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 Q1 2023 Earnings Conference Call. All lines have been placed on mute to prevent any background noise. After the speaker's remarks, there will be a Q&A session. If you would like to ask a question during this time, simply press star then the number one on your telephone keypad. Thank you. I will now turn the call over to Richard Gu, Vice President of Investor Relations for Cadence. Please go ahead. Thank you, operator. I would like to welcome everyone to our Q1 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. The webcast of this call and a copy of today's prepared remarks will be available on our website, 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 in 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. We will present certain non-GAAP measures, which should not be considered in isolation from or as a substitute for GAAP results. Reconciliation of GAAP to non-GAAP measures are included in today's earnings release. For the Q&A session today, we would ask that you observe a limit of one question and one follow-up. I'll turn the call over to Anirudh. 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 Q1 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 groundbreaking generative AI solutions in the digital verification and system areas. 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 heterogeneous system design, 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 latest innovations in generative AI to accelerate PCB design with more than a 10x reduction in turnaround time. At a recent launch, it was endorsed by Schneider Electric and Kyocera. All of these powerful engines are fueled by our unique, differentiated big data analytics JedAI platform that unifies massive amount 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. 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 system companies, creating rich market opportunities for differentiated end-to-end EDA, IP, and system solutions. I'm 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. 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 system 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 RF and system analysis solutions. Cadence expanded its collaboration with TSMC and Microsoft as we leverage our Pegasus Verification System and CloudBurst platform to accelerate gigascale physical verification in the cloud. Ever-increasing complexities in system verification and software bring up continue to propel our verification business to a 31% year-over-year revenue growth. Hardware-based verification has become a must-have part of the customer's design flow. 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 40 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 tape outs, 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 technology. During NVIDIA's GTC 2023, 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. 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 nonlinear growth in 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'm 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. I will turn it over to John to provide more details on the Q1 results and our updated 2023 outlook. Thanks, Anirudh. Good afternoon, everyone. I'm pleased to report that we exceeded our key financial and operating metrics for the Q1 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 Q1, starting with the P&L. Total revenue was $1,022 million. 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. 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. 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. 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. We expect to repurchase approximately $125 million worth of Cadence shares. As usual, we 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. With that, operator, we will now take questions. At this time, I would like to remind everyone who wants to ask a question to press star, then one on your telephone keypad now. We'll pause for a moment to compile the Q&A roster. Your first question comes from the line of Gary Mobley with Wells Fargo. Your line is now open. 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 Q1. 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? Yes, Gary, great question. 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. Again, we wanted to reiterate the fact that, you know, last year our recurring revenue mix was 85% of our total revenue, 15% upfront. We still expect that to be the case that for this year. 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. Okay. Related to that, John, if I'm not mistaken, two and a half months ago when you gave the initial fiscal year 2023 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? That's it for me. Thank you. Yeah, 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 pipeline 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. The rest of that was, you know, strength on the software side. Probably predominantly in the system design analysis space. We raised that for the year. That's kind of recurring throughout the year. We haven't taken up the second half of the year for hardware. I'd like to wait until the middle of the year for that. Got it. Thank you. We still I mean, we expect all the businesses to grow strongly this year. Thank you. Your next question comes from the line of Jay Vleeschhouwer with Griffin Securities. Your line is now open. Thank you. John, for you first on RPO. According to the Form 10-Q, it looks like you had about a $400 million sequential decline from the end of from Q4. Also a sequential decline in the next 12-month expected revenue from RPO. 