. The company emphasized its strong market position, driven by product innovation and a stable revenue model. However, it also acknowledged challenges in the Chinese market, projecting flat revenue growth for the year.

Key Takeaways

• Cadence's Millennium m2000 supercomputer integrates with NVIDIA systems, enhancing engineering and scientific applications.
• The company reported a 19% year-over-year revenue increase in China for Q1, despite previous declines.
• Cadence's "star IP" strategy focuses on high-value, differentiated IP, contributing to a 40% growth in Q1.
• Strong demand for hardware products like Palladium and Protium, with expectations for another record year in 2025.
• Strategic partnerships with NVIDIA and Secure IC bolster Cadence's market position.

Financial Results

• Predominantly recurring revenue model with high gross margins.
• Q1 saw a 40% growth in IP and a 19% increase in China revenue.
• Despite a 16% decline in China's revenue last year, the company anticipates stable performance in 2025.
• Record years in hardware revenue, with 2025 expected to continue this trend.

Operational Updates

• Launch of the Millennium m2000 supercomputer for engineering and scientific workloads.
• Introduction of the Tensilica NeuroEdge coprocessor, offering significant area and power savings.
• Strong partnerships, including a notable order from NVIDIA for 10 Millennium units.
• High demand for Z3x3 hardware accelerators, surpassing supply.

Future Outlook

• Continued investment in "star IP" for scalable growth.
• Expansion into life sciences, leveraging AI-driven tools.
• Focus on verification needs in AI chip design.
• Anticipated flat revenue growth in China, but optimistic about hardware revenue records.

Q&A Highlights

• Millennium's integration with GPUs enhances EDA workloads.
• New Intel CEO Lip Bu Tan's strategies may benefit Cadence, emphasizing standard workflows and IP.
• Cadence's role in China's design activity points to future growth opportunities.

For more detailed insights, readers are encouraged to refer to the full transcript.

Full transcript - 20th Annual Needham Technology, Media & Consumer 1x1 Conference:

Charles, Conference Host: Hi, everyone. Welcome to join us at the twentieth Annual Needham Technology, Media, and Consumer Conference On the virtual stage with me today are Nimesh Nimesh Mali, the senior vice president and the general managers for strategy and new ventures, as well as Richard Gu, vice president of investor relations, from Cadence Design Systems. Before we begin, so really a couple housekeeping items. I'll first read the following safe harbor statement on behalf of the Cadence team. Today's discussion will contain forward looking statements, including Cadence outlook on future business and operating results.

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Due to risks and uncertainties, actual results may differ materially from those projected or implied, in today's discussion. Next, since this is a really a virtual fireside chat, please feel free to submit your questions in the q and a box. We'll have some time, near the end of the this session, to out allow our guests to address your pressing questions to directly to Nimesh or Richard. As usual, we'll keep your questions anonymous. Alright.

Nimesh, really welcome back. Last year, you were here with me at at the same conference, so that was the first time I think we had a we win we've we've known each other for for a little bit longer than that for sure, but welcome back. A lot has changed over the past twelve months. Right? But it feels like cadence hasn't hasn't really changed much.

I'm making it a in a positive way. The business is still growing. The top line in low double digits. Your operating margin is still in the forties and, still expanding. Right?

While there's, this increased worry about the macroeconomic conditions, as it relates to maybe AI infrastructure build build up cycle and maybe more specifically the the the semiconductor cycle as of today, partially due to some really meaningful change and, as we have seen today, the volatility in the in the policy landscape. So let me ask the first question this way, Nimish. You guys definitely talk about, resiliency of the business through any, market uncertainty. Tell us why Cadence is uniquely positioned in such a way in the semiconductor industry and what what leads to the this resiliency, which looks like a structural, you know, inherent to the Cadence business?

Nimesh Mali, Senior Vice President and General Manager for Strategy and New Ventures, Cadence Design Systems: Sure, Charles. First of all, thank you for inviting me back. It's good to be back. And, you know, the macro level, as you said, in many ways since the last time we had this chat, a lot has changed. A lot of movement at the macro level.

