Cadence Design Systems [CDNS] Conference call transcript for 2023 q1
2023-04-24 21:17:04
Fiscal: 2023 q1
Operator: Good afternoon. My name is Emma, and I will be your conference operator today. At this time, I would like to welcome everyone to the Cadence First Quarter 2023 Earnings Conference Call. All lines have been placed on mute to prevent any background noise. After the speakers' remarks, there will be a question-and-answer session. Thank you. I will now turn the call over to Richard Gu, Vice President of Investor Relations for Cadence. Please go ahead.
Richard Gu: Thank you, operator. I would like to welcome everyone to our first quarter of 2023 earnings conference call. I'm joined today by Anirudh Devgan, President and Chief Executive Officer; and John Wall, Senior Vice President and Chief Financial Officer. A webcast of this call and a copy of today's prepared remarks will be available on our website at cadence.com. Today's discussion will contain forward-looking statements, including our outlook on future business and operating results. Due to risks and uncertainties, actual results may differ materially from those projected or implied in today's discussion. For information on factors that could cause actual results to differ, please refer to our SEC filings, including our most recent forms 10-K and 10-Q and today's earnings release. All forward-looking statements during this call are based on estimates and information available to us as of today, and we disclaim any obligation to update them. In addition, we will present certain non-GAAP measures, which should not be considered in isolation from, or as a substitute for, GAAP results. Reconciliations of GAAP to non-GAAP measures are included in today's earnings release. For the Q&A session today, we'd ask that you observe a limit of one question and one follow-up. Now, I will turn the call over to Anirudh.
Anirudh Devgan: Thank you, Richard. Good afternoon, everyone, and thank you for joining us today. I'm pleased to report that Cadence delivered strong results for the first quarter of 2023, with ongoing robust demand for essential and innovative solutions driving solid double-digit growth. In view of the strong start to the year and the continuing momentum of our business, we are raising our financial outlook for the year. John will provide more details in a moment. Generative AI design tools are revolutionizing chip and system development by delivering unprecedented optimization and productivity benefits. Customers have already been benefiting from our ground-breaking generative AI solutions in the digital, verification and systems areas, and with the recent introductions of Virtuoso Studio and Allegro X AI, we now have an unmatched chip to package to board to systems generative AI portfolio. Leveraging 30 years of industry leadership Virtuoso Studio accelerates heterogenous system design, and through AI powered layout automation and optimization provides an average 3x productivity boost for designs in the notably complex analog domain. Several customers including MediaTek, Renesas, Analog Devices and TSMC provided testimonials for the launch. Allegro X AI technology utilizes the latest innovations in generative AI to accelerate PCB design with more than a 10x reduction in turnaround time, and at the recent launch, it was endorsed by Schneider Electric and Kioxia. All of these powerful engines are fueled by our unique, differentiated big data analytics JedAI platform that unifies massive amounts of design and verification data to carry forward learnings and insights to future designs. Our rapidly proliferative generative AI solutions are enabling customers to reap significant power, performance and area benefits through better optimized designs while greatly improving engineering productivity and accelerating design closure. Along with AI, other generational trends such as hyperscale computing, 5G and the digital transformation across multiple verticals continue to propel thriving design activity across semi and systems companies, creating rich market opportunities for our differentiated end-to-end EDA, IP and systems solutions. I am pleased with the momentum in our core EDA business as well as our continued expansion into systems area that provides us both revenue and margin opportunities. Now let's talk about our key highlights for Q1. In Q1, we deepened our collaboration with MediaTek, which includes a broad base of our digital, analog, verification and systems design and analysis solutions. We significantly expanded our collaboration with a marquee aerospace and defense systems company, that included the proliferation of our digital full flow, custom, verification products, as well as our RF and system analysis solutions. And Cadence expanded its collaboration with TSMC and Microsoft, as we leveraged our Pegasus Verification System and Cloudburst platform to accelerate giga-scale physical verification in the cloud. Ever increasing complexities in system verification and software bring-up continued to propel our verification business, to a 31% year-over-year revenue growth. Hardware-based verification has become a must have part of the customers design flow. And on the heels of a record year, our Palladium Z2 and Protium X2 hardware platforms delivered a record Q1 as market demand remained strong for these best-in-class solutions. With 14 new customers and nearly 30 repeat customers, more than 50% of the orders during the quarter included both platforms. Demand for hardware was broad-based, with particular strength seen in the aerospace and defense and automotive segments. Our new Verisium platform leverages big data and AI to optimize verification workloads, boost coverage and accelerate root cause analysis of bugs. Customers are realizing significant efficiency gains, with Renesas seeing up to a 6x improvement in debug productivity, shortening the time to market for its R-car designs. Our digital IC business had another solid quarter, with our digital full flow continuing to drive growth especially at the most advanced nodes at market shaping customers. Our innovative Cadence Cerebrus solution provides customers an AI-driven cockpit by applying generative AI to explore the entire design space and intelligently optimizing the digital full flow in a fully automated manner. Cadence Cerebrus now has well over 180 tapeouts. And at last week's CadenceLIVE event, several leading customers including TI, Renesas, Broadcom, Canon and arm described the remarkable benefits they realized with Cadence Cerebrus. Our system design and analysis business, which is driving our expansion beyond EDA, continued its strong momentum in Q1, delivering 27% year-over-year revenue growth. Accelerating hyperconvergence between system and silicon domains requires seamlessly integrated chip implementation, system design and analysis solutions. Our Integrity 3D-IC platform exemplifies that by natively integrating all the required engines to provide a comprehensive multi-chiplet and advanced packaging flow. Additionally, the growing complexity of designs as well as accelerating of virtual prototype trends require sophisticated multi-physics solutions that not just provide higher capacity and performance but also result in more optimized designs. Our system analysis portfolio couples our expertise in physics-based modeling with AI-driven optimization and are delivering superior results to customers across multiple end-markets. We are pleased with the new wins and growing repeat orders for our organic Clarity and Celsius products, as well as our CFD technologies. During Nvidia's GTC2023, Nvidia CEO Jensen Huang talked about our joint partnership, and the throughput and energy efficiency benefits offered by Cadence's CFD offerings running on Nvidia's accelerated computing platform. And last week, we announced a multi-year technology partnership with the San Francisco 49ers that's focused on sustainability and based on our Future Facilities digital twin technology. In summary, I'm pleased with our Q1 results. Exploding chip and system design complexity will drive a significant non-linear growth in the workload requirements, opening up a massive opportunity for computational software to help realize these innovative products by investing more of the R&D spend in automation. In addition to our strong business results, I am proud of our high-performance inclusive culture and thrilled that we have been selected yet again by Fortune and Great Place to Work as one of the 2023 100 Best Companies to Work For, for the ninth consecutive year. Now, I will turn it over to John to provide more details on the Q1 results and our updated 2023 outlook.