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 the remainder of the year. Then my follow-up. 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 we had a number of big software renewals in the first half. We don't have that this year. When you look at the second half, of course, I mean, any big renewal you have in Q3, you know, at the end of last year, we had, like, 9 months in CRPO for that, and now it's only six months at the end of this quarter. 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 that, you know, in terms of renewal timing, the Q1 and Q2 are the two quarters that kind of are like three years after the breakout of the pandemic back in 2020. Those were light for us anyway in terms of light renewals. 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, you know, a drop off on hardware because we deliver so much hardware in Q1, but it's mainly the timing of renewals. Okay. Understood. Great. Anirudh, for you on AI, the product launches the last couple of weeks, including last week, and the customer presentation was certainly very interesting. Just wanted to ask you about management comment at the conference last week that you were making, quote, "massive investments in AI." 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, you know, per product or per group, but not necessarily a very large percentage of your R&D head count. When you say massive investment, in what other ways perhaps do you mean that? Yeah. Jay, good question. First thing I would like to say, just to add on to what John was saying earlier, I mean, yeah, there could be some fluctuation and, you know, renewal timing, but the great thing about our business is we are not, you know, sensitive to that, right? I mean, it's mostly ratable business and. What I'm pleased to see is that, you need a data analytics platform to really do AI in an intelligent, comprehensive way. Also, you know, there are five big platforms on top of JedAI. From chip to package to board to system. We always had Cerebrus, which is doing phenomenal with more than one ASIC tape outs, Verisium for verification. Now Virtuoso Studio for analog with layout migration and, you know, design centering using AI. Then XAI for Allegro, you know, PCB packaging and Optimality for system design and analysis. It's a very comprehensive portfolio. Amount of R&D investment just depends on different products. Sometimes we have it within the product, sometimes we have outside, but it will be pervasive through the product portfolio. Like I have mentioned before, you know, our strength in computational software, you know, naturally allows our regular, even regular R&D to do a lot of AI. You know. We of course have AI specific R&D, but our regular R&D, given the rich history of EDA and computational software, you know, we can embed that in our product. The real value is to really do it comprehensively and make a big difference in terms of productivity, in terms of automation, you know, in terms of PPA benefits that we are delivering to the customers. Thank you, both. Your next question comes from the line of Charles Shi with Needham & Company. Your line is now open. Good afternoon. Thank you for letting me ask a question or two. Really just wanna 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 a renewal in the second half of the year? That's my first question. Yeah. Charles, yes, just for clarification, all of our renewals will be already be in backlog. 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. Then when you get to September, you'll have nothing left in backlog, and then you'll have the renewal will come through. Okay, okay. Those renewed contracts are not yet in your current backlog. That's what you're saying? Oh, the new ones will not be until we do them in the second half of the year. Got it, got it, got it. May I ask Yeah. Yeah. Go ahead, please. That. I just wanted to clarify that. Yes, 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. Got it. Got it. That will be additive to the backlog. Got it. Just want to really clear 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. Now in hindsight, it looks like it's just, 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 industry today? Thank you. 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, you know, the timing of those renewals is not especially important, that 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. Thank you, John. Thanks. Your next question comes from the line of Harlan Sur with JP Morgan. Your line is now open. Hi, good afternoon, nice job on the strong quarterly execution. You know, 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, they told us that they're seeing a pickup just over the last sort of 60 to 90 days, just a 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, 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? Yeah, Harlan, that's a great point. In general, like I mentioned earlier, I mean, there is a lot of strong design activity. You know, we see with our customers, you know, both on the semi and the system side, and when I talk to, you know, our ecosystem partners, right? You know, the foundries and the IP providers. Overall, I think design activity is very strong. Now, in particular to your specific question on AI, I definitely see a lot more interest. The reason is, I mean, you know, I mean, at least one of the reasons I think, which we know or you may know already is, you know, this new kind of generative AI and all this talk about, you know, ChatGPT is that, you know, traditionally, you know, search or this kind of, AI influencing the past was done on, you know, CPUs. This new