But at the same time, this just underscores some of the cornerstones about our business that makes us that much more buffered and resilient. So if we kinda break it down, first of all, you know, we are essential to our customers. You know, the semi and system companies are, you know, primarily our customers. We are tied to the customer's r and d budgets and their design cycle. So you remember that the customer's design active activity of today is translating to the product which is coming out in the market two to three years down the road.

Right? So they wanna be ready to come out with, you know, their competitive products on the other side of any potential downturn, which may be, you know, in the offing. And so core e r and d is usually one of the very last things which gets impacted. Secondly, from a cadence perspective, we are very diversified in terms of products. You know, we got all kinds of products, right, end to end core EDA products.

We got IP, growing IP portfolio, which we'll talk about later, system products, hardware. You know, we have a very diversified customer base, you know, across our semi end systems customers. We don't have any 10% customer, and we're also very broadly geographically diversified as well. And lastly and very importantly, you know, we have a predominantly recurring business model. Right?

It drives a lot of, you know, visibility, predictability. So, you know, very high gross margins, strong exit, you know, q one backlog. So when you bend the ratable model, which is predominantly recurring. So when you put it all together, we feel pretty good about, you know, how we are set up and to to withstand this. Now, again, to be clear, we're not we're not completely immune to you know, if there's a significant prolonged downturn, you know, we'll we'll we'll see.

By the way, we are situated very well, and you can see the multiple elements that which are driving the structural resiliency in the business. And which is why, you know, this environment not we're not withstanding we beat and raised, and when we reported q '1.

Charles, Conference Host: Thank you, Nimesh. So maybe moving on to some of the more more recent more recent events. I wanna talk about the the product announcements you guys made at a Cadence Live, which happened a couple weeks ago. One yeah. One is Millennium, and the other is about the around the Tensilica.

I I wanna I wanna ask you more about the Millennium here. I think Jensen Huang, the media CEO, he he showed up, but he had a fireside chat with Annie Ruth. But he talked about buying 10 units of a Millennium for you guys. Right? I I thought that because thanks

Nimesh Mali, Senior Vice President and General Manager for Strategy and New Ventures, Cadence Design Systems: to

Charles, Conference Host: you guys. Right? Millennium, I think you guys launched not this year, right, but probably in the prior year. I thought that it was a hardware product for something called the CFD, right, computational fluid dynamics. And I recall the target customers were more like car companies, aerospace, defense companies, but now NVIDIA is a customer.

So can you tell us what what Millennium is about and why Millennium today feels more like a new kind of UDA hardware and much, much more relevant for the semiconductor customers? And how should we think about, like, product positioning between that same millennium and other existing cadence hardware products like, famously, the Palladium and and Proteon?

Nimesh Mali, Senior Vice President and General Manager for Strategy and New Ventures, Cadence Design Systems: Yeah. Great questions. So, you know, we are super excited about the Millennium m 2,000 supercomputer, which we launched last week. I mean, it's got tremendous potential to really bring some significant change to our customers, you know, across the engineering workload, science workloads. You know, we have a a very strong and growing partnership with NVIDIA.

And as you mentioned, Jensen on stage, you know, announced that the the, you know, the PO for the 10 units, but there's a lot which goes to be you know, has been leading up to it. We've integrated our massively scalable solvers with NVIDIA Blackwell Systems, you know, and and the numbers are in terms of performance, energy x that we talk about in terms of performance, 20 x low you know, more energy efficient. So as you pointed out, you know, last year, we we launched the first application on Millennium, which was CFD. But your question about, you know, how is it extensible beyond, you know, CFD? So without going into too much detail, but, you know, take a step back and let's look at the the architecture, the software elements of traditional GPU based systems.

Right? So historically, GPUs have been, excuse me, very, very good. They have been exceptional for highly parallel, very dense computation, right, especially matrix multiply operations. So it makes them very ideal, you know, for AI workloads, training deep neural networks, but in all billions of dense multiplications. And CFD simulations are very similar in in terms of structure over there.

You know? So it lends itself these kind of simulations lend itself to themselves to more regular computation. EDA is different. EDA workloads are fundamentally different. They involve what we call a sparse matrix operations, require double precision floating point or f p 64.