John Wall: Thanks, Anirudh, and good afternoon, everyone. I am pleased to report that we exceeded our key financial and operating metrics for the first quarter of 2023. As planned, we increased our hardware production capacity to improve delivery lead times, resulting from strong demand for our hardware solutions. Here are some of the financial highlights from the first quarter, starting with the P&L. Total revenue was $1.022 billion. GAAP operating margin was 31.6% and non-GAAP operating margin was 42.1%. GAAP EPS was $0.89 and non-GAAP EPS was $1.29. Next, turning to the balance sheet and cash flow. Cash balance at quarter-end was $917 million. Operating cash flow was $267 million. And we repurchased $125 million worth of Cadence shares. Before I provide our outlook for Q2 and the year, I'd like to highlight that it contains our usual assumption that the export control regulations that exist today remain substantially similar for the remainder of the year. Also, for the year, we continue to expect our revenue mix to be consistent with the 15% upfront and 85% recurring revenue mix that we experienced in 2022. With that in mind, our updated outlook for fiscal 2023 is: revenue in the range of $4.03 billion to $4.07 billion; GAAP operating margin in the range of 30% to 31%; non-GAAP operating margin in the range of 41% to 42%; GAAP EPS in the range of $3.26 to $3.34; non-GAAP EPS in the range of $4.96 to $5.04; operating cash flow in the range of $1.3 billion to $1.4 billion; and we expect to use approximately 50% of our free cash flow to repurchase Cadence shares. For Q2, we expect: revenue in the range of $960 million to $980 million; GAAP operating margin in the range of 29% to 30%; non-GAAP operating margin in the range of 40% to 41%; GAAP EPS in the range of $0.73 to $0.77; non-GAAP EPS in the range of $1.15 to $1.19; and we expect to repurchase approximately $125 million worth of Cadence shares. As usual, we've published a CFO Commentary document on our Investor Relations website, which includes our outlook for additional items, as well as further analysis and GAAP to Non-GAAP reconciliations. In conclusion, we had a good start to the year. With the increase in our outlook, at the midpoint, we now expect revenue growth for the year at approximately 14%. As always, I'd like to close by thanking our customers, partners and our employees for their continued support. And with that, operator, we will now take questions.
Operator: Your first question comes from the line of Gary Mobley with Wells Fargo. Your line is now open.
Gary Mobley: Good afternoon, everybody. Thanks for taking my question. I wanted to ask about an observation that is your upfront revenue, your functional verification revenue and your China-related revenue were all very strong in the first quarter. So, I'm curious to know if all those were related and relate specifically to maybe some pull-forward of some customer deliveries or some customer orders, or was it more so a function of having the ability to turn the hardware verification business around a little bit quicker than expected?
John Wall: Yes, Gary, great question. And, yes, they're all related. We were very pleased to be able to ramp up the production of our hardware because we had such strong demand for hardware solutions in the functional verification business. We successfully ramped that up in Q1 and the subsequent upfront revenue benefited functional verification, it benefited China. I think China is up to 17% of our revenue for Q1, that's mainly hardware driven. And again, we wanted to reiterate the fact that last year we did -- our recurring revenue mix was 85% of our total revenue, 15% upfront. We still expect that to be the case for this year. But in Q1, because of the increased hardware deliveries, the mix was 80% recurring and 20% upfront for the quarter. We wouldn't expect that to repeat for the rest of the year.
Gary Mobley: Okay. And related to that, John, if I'm not mistaken two-and-a-half months ago, when you gave the initial fiscal year '23 revenue guide, you were expecting maybe the hardware-related business to tail off into the second half of the year. Is that still the expectation? Or are you still running near record backlog for that hardware verification business? And that's it from me. Thank you.
John Wall: Great question again, Gary. Yeah, we were very pleased with hardware bookings again in Q1. We didn't take up the second half of the year. I want to wait until the summer to have a look at the pipelines, because hardware is very much a pipeline business. However, we did take up the year by $20 million, and part of that is the beat in Q1, which was some hardware. But the rest of that was strength on the software side, probably predominantly in the system design analysis space. And we raised that for the year, and that's kind of recurring throughout the year. But we haven't taken up second half of the year for hardware. I'd like to wait until the middle of the year for that. We still expect -- I mean, we expect all the businesses to grow strongly this year.
Gary Mobley: Thank you.
Operator: Your next question comes from the line of Jay Vleeschhouwer with Griffin Securities. Your line is now open.