generative AI tools, you know, of course the training is done on GPUs as always, but even inferencing, you know, when you ask it a question, you know, a lot of the inference is done on GPUs, which is traditionally, you know, it's a great accelerating platform, but traditionally more expensive than CPU platform. Not only it will drive more and more adoption of GPU and accelerate computing in the cloud, but also naturally look for customized silicon, you know, that can do it much more effectively and efficiently, both for performance and power. We do see, you know, generative AI and the adoption of this more reinforcement learning-based kind of inference, you know, training and 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. In general, right, you know, we have talked about for several years, you know, the need for customized silicon, whether it is for generative AI now or in general for, you know, self-driving or, you know, variety of applications is expected to continue, and we are pleased to see continued momentum in that space. Yeah. No, I appreciate that. Maybe as just a follow on to that question, you know, 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 go the extra distance, right? Pull together the capability to do the entire chip designs themselves, right, or 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 and verification tools. Are you guys seeing this trend as well? Yes, absolutely. 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, you know. That's why I've commented in the past that we are still in the second inning of this. Mm-hmm. You can look at other companies, like in the mobile space, when they started doing their own silicon. The first phase is, you know, using a, you know, ASIC provider. Actually we have great relationship with almost all the major ASIC providers. You know, we have very deep partnership with all the, you know, in all geography world-leading ASIC providers. Typically the system companies will start with ASIC provider, but then typically go to a COT flow or customer-owned tooling. In that, you know, they will do more and more back-end design and more and more. Right T hat is, you know, more opportunity for Cadence. 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. That's one thing that really has already happened in other system companies, is happening in the newer ones. Right. And the other thing, of course, is that they will do more and more designs also. You know, initially they start with one or two designs. You know, like, and you can see these examples in, you know, all the public ones like, you know, Amazon doing in the beginning a networking chip. Once that networking chip is successful, they move to Graviton, which is a compute server. Then once that's successful, they go to an AI chip. The number of chips also increases. The third reason that there is more and more business is new system companies get in. You know, traditionally, you know, 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, you know, part of the flow in-house to full flow in-house, which is, you know, moving to COT from ASIC. Mm-hmm. You know, more and more designs being done. Thirdly, more and more companies doing silicon. Okay. All these three trends are positive for Cadence and the products that we supply. Yep. Insightful. Thank you. Your next question comes from the line of Jason Celino with KeyBanc. Your line is now open. 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, you know, was this driven more from your existing business there, or was it from OpenEye? I guess, how is OpenEye doing relative to expectations? Yeah, Jason, we took up the year by about $20 million. About half of that was hardware from Q1, 'cause that was a big portion of the beat in Q1. The other half of that was spread across our software business, mostly in the System Design Analysis space. Mostly organic. There was some inorganic contribution as well. Okay. Go- Sorry, go ahead, Anirudh. Go ahead, Jason. Yeah. Oh, sorry. Yeah. My second question on the guide. You know, it looks like Q2 is gonna decline sequentially by about 5%, you know, consistent with we saw last year too. Maybe just a quick refresher on, you know, what's driving the seasonality here? Yeah, Jason, I mean, when you, when you look at it'll show up in the functional verification number next quarter. I think 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 was also looks great. It's gonna be up low teens again, compared to Q1 2022, but functional verification will be up probably closer to 20% rather than 30%. It's our expectation that, like 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. In Q1, it was 80%, 20%, so there was a lot of upfront 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'll average 85/15 for the year. You're seeing that in the Q2 guides. Okay. Excellent. Also. Thanks, John. Jason. Yeah. Just to add on to what John said. You know, if you look at the Q2 guide, it's we're still up nicely from Q2 of last year. Okay. Okay, awesome. Good. Thanks for the clarification. Your next question comes from the line of Vivek Arya with Bank of America. Your line is now open. Thanks for taking my question. I had a near term and then kind of a bigger picture question. Near term, your IP sales have slowed down, I think, for three quarters now. I think they are actually down year-over-year. I'm curious on what's driving this slowdown, Anirudh. Do you expect IP to grow in line with the 14% sales growth for the entire company? What will help those sales re-accelerate in the back half? Vivek, in general, you know, we, you know, IP is still good business, and we expect in 2023, you know, IP business to grow in the low teens compared to last year. There is some quarter-by-quarter fluctuation, but in general, we expect IP business to perform well in 2023. Yeah. Yeah. Yeah. Then what I would add to that is that when, you know, IP revenue generally can be lumpy because some of it's upfront and it's based on the timing of deliveries. 