Memory accesses are very irregular. So all of these characteristics have made it very hard for, you know, EDA to be ported over and do well optimized on GPUs. But what has happened over time is GPUs themselves have become more and more general purpose, if you will. So when you have architectures like Hopper, like Blackwell, the these these GPUs, they support, you know, very efficient sparse matrices. They have very large on chip memory, very high bandwidth.

And they also support these irregular flows, which are data dependent, which are which is very common in in EDA. So, anyway, the point being that, you know, the GPU architectures have evolved to make themselves more in line with what the requirements are for EDA workloads, number one. Number two, cadence. Instead of just porting over our EDA, you know, workloads over to the GPUs, we rearchitected the solvers, right, to exploit the GPU parallelism, to minimize the data movement bottlenecks and the like. And and then thirdly, I think NVIDIA has just done a phenomenal job with with their GPU optimized CUDA libraries that they help tremendously, you know, in terms of just out of the box, you know, kind of performance improvements alike.

So you put it all together, and then that's where you see all those kind of very strong numbers. You know? And on EDA workloads, very it's very impressive, you know, particularly impressive, not just the speed up, but you can do things which you were just not able to. MediaTek set that, that they can now run world disrupt simulation that was just not possible before. So that's that's, you know, what's changed, and that's why it's so exciting.

And then now you can apply Millennium across, you know, EDA, SDA, and and bio as well. I mean, we we gave some numbers on bio with Trina and Biosciences as well as a reference. Now to your question about palladium and proteome and Melena, how are they all different? So they're they're used for very different purposes. They're very fundamentally different.

So palladium and proteome are for, you know, what you would call accelerating kind of Boolean operations, you know, Boolean computations, which are very prevalent in functional simulation. You know? So the architecture is much more structured, much more simpler, and Millennium is more for numerical simulation. So these two are complementary to each other, you know, specific different purposes. And, know, both both are very much needed for for different elements of the workflow.

And lastly, on your question on Tensor, we also announced that Tensilica NeuroEdge. I mean, it's it's really a coprocessor designed to complement any neural processing unit and handles tasks which are best offloaded, you know, by by the main NPU. So, again, it does very well. We we we talked about seeing 30% smaller area, 20% dynamic power savings. So exciting as well.

So, yeah, I mean, this was a good, you know, good batch of excitement of exciting announcements and Millennium especially. We feel really, really you know, given the breadth of the applications that it can help accelerate, you know, we and our customers are very excited about that. Thanks,

Charles, Conference Host: Nimesh. If if I may, I do wanna ask a follow-up on Sure. Panium, as it relates to EDA. So sounds like you you are you basically are talking about GPU is moving closer to EDA workloads, and you guys are pushing EDA workloads closer to GPU. So looks like, increasingly, it sounds like EDA can be run on GPU platform.

But Millennium is a hardware product. And so I I I I I'm I'm just wanna to ask you this follow-up question. Do you more imagine Millennium to be a hardware business or maybe it's more like a cloud business? Or what do you think about the future here as

Nimesh Mali, Senior Vice President and General Manager for Strategy and New Ventures, Cadence Design Systems: Yeah. Yeah. Yeah. So so, Charles, the way to think about this is, you know, Millennium is actually not just a hardware product. It's a it's a hardware plus software co optimized offering that we are we are providing.

You know? So this is where we, you know, talked about our our solvers, EDS solvers that we have rearchitected to make them much more, quote, unquote, GPU friendly to take advantage of some of the GPU enhancements in the Hopper and Blackfoot platforms. You know? And so but now when you when you when you provide that in in that context, we are still offering our solvers standalone for traditional deals that you have, the two year, three year, you know, term deals that you have with the software, and customers can use it that way. In this context, we also apply or or or have our these solvers available in the public cloud.

You know? So in the public cloud, you know, Amazon or or other hyperscalers, they have CPUs available. They have GPUs available and the like, so that can also be, you know, what and then we also have our own Cadence on cloud. This is our own data center, and, you know, we we offer this, you know, mean, you know, offering through the cloud as well. So you can either buy the Millennium box as an on prem appliance, or you can also access it through the cloud.