Jay Vleeschhouwer: Thank you. John, for you first on RPO, according to the 10-Q, it looks like you had about $400 million sequential decline from the end of -- from Q4, and also a sequential decline in the next 12 months expected revenue from RPO. And I know that can move around, of course, with hardware and contract timing and so forth, but maybe just talk about the magnitude of that sequential decline in RPO and perhaps any expectations for that for the remainder of the year? And then, my follow-up.
John Wall: Yeah, sure, Jay. The second half of this year is very heavily weighted for bookings for the total year. We're very light in the first half of the year for software renewals. The second half of the year, Q3 and Q4, are very strong for software renewals this year. Unlike last year, last year, I think the first half was we had a number of big software renewals in the first half, we don't have that this year. And when you look at the second half, of course, I mean any big renewal you have in Q3 -- at the end of last year, we had like nine months in cRPO for that and now it's only six months at the end of this quarter. So, it's really just a function of renewal timing and the fact that the first half of the year is light for renewal timing. I'd remind you as well this in terms of renewal timing, the Q1 and Q2 are the two quarters that's kind of -- are like three years after the breakout of the pandemic back in 2020. So, those were light for us anyway in terms of light renewals. So, the second half of the year, much more heavily weighted towards the second half of the year for software renewals, and you see that impact on the RPO and cRPO. To a lesser extent, there was some a drop off on hardware because we delivered so much hardware in Q1, but it's mainly the timing of renewals.
Jay Vleeschhouwer: Okay, understood. Anirudh for you on AI, the product launches in the last couple of weeks, including last week, and the customer presentation was certainly very interesting. But just want to ask you about management comment at the conference last week that you were making "massive investments in AI." And what was interesting about that is just some of the ad hoc conversations at the conference suggested that the AI development teams are relatively small, perhaps a few dozen per product or per group, but not necessarily very large percentage of your R&D headcount. So, when you say massive investments, in what other ways perhaps do you mean that?
Anirudh Devgan: Yeah, Jay, good question. So, I think first things I would like to say just to add on to what John was saying earlier, I mean, there could be some fluctuations in renewal timing. But the great thing about our business is we are not sensitive to that, right? I mean, it's mostly ratable business and -- but what I'm pleased to see is that both in system and semi companies that design activity is very strong, okay? Because a lot of these products are -- I mean, we are resilient to the overall kind of macro environment. So, resilient because our products are critical and essential. And then, we are mostly ratable business. And then, we are very diversified, as you know, both geographically and markets. Now in terms of AI, I mean, this is having -- of course, having a significant effect in terms of amount of automation we can provide and the increased automation we can provide. So, we are embedding that, as we mentioned in our CadenceLIVE Conference last year in all products. And it will be pervasive throughout the product line. So, I'm actually pretty pleased to see not only our base kind of JedAI platform, which is you need a data analytics platform to really do AI in intelligent comprehensive way. But also, there are five big platforms on top of JedAI, so from chip to package to board to system. So we always had Cerebrus, which is doing phenomenal with more than 180 tapeouts; Verisium for verification; now Studio, Virtuoso Studio for analog with layout migration and design centering using AI; and then, X AI for Allegro, PCB and packaging, and Optimality for system design and analysis. So, it's a very comprehensive portfolio. And amount of R&D investment just depends on different products. And sometimes we have it within the product, sometimes we have outside, but it will be pervasive through the product portfolio. And like I have mentioned before, our strength in computational software naturally allows our regular -- even regular R&D to do a lot of AI. We, of course, have AI specific R&D, but our regular R&D, given the rich history of EDA and competition software, we can embed that in our product. So, the real value is to really do it comprehensively and make a big difference in terms of productivity, in terms of automation, in terms of PPA benefit that we are delivering to the customers.
Jay Vleeschhouwer: Okay. Thank you, both.
Operator: Your next question comes from the line of Charles Shi with Needham & Company. Your line is now open.
Charles Shi: Good afternoon. Thank you for letting me ask a question or two. So, we really just want to go back to the second half EDA renewal, the expected strength. May I ask those expected renewals, are they already in the backlog or not? Or are they not in the backlog, you expect to sign the renewal in the second half of the year? That's my first question.
John Wall: Yeah. So, Charles, yes, just for clarification, all of our renewals will be -- already be backlog. But if there's, let's say, you have a renewal that's coming up in September, you would have had nine months of backlog left on that renewal at the end of Q4 last year. Now, you have six months left in backlog. And then, when you get to September, you'll have nothing left in backlog and then you have the renewal will come through.
Charles Shi: Okay. So, those renewal contracts are not yet in your current backlog, that's what you're saying?
John Wall: So, the new ones will not be until we do them in the second half of the year.
Charles Shi: Got it. So, may I ask -- yeah, go ahead, please.
John Wall: So, that -- I just wanted to clarify that. Yes, the -- so the remainder of the existing bookings will be in backlog, but that will reduce until we get to the actual renewal date. And then, on the renewal date, we'll have a new booking come through.
Charles Shi: Got it.
John Wall: And that will be additive to the back up.
Charles Shi: Got it. So, just want to really fear this up. I think another analyst just asked about -- the implied booking seems to be down in Q1. And I think you did provide some color, but I want to ask from another perspective. I think in March 2021 quarter, if you still remember the details, that -- in that particular quarter, you had some similar relatively lower bookings back then. And now, in hindsight, it looks like it was just some one-off weakness in bookings and not meaning much in terms of the broader industry trend. Is that the same case this time? Or are you seeing some other more like a trend -- indicative of the trend going on in the industry today? Thank you.