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. It kind of skewed the year-over-year numbers. 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. Got it. Then, my bigger picture question is, what is the right, you know, kind of public metric to gauge how much benefit you're getting from AI? Is it accretive to your pricing, to your growth rate? Just what is the best public metric to, you know, appreciate how much benefit you're getting from AI? 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 you think it's kind of net accretive longer term, just given the larger TAM size and the greater customer engagement? 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? Yeah. Vivek, you know, what I would say qualify AI is another way of providing, you know, dramatic automation. You know, that's the history of our industry is to provide more and more automation. I would say AI is like third wave of massive automation and productivity improvement. I mean, the first wave was, you know, moving up abstraction level, you know, going from transistor level to gate level to RTL level to C level. You know, that's one wave that drove our industry, you know. The second wave in last 10 years is parallelism. You know, Cadence has invested heavily in massive parallelism, whether it's on-prem or on the cloud. You know, starting from 2013, we have lot of parallel products. Okay. Now the third wave of productivity and automation is using AI or, you know, what I always call AI for optimization, now called, you know, reinforcement learning or generative AI. We have a history over last 20, 30 years of doing this kind of. In all cases, you know, it doesn't cannibalize. Actually the activity increases and amount of software used and amount of optimization that happens, you know, more and more designs are done, you know, with the available, you know, resource headcount. 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 example. You know, talking to some very senior people in our industry, you know, one comment has been that, "Oh, you know, Moore's law has slowed," you know, in terms of actual, you know, improvement you're getting from one node to another node. Now, when you went from 65 to 40 nanometer, you get X amount of improvement. Now when you go to, you know, five to three, you know, that used to be 20% now is it went to 15, now maybe it's like 10% improvement. Even our tools, you know, like Cerebrus or a lot of the other AI-based tools can provide easily 5% to 10% improvement in PPA. You are getting improvement from better algorithms, which are similar to half or full node of a process technology improvement. Okay? That's just huge. You know, the amount of improvements you can get from this third wave of automation, you know, using generative AI is huge. 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. I think, and the other thing is to apply that across other things, you know, not just digital implementation, to apply to, you know, package design, to board design, to simulation. 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. The headcount I expect still will grow, you know, 5 to 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. Thanks, Anirudh. Your next question comes from the line of Gianmarco Conti with Deutsche Bank. Your line is now open. Hi there. Hi Anirudh and John. Thanks for taking my questions. 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. Secondly, you know, perhaps thinking about the specifics of what are the AI demand drivers here, whether those are correlated to increases on the lower nodes or if there are 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 sDNA, is this anything that we, you know, 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. Oh, absolutely. I think, you know, we talked about chip, right? How AI can help this third wave of automation. The same thing can be applied at package and system level. I do want to highlight that. You know, we have talked for a few years on importance of merging of system and semis and how system companies are doing semi, and then we can also provide solutions for system design and analysis like thermal simulation, you know, electromagnetic simulation, you know, fluid dynamics. Traditionally, you know, those areas were, First of all, the simulation capabilities could be improved. You know, just the raw simulation speed. For example, Clarity for electromagnetic, you know, we got order of magnitude improvement versus traditional methods because, you know, applying our computational software expertise, we can do a lot more simulation. On top of that, you know, there are two other things that can jumpstart, you know, system design and analysis. You're seeing that, you know, even our growth that you're seeing. One thing is use of GPU acceleration. You know, we talked about this in my prepared remark, and I think GPU acceleration is significant for system design and analysis there. The other thing is applying AI on top of simulation. EDA has a long history of optimization, you know, not just simulation. AI for optimization of generative AI is really new for system design and analysis because they are barely... You know, even the simulation capabilities were not keeping up, but they didn't really have that much optimization capability. 