So a lot of flexibility in terms of use models, and, of course, the business models will, you know, evolve with that as well. But the key thing is the Millennium is not just think about the Millennium itself as a you know, it's it's the sum of the parts, and where that's where you get, you know, exponentially good value when you're co optimizing all these things, the solvers, the GPU, the libraries, altogether creating that box, and you're providing them. That's where you're getting that special extra in terms of performance and and energy efficiency.

Charles, Conference Host: Thank you. This is such a new thing and many, optionality or possibilities, and definitely Yes. Excited about that. We'll we'll see as we go and see how how you guys really lead in this category. So maybe the next question.

Well, yeah, we talk about hardware. Right? I wanna wanna switch here a little bit to the more traditional hardware. Palladium, Protium, you know, these are, I I would just say, upside drivers, for Cadence for for a while. Right?

So you guys launched a z three x three last year. Wanna ask you this, which inning are we in, over that z three x three product cycle? I mean, the the the reason why I ask this is very simple. Right? When we look at the when we think about the product life cycle, how much revenue opportunity it can be for Cadence, we'll look at the z two

Right? Z two x two launched in, I think, April 2021. Right? Right. Revenue well, you you guys are not given the disclosure, but we can look at upfront revenue.

Right? It's ramping up throughout 2022 very strongly into the at least the early part of twenty three. Right? But looks like now we are now then you guys transition to z three x three. I'm sure you guys have done some bucket sizing.

So how much bigger do you think the z three x three, the product life cycle can be versus the z two x two? And plus my or to your question, which inning are we?

Nimesh Mali, Senior Vice President and General Manager for Strategy and New Ventures, Cadence Design Systems: Yeah. So I think, the way to think about this I mean, again, the emulation, the prototyping, which is really for, you know, verification. Verification is a very, very significant, probably the most complex, you know, kind of problem which the where their customers deal with because, you know, there's a lot of push on first time pass silicon and, you know, the cost of respends, the market opportunity, and all. You know, it's just something which is driving more and more of this verification to be done as early upstream as possible. And while there are multiple ways to do verification, I mean, simulation and and virtual prototyping and formal analysis, it's really the hardware accelerators, which really, you know, are are the ones which can run at tremendous speed and, you know, for the complexity of the design.

So verification is a NP complete problem. Right? You're never done with verification. You're never done with verification. You just get got to get enough confidence before you tape out that you really flushed out, you know, all the significant issues and the like.

And so with that and then you look at the workloads which are out there and you look at the systems and all, you know, AI super cycle, a lot of these chips which are you know, the AI chips are all, you know, most advanced nodes, radical limited, you know, and and and then all the software workloads on top. So you gotta verify it not just as the at the chip, but, you know, at the as a system level with the software. So all these drivers are what's driving the need for more and more, you know, verification. And and and emulation and prototyping are very key cornerstones of the of the verification kind of portfolio. So as you said, I mean, you know, the last cycle or the last z two and x 02/2021 is when we launched them, and then, you know, we we came out with with z three and x three in three years, you know, after that.

And, I mean, the demand has just been incredible. I mean, you know, we we can't build them fast enough. And, you know, this this the when you talk about the innings of this, you know, the innings statement is actually, you know, kinda relevant if the game is constant. The game itself is changing, and then you are you know, the innings is changing as well, if you will. But I I would still feel like we are still in the early stages, you know, of of this of this cycle.

And, you know, we are we are seeing customers, you know, again, very broadly diversified, but doesn't matter, you know, whether you're a big digital customer, AI customer, or you're doing mixed signal design. Verification, something you really, really, really gotta continue, you know, kinda really flexing and making sure that you're, you know, kinda pushing through the system level piece of it. So I think stay tuned. I mean, I think we crossed over from z three to sorry. From z two to x two sometime late last year, and we're just continuing to kinda ramp up, you know, the first half of this year.

So we we we, you know, we honestly believe based on customers' feedback, you know, that, you know, the the best system out there in the market from emulation is z three and next best one is z two. I mean and then just talking about the previous question that you asked, same thing. We offer the emulation as on on prem devices, but we also offer them in the cloud, you know, as well for for our customers to avail themselves. So, yeah, I think I think, you know, this this is we we are we feel very good about how we are situated, and and our customers' feedback just underscores the importance of these systems.