John Wall: Oh, thanks for the opportunity to clarify there, Charles. Certainly, I didn't see any weakness in bookings in Q1. Bookings in Q1 were stronger than we were actually expecting at the start of the quarter. What I was trying to convey was that we had very few software renewals that came up for renewal in Q1 and therefore bookings were expected to be light. The beauty of the recurring revenue model that we have is that the timing of those renewals is not especially important, but it's the annual value of those renewals. And that we continue to see growth in the annual value of those bookings, and we see growth across all of the businesses.
Charles Shi: Thank you, John.
John Wall: Thanks.
Operator: Your next question comes from the line of Harlan Sur with J.P. Morgan. Your line is now open.
Harlan Sur: Hi. Good afternoon, and nice job on the strong quarterly execution. We had a call last week with one of the largest ASIC semiconductor companies, a very large customer of yours, that they've got chip design programs with many of the cloud and hyperscalers. And they told us that they're seeing a pickup just over the last sort of 60 to 90 days, just the meaningful pickup in design activity and design project pull-ins on their accelerated compute and AI SoC programs from their hyperscale customers. I guess, it's not a surprise given the AI arms race amongst the cloud titans. But have you seen this recent pickup in customer design activity, program pull-ins reflected in your recent discussions on upcoming renewals and/or customer engagements?
Anirudh Devgan: Yeah, Harlan, that's a great point. So, in general, like I mentioned earlier, I mean, there is a lot of strong design activity. We see with our customers, both on the semi and the system side, and when I talk to our ecosystem partners, right, the foundries and the IP providers. So overall, I think design activity is very strong. Now, in particular, to your specific question on AI, I definitely see a lot more interest. And the reason is, I mean, you know -- I mean, at least one of the reasons I think in which we know -- or you may know already is this new kind of generative AI and all this talk about ChatGPT is that, traditionally search or this kind of AI inferencing the past was done on -- in a CPU. But this new generative AI tools, of course, the training is done on GPUs as always, but even inferencing, when you ask it a question, a lot of the inference is done on GPUs, which is traditionally -- it's a great accelerating platform, but traditionally more expensive than CPU platform. So, not only it will drive more and more adoption of GPU and accelerated computing in the cloud, but also naturally look for customized silicon that can do it much more effectively and efficiently both for performance and power. So, we do see generative AI and adoption of this more reinforcement learning based kind of inference -- training an inference, especially the inference part of it, to drive more silicon demand and more customized silicon, and which is -- which you are correct in your observation. But in general, right, we have talked about for several years, the need for customized silicon, whether it is for generative AI now or in general for self-driving or variety of applications is expected to continue, and we are pleased to see continued momentum in that space.
Harlan Sur: No, I appreciate that. And then, maybe just a follow-on to that question, many of your cloud and OEM customers that historically have worked with these large ASIC companies, we're also hearing that some of them may be trying to build extra distance, right, and pull together the capability to do the entire chip design themselves, right, what we call COT based models, which I would think would mean further expansion of their design teams beyond just front-end design, right, which again would be maybe more market opportunity for things like your Virtuoso franchise, and many of your back-end physical implementation of verification tools. Are you guys seeing this trend as well?
Anirudh Devgan: Yes, absolutely. So, I think if you look at this kind of transition of system companies doing their own silicon, I think there are at least three phases of that. And that's why I've commented in the past that we are still in the second inning of this. And you can look at other companies, like, in the mobile space when they started doing their own silicon. So, the first phase is using ASIC provider. And, actually, we have great relationship with almost all the major ASIC providers. We have very deep partnership with all the -- in all geography, world-leading ASIC providers. But typically, the system companies will start with the ASIC provider, but then typically go to a COT flow, or customer owned tooling. And in that, they will do more and more back-end design and more and more -- so usually that is more opportunity for Cadence. And so that the front-end and back-end can be optimized together. I mean, the ASIC provider can do that too, but typically, the customer will go to a COT flow over time. So that's one thing that really -- has already happened in other system companies, is happening in the newer ones. And the other trend, of course, is that they will do more and more designs also. Initially, they'll start with one or two designs like -- and as you can see these examples in all the public ones, like Amazon doing in the beginning in networking chip. And once that networking chip is successful, they moved to graviton, which is a compute server. And then, once that's successful, they go to a AI chip. So, the number of chips also increases. And then, the third reason that there is more and more business is new system companies get in. Traditionally like in the auto space, in the beginning, only one or two will do it, and then more companies will do it. See, that's why I think there is a growing trend will last for a while because there is companies moving from part of the flow in-house to full flow in-house, which is moving to COT from ASIC; more and more designs being done; and thirdly, more and more companies doing silicon. So, all these three trends are positive for Cadence and the products that we supply.
Harlan Sur: Yeah, insightful. Thank you.
Operator: Your next question comes from the line of Jason Celino with KeyBanc. Your line is now open.
Jason Celino: Hey, thanks, guys. Just two questions from me. Maybe my first one, John, you mentioned taking up the full year guidance based on some strength in system analysis. I'm curious, was this driven more from your existing business there, or was it from OpenEye? I guess, how is OpenEye doing relative to expectation?
John Wall: Yes, Jason, so we took up the year by about $20 million, about half of that was with hardware from Q1 because that was a big portion of the beat in Q1. And the other half of that was spread across our software business, mostly in the system design and analysis space and mostly organic. But there was some inorganic contribution as well.
Jason Celino: Okay. And then, my second -- sorry, go ahead, Anirudh.
Anirudh Devgan: Go ahead, Jason.
Jason Celino: Oh, sorry, yes. And then, my second question on the guide, it looks like second quarter is going to decline sequentially by about 5%, consistent with what we saw last year too. So maybe just a quick refresher on what's driving the seasonality here?