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. You know, because in general, if you're doing some thermal design or, you know, design of the data center, yes, you want to simulate or, you know, of a car, but you want to optimize, you know. Whether it's the shape of the wing or placement of the racks in the data centers. All this is really now possible with generative AI. I think the impact on this sDNA will be profound apart from the impact on chip design. We are the company that can combine those two things and apply AI to both of these areas. Great. Thank you. Just my second one is on M&A, whether there's any M&A insight or plan on increasing the portfolio, perhaps in sDNA, sorry, in system design analysis, or is 2023, you know, consistent with the plan of distributing cash to shareholders via buybacks? Yeah. I mean, in general, you know, we want to start with the strategy, and we feel we have a very, very strong strategy with intelligent system design, you know. This combination of silicon system and data. We are very pleased with our progress, and we continue to grow, you know, organically and perform well both in terms of revenue growth and margin. That's our base, you know, 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. In general, you know, we are pleased with our strategy and our organic execution. Got it. Thank you. Your next question comes from the line of Blair Abernethy with Rosenblatt Securities. Your line is now open. 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? Secondly, just, you know, on the multi-physics side of things, how are you doing in terms of, you know, your go-to-market strategy and scaling the business up? It looks like it's, you know, getting close to a $500 million run rate. Just want to see how you're doing in the go-to-market side of things. Yes, absolutely. The growth rate is a combination of organic and inorganic, right? The acquisitions we made in the past. In terms of go to market, you know, of course, there is a lot of overlap with our current customers too. Of course, some of the customers are new customers. We try to leverage both our existing channel, and then we also have set up a, you know, a system kind of sales team that targeted, you know, new customers that we traditionally haven't talked to. One thing to remember in sDNA, you know, as this overlap of system and semi companies, a lot of the leading companies in sDNA are companies that Cadence already has very deep relationships with. We are still selling to the engineering organizations, and it's just the good part is both the EDA and the SDA are engineering software. You know, maybe different parts of the customer's engineering organization, but more and more coupled engineering organizations with the combination of system and semi. When we go to sDNA side, we always look at a three-pronged approach in terms of go to market. One is direct sales, you know, like we do for our EDA business. That, you know, we have great relationship with, you know, the top customers in the world which are consuming both EDA and SDA. I think in sDNA, there is a bigger portion of indirect or channel. You know, we had a strong channel for our Allegro and OrCAD businesses, which is PCB and packaging. We have expanded the channel to now include sDNA, you know, to bring our new channel partners throughout the world. The third part of our go-to-market is using cloud and on cloud. You know, we announced last year. Go direct, you know, especially for smaller customers who don't want to have in their own IT department, and especially in the system space, you know, they are much more amenable to, you know, direct, you know, SaaS kind of cloud offerings. You know, overall, this is a ongoing progression. You know, as you said now, the business is getting to a good scale, and especially in sDNA, you know, we want this three-prong approach of direct, indirect plus cloud. One thing to remember is a lot of the top customers in sDNA are already existing, you know, EDA customers, and that really helps us as we go to go to market. Yeah. That's great. Thank, thanks, Anirudh. Your next question comes from the line of Ruben Roy with Stifel. Your line is now open. Thank you. Thanks for taking my question. John, I had a question on the commentary around renewals and, just thinking back to the pandemic and how you guys thoughtfully, you know, took into account some of your smaller customers and, you know, how that might impact some of your software renewals. Just wondering, given the state of the economy right now, and, you know, 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, you know, something that you're worried about? Yeah, 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. We did see some softness in the lower creditworthy tier of customers like startups in Q1 and we have already factored that into our guidance for the year, for both Q2 and for the year. Generally at the high end, with the big renewals are with like the strongest creditworthy customers in the industry. Right. Got it. Thank you, John. A quick follow-up for Anirudh on the hardware. It's come up now a few times, Anirudh, on your calls, which is nice to see, that the take rate of or attach rate, I should say, of hardware continues to move up. The numbers, you know, 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, you know, continued refresh cycle coming around that, you know, if that's a relevant metric at all. You know, to, and to think about, you know, kind of what the percentage of customers is, and if that continues to go up, is 85/15 sort of the right way to