Charles, Conference Host: Yeah. So just to really to to check some of the statement that management pre previously made. Right? I I think '24 was the record hardware revenue year, and '25 will be another record year. Is that the is that still the the case?

Nimesh Mali, Senior Vice President and General Manager for Strategy and New Ventures, Cadence Design Systems: We've had multiple record years in a row, and, yeah, that is correct. We expect '25 to be another record year.

Charles, Conference Host: Got it. Thank you. So now let's ask, let's discuss something, more around the core EDA software. One of the key debates among investors, I I would say since March, is what Lipu, becoming Intel CEO means for Cadence. I'm sure you have stories to tell as you worked under leadership at Cadence for many years.

Right? So so from from the investment community, I'm hearing two sides of the arguments, I I would say. On one hand, some folks think Intel is going to do a lot of cost cutting. Well, they they are doing that and not going to. And headcount risk reduction.

Right? Sounds like possibly a negative for overall EDA spending by Intel. But on the other hand, Intel, still runs legacy in house EDA, has historically, favored one EDA vendor, your competitor. And has multiple times has said Intel is a low watermark in terms of your market EDA market share. Right?

I mean, yeah, amongst all the global customers, which could mean upside for Cadence going forward. That was the that was the bull case. Right? So between the bull and the the bear cases, which one do you think will prevail? In your opinion and why?

Nimesh Mali, Senior Vice President and General Manager for Strategy and New Ventures, Cadence Design Systems: Yeah. I mean, there's obviously we get asked this question a lot these days. And, you know, let's just say, you know, we are obviously very pleased, with the announcement of Lip Bu, becoming the Intel CEO. I mean, you know, in a bigger picture view, we all know about, you know, his incredible track record in the industry. You know, he drove this remarkable turnaround with Cadence, you know, all these years ago.

And we think there's a great deal of excitement about what he'll bring to Intel. Now last week, you know, at Cadence Live, we honored to have him, you know, for a fireside chat with with Anrud. And during that chat, I mean, Lipu, you know, stressed his priority, you know, to focus on innovation, to reformulate their strategy and the AI strategy particularly, and the importance of first time pass silicon increasing the productivity and the effectiveness of the of the engineering teams. Right? So, you know, he also stated expressly his desire to move away from custom e EDA, from custom IP, and embrace standard workflows, embrace standard IP.

You know? So I think this approach, this mindset really, I mean, should enable Intel to, you know, not just rationalize the internal investments they are making in a in a informed manner, but more importantly, it increasingly allows them to move to broad, you know, industry tested best in class technology to help, you know, with their with their development, with their designs. Now from a cadence perspective, as you said, Anuj has mentioned this before, you know, we have made progress, of course, at Intel on the Foundry side as as well as on the product side. A lot more to do over there. You know?

And and as you know, Charles, I mean, our solutions are being used by the marquee companies at the most advanced nodes and other foundries. So we think there's much more opportunity for us to help Intel, not just on the chip design side, but, you know, even beyond that on packaging. I mean, Intel's got a great packaging solution. We got the best, you know, three d IC and and Allegro solutions out there on system analysis. And so we look forward to the opportunity to help and work with Intel.

And as Lip Bu said, you know, there's a lot more opportunity for us to do stuff together and to learn from each other. So that's basically you know, stay tuned.

Charles, Conference Host: Stay tuned. We're definitely looking forward to more more updates. So let's pivot to IP. This has been an area. Cadence seems a little bit behind, your closest competitor, Synopsys.

In recent years, I we've been hearing from on earnings calls about this star IP strategy. I think maybe it's a little bit, not fully elaborated to to investment community. Maybe tell us what a star IP means and why Cadence think this is the right strategy.

Nimesh Mali, Senior Vice President and General Manager for Strategy and New Ventures, Cadence Design Systems: Yeah. Yeah. So IP again, huge opportunity, with us. And, you know, you look at what the trends are, again, kinda like the previous question, more and more customers want to outsource IP, you know, outsource their, you know, standard space, interface IP, for example. There's really no good reason for them to continue doing it in house And, you know, so more and more customers want to focus on their own unique innovation.