John Wall: Yes, Jason, when you look at it, it will be -- it'll show up in the functional verification number next quarter. I think the -- when I look at -- like Q1 was great. I mean, functional verification was up 30% year-over-year. The quarter was up low teens. When I look at Q2, Q2 also looks great. It's going to be up low teens again compared to Q1 '22, but functional verification will be up probably closer to 20% rather than 30%. But -- so, it's our expectation that in our guide, we're assuming that the recurring revenue mix for the year stays at 85-15, 85% recurring, 15% upfront, same as what we experienced last year. Now, in Q1, it was 80%, 20%, so there was a lot of open revenue for the hardware deliveries that went out in Q1. In Q2 -- we expect Q2, Q3, Q4 to be less than the 80-20, and it will average 85-15 for the year. So, you're seeing that in the Q2 guide.
Jason Celino: Okay. Excellent...
Anirudh Devgan: Also, Jason, just to add on to what John said, if you look at the Q2 guide, we're still up nicely from Q2 of last year.
Jason Celino: Okay. Awesome. Thanks for the clarification.
Operator: Your next question comes from the line of Vivek Arya with Bank of America. Your line is now open.
Vivek Arya: Thanks for taking my question. I had a near term and then kind of a bigger picture question. So near term, your IP sales have slowed down. I think, for three quarters now, I think they are actually down year-on-year. I'm curious on what's -- Anirudh, what's driving the slowdown? And do you expect IP to grow in line with the 14% sales growth for the entire company? What will help those sales reaccelerate in the back half?
Anirudh Devgan: So, Vivek, in general, IP is still a good business, and we expect, in 2023, IP business to grow in the low teens compared to last year. So, there is some quarter-by-quarter fluctuation, but in general, we expect IP business to perform well in 2023, yes.
John Wall: And so, yes, and what I would add to that is that -- and you know what, IP revenue generally can be lumpy because some of it's upfront and it's based on the timing of deliveries. Now last year, our IP revenue, we had more deliveries that fell into the first half compared to the second half. This year, it's the other way around, we have more IP deliveries that fall into the second half compared to the first half. So, it kind of skewed the year-over-year numbers, but we're very, very pleased with the performance of the IP business. As Anirudh says, we're generally targeting increasingly profitable low-teen growth every year for our IP business, and we're on track for that.
Vivek Arya: Got it. And then my bigger picture question is, what is the right kind of public metric to gauge how much benefit you're getting from AI? Is it accretive to your pricing to your growth rate? So just what is the best public metric to appreciate how much benefit you're getting from AI? And is there a scenario where just the improved productivity, right, or accuracy that AI provides, could it even cannibalize some of your hardware or software part of the business, or do you think it's kind of net accretive longer term, just given the larger TAM size and the greater customer engagement? So, just what have you seen so far from AI? What is the best way for us to track how much incremental benefit? And do you expect it to be net accretive over time?
Anirudh Devgan: Yes, Vivek, what I would say qualify AI is another way of providing dramatic automation, that's -- and this history of our industry is to provide more and more automation. And I would say AI is like third wave of massive automation and productivity improvement. I mean, the first wave was moving up abstraction level going from transistor level to gate level to RTL level to C level. That's one wave that drove our industry, which is -- the second wave in the last 10 years is parallelism. Cadence has invested heavily in massive parallelism whether it's on-prem or on the cloud, and starting from 2013, we have a lot of paddle products. And then, now, the third wave of productivity and automation is using AI or what I always call AI for optimization now called reinforcement learning or generative AI. So, we have a history over the last 20, 30 years of doing this kind of -- and in all cases, it doesn't cannibalize. Actually, the activity increases and amount of software used and amount of optimization that happens, more and more designs are done with the available resource headcount. So I expect AI to do that. I mean, in general, the benefit is so huge that when you get these new capabilities, you use it to do much more efficient design. Okay. I'll give you an example, starting to -- some very senior people in our industry, and one comment has been that the Moore's Law has slowed in terms of actual improvements you're getting from one node to another node, when you went from 65 to 40-nanometer, you get X amount of improvement, and now when you go to 5 to 3, that used to be 20%, now is -- they went to 50%, now maybe it's like 10% improvement. And even our tools like Cerebrus or a lot of the other AI-based tools can provide easily 5% to 10% improvement in PPA. So you are getting improvement from better algorithms, which are similar to half or full node of a process technology improvement, okay? And that's just huge. The amount of improvement you can get from this third wave of automation using generative AI is huge. So -- and I think that's one metric that we have published a lot in terms of how much PPA and product improvements we are getting, and that's what we closely monitor with our customers. And I think -- and the other thing is to apply that across other things, not just digital implementation, to apply to package design, to board design, to simulation. And what I think it -- opportunity it gives us is, over time, we can get higher share of R&D invested in automation, because the complexity of these things is going up exponentially, so the headcount can't go up exponentially. So, the headcount, I expect, still will grow five, 10 years from now in terms of R&D spend in our customers, but we can get a bigger share of that R&D spend applied to automation.
Vivek Arya: Thanks, Anirudh.
Operator: Your next question comes from the line of Gianmarco Conti with Deutsche Bank. Your line is now open.
Gianmarco Conti: Hi, there. Hi, Anirudh and John. Thanks for taking my questions. So, on my first one, I just want to touch base again on the AI suite piece. Firstly, whether you're entering a more mature phase of the price discovery mode as you're accelerating volumes? And secondly, perhaps thinking about the specifics of what are the AI demand drivers here, whether those are correlated to increased design at the lower nodes, are there other trends that we should be aware of other than the increase in complexity, i.e. some specific trends in the industry that you're seeing beyond the semi players, particularly as you've mentioned, of course, optimality in SD&A? Is there anything that we can sort of like track or understand what's going on behind the bonnet? I'll ask a follow-up question after. Thank you.