think about the longer term mix for the company? I mean, the good thing with the hardware is that, you know, like we mentioned in the past, like, you know, it has become almost essential part of the design process. It's, it's almost, it's virtually impossible to design these complex chips without use of these hardware platforms. I would say, you know, all the major customers, especially all the big major customers that drive most of our revenue are using, you know, hardware anyway. Now there's always room for, you know, re-refresh of that, you know, of the hardware they're using. Also, as the chips go to different nodes, I mean, we are at, like, five nanometer going to three to two to 1.4 to one. There is at least, you know, 10 years of node refresh ahead of us. Every time you go to a new node, you know, the size of the chip increases, you know, the number of gates that are on a chip increases, you typically need more and more hardware. The capacity requirement for hardware increases. That's why I think that for long term, you know, hardware is going to be in a secular growth period. Not only is it critical, but you need more and more, and that's gonna last for, you know, at least for the next 10 years, if not more. 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. At this point, most of our big customers are using hardware, but still there is growth because the chip sizes increases. if they're using Palladium, they can use more Protium and vice versa. 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. Of course, that grew the upfront hardware was so strong last year, it went to 85/15. Of course, we're guiding to the year of 85/15 now, without with the caveat that, you know, we're going to take another look in the summer, and we may take the second half up if we see continued hardware strength, 'cause strength continued into Q1. Although we're guiding 85/15 right now, I would take the over on the 15 rather than the under. 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? We should get back to more normal lead times by the middle of the year. 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 wanna set up demo models for customers for future sales and things like that. The Q1 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. We expect to be back to more normal lead times by the middle of the year. That's great. Thanks, John. Your next question comes from the line of Joe Vruwink with Baird. Your line is now open. Great. Thanks for squeezing me in. I wanted to take another crack at the topic of AI and adoption. When you think about maybe the best example is Cerebrus. Within an implementation effort, if you think about the total block engineers at an account, what share of those engineers are typically using the product at this point? In your mind, is that something as we enter the next round of renewals, it could get more widely deployed across the entire team? Yeah, 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. We are engaged with all the top customers, and then five hyperscalers are using. Still, you know, I think, you know, there's still a lot of opportunity for growth there. The way I look at it is, you know, especially Cerebrus or JedAI or all these platforms, that I think over time, you know, they will become the cockpit. In the old days, you know, in case of digital implementation, you know, Innovus was the cockpit. The customers would run Innovus or, you know, try different experiments with Innovus. Now Cerebrus can do that, you know, mathematically, you know, with the AI, and then you can still combine that with the, you know, you can still do manual experiments on top of that. I think overall, I would expect in, you know, three to five years, you know, almost all designers would be using Cerebrus what they were using, you know, Innovus in the past. Okay. Same thing with Optimality, same thing with Allegro X AI. We are still ways from that. There is still this progression that has to happen. I think we are engaged with all the customers. We are, you know, they're using it. I think over time, you know, it will become the dominant way of running products will be using Cerebrus rather than using, you know, the old way. It's like going from, you know, manual cars to automatic cars. Some people may still want to drive manual, more and more people will drive automatically using Cerebrus. 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. You know, in our business, you know, like we mentioned earlier, we're looking at, you know, annual contract value and let the natural adoption happens over the next few years. Okay. That's, that's great. On the system design segment, I don't think I heard it, just an update on where you expect growth to be in 2023. In reflecting on the developments here and kind of the upside you're seeing in bookings, is it possible to pinpoint it to, you know, something like you talked about the repeat orders on the organic solvers. You've obviously built a bigger CFD business through some new channel initiatives. Are any of these things more important than others in terms of driving the upside you've seen? I think 2023, I still expect, you know, 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, you know, is we are obsessed with, you know, best-of-class products first. That's the most important thing. You know, if the products are differentiated, you know, the customers always use it. All these channel initiatives help and, you know, awareness of our products with marketing helps. In the end, you know, we always focus on, you know, developing and supporting, you know, making best-in-class products. On