And then these kind of things, okay, more outsourcing is happening. So that's number one. The Foundry ecosystem, you know, build out is happening. So that is well, I mean, you got now four big foundries. Right?

We're all focused on the most advanced nodes. They all need, you know, IP, which is optimized for for their technology. That's happening. From a cadence perspective, you know, we have kinda built out our portfolio over time. And, you know, about a few years ago, you know, our our focus changed, if you will, or was more refined to move not just from growth by any means to scalable and profitable growth.

And so what that meant was that, you know, we made the decision to say, okay. This is what we're gonna really focus on. We think the biggest opportunities were with, you know, let's say, AI, HPC customers that were designing chips at the most advanced nodes. You had systems companies like hyperscalers building their own silicon who needed outsourced IP. I mean, it's one thing for the other companies, the semiconductor guys who have been building IP over the years and want to outsource it.

Hyperscalers has nothing to outsource. They didn't have it in the first place. So all this was very synergistic, you know, this whole thing on AI HPC, most advanced nodes with our digital business, where we also focus on providing tools for the most advanced node designs for customers, the most bleeding edge. Know? So that's what we mean when we talk about star IP, from high value differentiated IP targeted for specific verticals, you know, and and delivered at the most advanced nodes.

So think about this as titles like PCIe, all the all the different, you know, versions of the DDR, high bandwidth memory, and also our Tensilica computing IP. So what Cadence has done then, you know, over the past few years has methodically built out this portfolio. You know? It's it's customers have been giving us feedback, and our IP is also getting better. It's getting you know, giving better PPA, better quality.

And so based on customer needs and guidance through organic investments, and we have been investing more and more over the last three, four years, and also inorganic, meaning acquisitions. You know, we augmented our portfolio with high bandwidth memory IP from Rambus. We added, you know, internally chip that connectivity IP like UCIE, And and then security is becoming a key care about, so we signed this agreement with Secure IC earlier this year. And and, you know, and then I mentioned the Foundry ecosystem, you know, Samsung and and TSMC, of course, but then Intel Foundry, Rapidus. We have this big deal.

We talked about it in q four of last year. So and then most recently, you saw the announcement on on the Artisan foundational IP, right, as well, standard cells, IO, memory compilers. So these are all gonna be optimized and validated at different process nodes at different foundries. And so, you know, so we are we are in good shape. IP grew, you know, 40% in q one.

And, yeah, we we feel like we're in a really good place. We continue investing, continuing delivering, and, growing the portfolio. And, yeah, we're excited about where we are in IP.

Charles, Conference Host: Thanks, Nimish. Maybe let's move forward, to the next topic. I wanna ask you about China. We know that last year, probably not a good year for for Cadence overall China business. You guys began the year, thinking maybe China could be flat.

Mean, 2024. And I think I ended the 2024 at minus 16%, growth for for for the overall China revenue. But still, kudos to the team for really maintaining and actually slightly raising the the growth, through, growth outlook through the year despite that, China headwind. So what's the outlook for this year? Mind if you reiterate some of the things that, you you guys recently, talked with the investor is about.

And how should we think about what could lead to the upside or the downside, for your overall China business compared with the with the baseline outlook you just laid out at the in the in the last earnings call?

Nimesh Mali, Senior Vice President and General Manager for Strategy and New Ventures, Cadence Design Systems: Yeah, Charles. I mean, I think the the key thing over here again is that, you know, we are driven by, you know, design activity. Right? And design activity continues to be strong. I mean, that's what we said in the earnings call.

We continue seeing that, you know, across, you know, not just China. I mean, broadly as well, but also in China. It's we we continue seeing strong design activity. I mean, again, keep in mind, you know, that customers are designing products of today that are gonna hit the market, you know, tomorrow, few you know, two years, three years down the road. Dynamics are very similar.

There's a lot more silicon being built, you know, domain specific workloads. Mean, a lot of accelerators, many systems companies wanting to build their own silicon hyperscalers and others. I mean, Alibaba, ByteDance, Tencent. Right? And so we all of those dynamics are very similar, you know, as we see in in in other parts of the world as well.