Anirudh Devgan: Absolutely. I think, we talked about chip, right, and how AI can help this third wave of automation. But the same thing can be applied at package and system levels. I do want to highlight that. We have talked for a few years on importance of merging system and semi and how system companies are doing semi and then we can also provide solutions for system design and analysis like thermal simulation, electromagnetic simulation, fluid dynamics. And traditionally, those areas were -- first of all, the simulation capabilities were -- could be improved, just the raw simulation speed. So, for example, Clarity for electromagnetic, we got order of magnitude improvement versus traditional methods, because applying our computational software expertise, we can do a lot more simulation. But on top of that, there are two other things that can jump to our system design and analysis, and you're seeing that even our growth that you're seeing. So, one thing is use of GPU acceleration. And we talked about this in my prepared remarks. And I think GPU acceleration is significant for system design and analysis there. And the other thing is applying AI on top of simulation. So, EDA has a long history of optimization, not just simulation. An AI for optimization of generative AI is really new for system design and analysis, because they are barely -- even the simulation capabilities were not keeping up, but they didn't really have that much optimization capability. So, the response we are getting from Allegro X AI and Optimality is huge, because not only simulation is possible for the first time, but the optimization of simulation. Because in general, if you're doing some thermal design or design of the data center, yes, you want to stimulate of a car, but you want to optimize, whether it's the shape of the wing or placement of the racks in the data centers. And all this is really now possible with generative AI. So, I think the impact on this SD&A will be profound apart from the impact on chip design. And we are the company that can combine those two things and apply AI to both of these areas.
Gianmarco Conti: Great. Thank you. And just my second one is on M&A, whether there's any M&A in sight or plan on increasing the portfolio perhaps in SD&A -- sorry, in systems and analysis, or is 2023 consistent with the plan of distributing cash to shareholders via buybacks?
Anirudh Devgan: Yes. I mean, in general, we want to start with the strategy, and we feel we have a very, very strong strategy with intelligent system design, this combination of silicon system and data. And we are very pleased with our progress, and we continue to grow organically and perform well both in terms of revenue growth and margin. So that's our base strategy, base outlook. Now, we always evaluate M&A as it comes up and if it's a good return for our shareholders and good return in terms of R&D. But in general, we are pleased with our strategy and our organic execution.
Gianmarco Conti: Got it. Thank you.
Operator: Your next question comes from the line of Blair Abernethy with Rosenblatt Securities. Your line is now open.
Blair Abernethy: Thank you. Just a quick question on the multi-physics side of things, the system design. The growth, I think you called it, was around 27% year-over-year. Just want to clarify, was that including the acquisitions, or is that organic? And then, secondly, just on the multi-physics side of things, how are you doing in terms of your go-to-market strategy and scaling the business up? It looks like it's getting close to a $500 million run rate. Just want to see how you're doing in the go-to-market side of things.
Anirudh Devgan: Yes, absolutely. The growth rate is a combination of organic and inorganic, right, the acquisitions we made in the past. And in terms of go-to-market, we have -- of course, there is a lot of overlap with our current customers, too. And then, of course, some of the customers are new customers. So, we try to leverage both our existing channel, and then we also have set up a system kind of sales team that targeted new customers that we traditionally haven't talked to. But one thing to remember in SD&A, as this overlap of system and semi companies, lot of the leading companies in SD&A are companies that Cadence already has a very deep relationships. So -- and we are still selling to the engineering organizations and it's just -- so the good part is both the EDA and the SDA, our engineering software maybe different parts of the customers are engineering organization, but more and more coupled engineering organization with the combination of system and semi. And then, when we go to SD&A side, we always look at a three-pronged approach in terms of go-to-market. So, one is direct sales, like we do for our EDA business. And that -- we have great relationship with the top customers in the world, which are consuming both EDA and SDA. And then, I think in SD&A, there is a bigger portion of indirect or channel. So, we had a strong channel for our Allegro and OrCAD businesses, which is PCB and packaging, but we have expanded the channel to now include SD&A to bring our new channel partners throughout the world. And then, the third part of our go-to-market is using cloud and OnCloud, we announced last year. So go direct, especially for smaller customers who don't want to have in their own IT department and especially in the systems space, they are much more amenable to direct SaaS kind of cloud offering. So, overall, this is an ongoing progression. As you said now the business is getting to a good scale and especially in SD&A, we want this three-pronged approach of direct, indirect plus cloud. But one thing to remember is a lot of the top customers in SD&A are already existing EDA customers, and that really helps us as we go to go-to-market.
Blair Abernethy: That's great. Thanks, Anirudh.
Operator: Your next question comes from the line of Ruben Roy with Stifel. Your line is now open.
Ruben Roy: Thank you. Thanks for taking my questions. John, I had a question on the commentary around renewals. And just thinking back to the pandemic and how you guys thoughtfully took into account some of your smaller customers and how that might impact some of your software renewals. Just wondering, given the state of the economy right now, and we've already seen some slowing in IT spending, do you think you might see some uncertainty given the soft macro and renewals in the second half? Are you calibrating that into your thinking for full year guidance at this point, or is that not something that you're worried about?
John Wall: Yes, Ruben, I'm not really worried about that in the second half in terms of the renewals. The renewals are with really large very, very highly creditworthy customers. But we did see some softness in the lower creditworthy Tier of customers like start-ups in Q1. And we have already factored that into our guidance for the year -- for both Q2 and for the year. But generally, at the high end with the big renewals are with like the strongest creditworthy customers in the industry.