that, you know, we made a lot of progress and benefits. I mean, recently, you know, I talked about in my prepared remarks, but, you know, one thing I think in System Design and Analysis, like I mentioned, I'm very optimistic about use of GPUs. Traditionally, GPUs haven't worked that well in EDA. You know, 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 in spirit to AI. Like, recently with our collaboration with NVIDIA, you know, Jensen talked about that Cadence CFD on GPU for the same cost is giving a 9x improvement in speed up and 70x improvement in power efficiency. You know, GPUs are slightly more expensive than CPUs. I mean, typically, I would guess, you know, at least 3x to 5x. You're getting 30x to 50x speed up on GPUs. That normalized for cost, you're still getting 10x or 9x improvement in speed. That's a huge improvement, you know, based on our special algorithms. You know, because we have a long history of massive parallelism in CPUs, and now we are applying it to GPUs, both, you know, especially in sDNA, you know, both for, you know, electromagnetics and then CFD. I think that can also provide a lot of growth. You know, I talked about AI and all for chip and system, but this acceleration on GPUs, accelerated compute for system analysis is another big vector. Even in OpenEye, we use GPUs for acceleration. I think that's, we have multiple ways to accelerate our position in sDNA, but we're always focused on, you know, best in class first. Right. Yeah. Thank you. Your next question comes from the line of Andrew DeGasperi with Berenberg. Your line is now open. Thanks for fitting me in. I guess one question I had is. I know you've talked a lot about AI on this call, 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, just wondering if we saw within portfolio that you have relative, and your investments that you made relative to your competitors, do you think that could change? Yeah, that's a good point. I mean, in general, like I mentioned, we are always focused on best in class, right? And that AI can play a big role in that. I do think that the real opportunity for the industry, you know, both for EDA, sDNA, you know, 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 wanna have best in class solutions in our products. I think the bigger trend will also be, you know, these things are getting so complex, there's not gonna be enough headcount to design these things, you know, five, seven years from now. The bigger opportunity for the entire industry is more shift to automation, and that's, I think, good for everyone. That's helpful. I think the way we look at. Yeah. Sorry, go ahead. Yes, please. No, go ahead. I mean, that was just. Yeah, the other thing I think, the way we are unique is not just apply, you know, best in class products in EDA, but we combine, you know, chip and systems. I think that's also provides 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. Applying AI improves our EDA solution, but also the combination of EDA plus SDA and computational software, that also improves our, you know, competitive position in the market. That's helpful. 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 has it been kind of consistent relative to the previous quarters? I think that. I mean, you know the news is, I mean, it's a tough environment for our. You know, in general, you know, with all the news is. In general, like I said, the design activity is strong. Okay. Our, you know, results are strong. I think the data center customers still, you know, invest heavily in automation and, you know, R&D. The new uptick, like the beginning of the call, we talked about the new uptick, 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, you know, to serve this whole generative AI base. That will require use of specialized hardware. Different kind of hardware mix in the infrastructure. I think that's going to be a change, and that's good for our opportunities for us. Yeah. Great. Thank you. Your next question comes from the line of Arsenije Matovic with Wolfe Research. Your line is now open. Hi, this is Arsenije on for Josh. Just to 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 maybe the shifts in 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. Well, I would say that, you know, in system companies, data center is always a lot of activity, you know, driven by generative AI. 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. If you have to pick like a few verticals, definitely data centers with AI and then automotive, AI in general, but also electrification and more A&D. We are seeing that in our own engagements with customers. Yeah. Got it. 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 kinda like quantify that from a high level, be helpful. I think it's a combination of both. It's both, you know, like the system the semi companies as, you know, more designs and newer designs require more and more hardware. System companies by its nature also have software. You know, otherwise they wouldn't be system companies. In system companies, you know, our dual, you know, dynamic duo of Protium and Palladium really helps because Protium is more for software bring up and then Palladium for chip bring up. I would say both are strong, but there is more software content by nature in the system companies. Yeah. Thank you. I will now turn the call back over to Anirudh Devgan for closing remarks. 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. 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. Thank you for participating in today's Cadence Q1 2023 earnings conference call. This concludes today's call. You may now disconnect.