And and that's driving much more design activity. And then the other thing to point out is that, you know, we sometimes gotta, you know, given all the all the hype and the excitement around AI, kinda just focus on, you know, data center and and AI and the likes. So, of course, that's there. That's a key part of it, but it's not just that. Right?

We've it's also the physical AI. Right? The emergence of physical AI. And in there, you're seeing, you know, autonomous vehicles, robots, and drones. There's a lot of design activity which is happening over there as well.

Right? And autonomous, especially on EV, tremendous activity happening in China on that. So from a cadence perspective, you know, we are we are pleased, you know, with the 19% year over year q one growth in China. And as we have said, I mean, we we are, you know, we think it's prudent to to be prudent, and we'll see how it goes. But we, you know, we are assuming at this point that China Twenty Twenty Five revenue could stays flat year over year.

We'll see we'll see, obviously, as we go get deeper in the year, we'll provide more updates. But at this point, happy in q one and maintaining our our assumption of being flat year over year for the year.

Charles, Conference Host: Thank you, Nimesh. I wanna spend the last question on a little bit of a more kinda maybe you can call it a blue sky kind of, discussion. A bit longer term for sure. So Aniruth in the past has laid out how AI benefits cadence are roughly three main aspects. More companies designing more AI chips, that's number one.

More customers adopting Cadence AI products, that's number two. And and and Cadence expanding into adjacent areas such as drug discovery. Well, that the area that can be disrupted by AI. Right? That's that's number three.

I think investors are largely thinking that the first one, more companies, especially system companies, hyperscalers designing more AI chips, have not fully played out in a way that that it meaningfully reaccelerate cadence growth. So imagine this. Right? I mean, this is the thinking behind that. If magnificent max seven companies, a magnificent seven companies become more like semiconductor companies each on chips and, from the from the beginning to the end, and each one of them can, let's say, put a number there, contributes 5% of Cadence revenue.

I know it's probably not there, probably not for most of them. But seven times five, that's 35%. That could be 35 of a Cadence revenue. I'm sure you guys really not quite there, but, when will that happen if that happens at all? And what is cadence doing to to make it happen?

I I think this is a this is a top, a long term questions, I think, everybody have in their mind.

Nimesh Mali, Senior Vice President and General Manager for Strategy and New Ventures, Cadence Design Systems: Yeah. That's a great question. Big big big like you said, blue sky, big picture question. Right? I mean well, first of all, you know, just reemphasizing, we got a very diversified customer base, no 10% customers.

You know? And we have said this in the past as well about that the top 40 customers bring in roughly 55 to 60% of our total revenue. Now when you talk specifically about AI, I mean, we have said this. Right? It's a generational megatrend.

I mean, we are still, I think, in the very early stages of this secular cycle. It's gotta be a multiyear, some say multi decade super cycle. And, of course, you know, as I said, you know, HPC data centers are what folks typically think about when speaking about AI. And the demand for hyperscalers is ginormous. Right?

I mean, massive training requirements, the scale at which they are operating. Everyone's designing their own custom chips, AI chips, very complex chips, radical limited, most advanced nodes, and they're requiring very sophisticated design tools, very sophisticated verification tools. You know? And that's what Cadence has been providing. And all some of those things that we talked about, the AI driven tools that we are providing, you know, be it on for PPA optimization, be it for, you know, verification like Vericium or or or system analysis and the like.

And so all so that's that's in the context of, you know, the chip. Now we've talked about the needs are being beyond just silicon. Chiplet architectures are becoming more prevalent, you know, means you need advanced packaging. And it's not just packaging by itself. You know, you're running into more and more thermal issues, electromagnetics issues, warpage issues.

Right? That requires a lot of in design analysis. You know? So it's the the workflow itself. The way that the engineers, customers are designing these things are different as well.

You know, it's not just designing the chip and then, okay, ship it over to to the, you know, the package or the systems guy. It's in design that you gotta kinda go and do all this stuff. So it's it's the type of designs are changing. The way you do the design development is changing. And, you know, so even, you know, when we talk about hyperscalers and and the way they are doing their design, I mean, obviously, they're one of our fastest growing verticals, you know, and but their flows are evolving.