Ruben Roy: Right. Got it. Thank you, John. And then, a quick follow-up for Anirudh on the hardware. It's come up now a few times, Anirudh, on your call, which is nice to see that the take rate, or attach rate, I should say, of hardware continues to move up. The numbers have been quite strong, obviously. Is there a way to think about the percentage of your customers now that are on the new Palladium and Protium systems? Just wondering if there's a continued refresh cycle coming around that relevant metric at all to think about kind of what the percentage of customers is. And that continues to go up, is 85-15 sort of the right way to think about the longer-term mix for the company?
Anirudh Devgan: I mean the good thing with the hardware is that, like we mentioned in the past, like it has become almost an essential part of the design process. So -- and it's almost -- it's virtually impossible to design these complex chips without use of the hardware platforms. So, I would say all the major customers, especially all the big major customers that drive most of our revenue are using hardware anyway. Now, there is -- so there's always room for refresh of that of the hardware they're using. And also, as the chips -- as they go to different nodes -- I mean we are like 5-nanometer going to 3, to 2, to 1.4, to 1, so there is at least 10 years of node refresh ahead of us. So, every time we go to a new node, the size of the chip increases, the number of gates that are on chip increases. So, you typically need more and more hardware. So, the capacity requirement for hardware increases. So that's why I think that for long term, hardware is going to be in a secular growth period. Not only is it critical, but you need more and more and that's going to last for at least for the next 10 years, if not more. And then sometimes, there's opportunities for some of the smaller customers to add hardware, and we look at that also, and we have a variety of business models to help the smaller customers. But at this point, most of our big customers are using hardware, but still there is growth because the chip size increases, or if they're using Palladium, they can use more Protium and vice versa.
John Wall: Yeah, I would just add to that, Ruben, that I think your question emanates from the fact that back in 2021, I think our recurring revenue to our upfront mix was 88-12. And of course, that grew the upfront. And hardware was so strong last year, it went to 85-15. And of course, we're guiding to the year of 85-15 now. Without -- with the caveat that we're going to take another look in the summer, and we may take the second half up if we see continued hardware strength, because strength continued into Q1. And although we're guiding 85-15 right now, I would take the over on the 15 rather than the under.
Ruben Roy: That's really helpful, John. Thanks. I guess, just really quick, I know I'm only allowed one follow-up. But just on that point, have lead times normalized, would you say, or is there more work to be done on the production side?
John Wall: We should get back to more normal lead times by the middle of the year, but we thought it was really important in the first half to prioritize deliveries to customers that have been waiting the longest for the hardware. I mean, as you know, we have multiple uses for the hardware. We want to set up demo models for customers for future sales and things like that. But the first quarter was heavily weighted towards deliveries to customers that have been waiting a long time for those orders. We're still working through those lead times, but we expect to be back to more normal lead times by the middle of the year.
Ruben Roy: That's great. Thanks, John.
Operator: Your next question comes from the line of Joe Vruwink with Baird. Your line is now open.
Joe Vruwink: Great. Thanks for squeezing me in. I wanted to take another crack at the topic of AI and adoption. So, when you think about -- maybe the best example is Cerebrus, within implementation efforts, if you think about the total block engineers as an account, what share of those engineers are typically using the product at this point? And in your mind, is that something as we enter the next round of renewals, it could get more widely deployed across the entire team?
Anirudh Devgan: Yes, Joe, what I would say is that, I mean, like we talked about, I think, out of top 20 customers, I think 10 of them are using Cerebrus for production. And then, we are engaged with all the top customers and then five hyperscalers are using. And I think -- but still it's not -- I think there's still a lot of opportunity for growth there. Because the way I look at it is, especially Cerebrus or JedAI or all these platforms that I think over time, they will become the cockpit. So, in the old days, in case of digital implementation, Innovus was the cockpit. So, the customers would run in Innovus or try different experiments with Innovus. But now Cerebrus can do that mathematically with AI. And then, you can still combine that with the -- you can still do manual experiments on top of that. So, I think overall, I would expect in three to five years, almost all designers would be using Cerebrus what they were using Innovus in the past, okay? And same thing with Optimality, same thing with Allegro X AI. So, we are still ways from that. So, there is still this progression that has to happen. So, I think we are engaged with all the customers. They're using it. But I think over time, it will become the dominant way of running products will be using Cerebrus rather than using the old way. It's like going from manual cars to automatic cars. Some people may still want to drive manual, but more and more people will drive automatically using Cerebrus. So, I think in that, we are still in the early innings. So, it's still like years to go in that. And that's good. We are -- in our business, like we mentioned earlier, we're looking at annual contract value and let the natural adoption happens over the next few years.
Joe Vruwink: Okay. That's great. And then, on the system design segment, can you -- I don't think I heard it, just an update on where you expect growth to be in 2023? And then, in reflecting on the development here and kind of the upside you're seeing in bookings, is it possible to pinpoint at something like -- you talked about the repeat orders on the organic solvers. You've obviously built a bigger CFD business. There's some new channel initiatives. Are any of these things more important than others in terms of driving the upside you've seen?