We see hyperscalers going from doing ASIC flows, right, where you do the front of the micro architecture, the logic verification, then you ship it over to the ASIC vendor for the implementation. But, you know, some of the hyperscalers and more and more of them are looking at, you know, doing it in house, bringing it all in house, doing a COT, a customer owned tooling flow. So even that workflow is changing. You know? And then as I mentioned that the need is not just in data center and and hyperscalers.

It's also physical AI. You know, autos, robots, drones. Now there are several applications across all these multiple verticals there. So, anyway, the point being, there's a lot of demand, much more AI chips being built. It's a virtuous cycle.

The more the demand for AI silicon, the more the demand for our tools, and then it pulls in our tools and our AI driven tools to deliver to those complex designs, which allows them to do even more complex designs. You know? And so that's basically this virtuous cycle that we see. And then beyond electronics, you know, as you mentioned, we also view life sciences as an area which is, you know, pretty ripe for disruption. I mean, we've talked about this in the past, Charles, that, you know, 99% of design in chips is done, right, virtually digitally.

You know? About 25% in systems. But in life sciences, only 1% is being done with in silico methods. And so I think this is, we think, a huge opportunity five years, seven years down the road for us to kinda look at that. So, anyway, that's the way we we look at this.

So we think we got several exciting growth vectors for different phases of the AI cycle as it plays out, and I think, you know, we'll we'll keep reporting on how how the progress we are making over there.

Charles, Conference Host: Thank you, Nimesh. And, I think, folks, we have probably four more minutes, and we can take some questions from the audience. Once again, if you have a question, feel free to type it in, and I'll read your questions. So far, there's no question in the queue, but, maybe, Nimesh, let me start a question. As a quick follow-up, you mentioned about, you guys, acquired the the art business from Arm, and it's it's a they they call it I think they call it a physical IP.

And can you tell us where does it fit in the Cadence portfolio? And and quite frankly, Arm is also, like, IP company. Right? They're number one in IP. You guys are number three in IP.

And why, Artisan, why Cadence is a better owner of Artisan than Arm? Why why you guys make that transaction? What's the rationale? Why why it's why it's why it's good for both of you?

Nimesh Mali, Senior Vice President and General Manager for Strategy and New Ventures, Cadence Design Systems: Yeah. Yeah. So from Charles, from our perspective, Cadence, like I said, we have been building out a portfolio on IP, and, you know, we kinda layer on these different capabilities to make it a more full featured portfolio. You know? So we have the compute IP with Tensilica.

You know, then we we know this interface based IP, the star IP that we talked about earlier, then we added on high bandwidth memory, you know, which was being driven by AI. And then, you know, we got the security IP, secure IC, although the the acquisition hasn't closed yet. So when we looked at it from that perspective, foundation IP is something we have had our eye on the past, but never felt that there was a compelling need to add it to the portfolio because we are focused more on, you know, layering on these other things which are much more mainstream, number one. And number two, we felt the market was adequately serviced by what was available out there at the time for the opportunity. Now the opportunity has changed.

Now you got the Foundry ecosystem building. So when you have these new foundries coming in, they are looking for their own you know, the standard cells, the memory compilers, the IO buffers, and all these what we call foundational elements to be optimized for the Foundry. They need help with that. So that when the opportunity came along from from Arm's perspective, Artisan, a very well known brand, you know, in the market, very prevalent out there. And from an Arm's, you know, strategic perspective, you know, they were willing to divest that, and so we had these discussions.

So the opportunity came along, the need was there, and we we we had this, you know, the great opportunity to pick up some really well established IP. And, you know, so we we signed a definitive agreement on that. Yeah. It's not closed yet, though. Yeah.

Charles, Conference Host: Thank you. Let me double check again, but, my screen shows there are no further questions from the audience. And I think, we are almost at the end of the session. Maybe it's a good time to wrap up. Thank you, Nimesh.

Thank you, Richard, for joining us, and thanks everyone on the line. And, please enjoy the conference, and, we'll talk soon.

Nimesh Mali, Senior Vice President and General Manager for Strategy and New Ventures, Cadence Design Systems: Thank you very much, Charles. Looking forward to doing it again next year.

Charles, Conference Host: Thank you.

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