Anirudh Devgan: I think 2023, I still expect a very good year for system design and analysis. In terms of initiatives, I think there are a whole bunch of initiatives we are driving. I think what we always say is we are obsessed with best-of-class products first. So that's the most important thing. If the products are differentiated, the customers always use it. And all these channel initiative helps, and awareness of our products with marketing helps. But in the end, we are always focused on developing and supporting making best-in-class products. So on that, we've made a lot of progress and benefits. I mean, recently, I talked about it in my prepared remarks. But one thing I think in system design and analysis, like I mentioned, I'm very optimistic about use of GPUs. And GPUs have done wonders in AI, right, by accelerating AI computation. And traditionally, GPUs haven't worked that well in EDA. They do help EDA, but it can dramatically help SDA, because SDA is a more kind of the -- it's more physics-based simulation. So, it's more kind of matrix multiply, which is similar to (ph) AI. So, like recently with our collaboration with NVIDIA, Jensen talked about that Cadence CFD on GPU for the same cost is giving a 9x improvement in speed up and 17x improvement in power efficiency. And GPUs are slightly more expensive than CPUs. I mean, typically, I would guess, at least 3x to 5x. So, you're getting 30x to 50x speed up on GPUs that normalized for cost is still getting 10x or 9x improvement in speed. So that's a huge improvement based on our special algorithms, because we have a long history of massive parallelism in CPUs and now we are applying it to GPUs, both especially in SD&A, both for electromagnetic and CFD. So, I think that can also provide a lot of growth. I talked about AI and all for chip and system, but this acceleration on GPUs, accelerated compute for system analysis is another big vector. And even in OpenEye, we use GPUs for acceleration. So, I think that's -- we have multiple ways to accelerate our position in SD&A, but we're always focused on best-in-class first, right?
Joe Vruwink: Thank you.
Operator: Your next question comes from the line of Andrew DeGasperi with Berenberg. Your line is now open.
Andrew DeGasperi: Thanks for fitting me in. I guess one question I had is, and I know you've talked a lot about AI on this call, but just wondering if you think this could potentially lead to more pronounced market share shifts in the future? I know historically, there's not been a lot of market share changes in EDA. But just wondering if we thought with the portfolio that you have relative and your investments that you made relative to your competitors, do you think that could change?
Anirudh Devgan: Yes, that's a good point. I mean, in general, like I mentioned, we're always focused on best-in-class right, so and that AI can play a big role in that. But I do think that the real opportunity for the industry, both for EDA, SD&A is more and more share of R&D going to automation. I think that will be good for all players, of course, we invest heavily. We want to have best-in-class solutions in our products. But I think the bigger trend will also be -- these things are getting so complex. There's not going to be enough headcount to design these things five, seven years from now. So, the bigger opportunity for the entire industry is more shift to automation, and that's, I think, good for everyone.
Andrew DeGasperi: That's helpful. And then -- sorry, go ahead.
Anirudh Devgan: Yes, please.
Andrew DeGasperi: No, go ahead.
Anirudh Devgan: I mean yes, the other thing I think the way we are unique is not just apply best-in-class products in EDA, but we combine chip and systems. I think that's also provided us unique differentiation with our customers and our market position. And that's the strategy we have been implementing for the last four or five years. And applying AI improves our EDS solution, but also the combination of EDA plus SDA and computational software, that also improves our competitive position in the market.
Andrew DeGasperi: That's helpful. And then, maybe on just general trends this quarter. Just wondering in terms of the systems business, have you seen any change, particularly in the data center side in terms of demand, or is it being kind of consistent relative to the previous quarters?
Anirudh Devgan: I think that -- I mean you know the news is -- I mean it's a tough environment for our -- in general, with all the news. But in general, like I said, the design activity is strong, okay, and so -- and our results are strong. I think the data center customer is still invest heavily in automation and R&D. And the new uptick like beginning of the call we talked about, the new uptake, I think, is more to the infrastructure to serve generative AI. I think that's definitely a very active area for the big data center companies, because these things are really complicated and complex to serve this whole generative AI base. So, that will require use of specialized hardware, also different kind of hardware mix in the infrastructure. So, I think that's going to be a change, and that's good for our opportunities for us.
Andrew DeGasperi: Great. Thank you.
Operator: Your next question comes from the line of Arsenije Matovic with Wolfe Research. Your line is now open.
Arsenije Matovic: Hi. This is Arsenije on for Josh. So, just a double click on the systems company strength. And I wanted to see if there was any kind of call-outs, in particular end markets, and how many dealerships the end markets have changed relative to last year, or any kind of outlook changing in terms of end market demand within those companies? Thanks, and then a quick follow-up.
Anirudh Devgan: Well, I would say that in system companies, data center is always a lot of activity driven by generative AI. And I think we mentioned also in our prepared remarks, automotive and A&D are definitely -- we're seeing a lot of design activity in those. So, I would -- if you have to pick like a few verticals, so definitely data centers with AI and then automotive, AI, in general, but also electrification and more A&D, and we are seeing that in our own engagements with customers.
Arsenije Matovic: Got it. And then, if we could kind of think about some of the strength in hardware, how much of that is driven from refresh from existing large semi customers versus maybe new purchases from systems companies? If you kind of like quantify that from a high level would be helpful.
Anirudh Devgan: I think it's a combination of both. It's both like the system -- the semi company has more designs, and newer designs require more and more hardware. And system companies, by its nature, also have software. That's -- otherwise there wouldn't be system companies. So, in system companies, our dual dynamic view of Protium and Palladium really helps, because Protium is more for software bring-up and then Palladium for chip bring-up. So, I would say both are strong, but there is more software content by nature in the system company.
Arsenije Matovic: Thank you.
Operator: I will now turn the call back over to Anirudh Devgan for closing remarks.
Anirudh Devgan: Thank you all for joining us this afternoon. It's an exciting time for Cadence with strong business momentum and growing opportunities in the semiconductor and systems industry. We are proud of the innovative and inclusive culture we have built at Cadence. And on behalf of our employees and our Board of Directors, we thank our customers, partners and investors for their continued trust and confidence in Cadence.
Operator: Thank you for participating in today's Cadence First Quarter 2023 Earnings Conference Call. This concludes today's call. You may now disconnect.
