Good afternoon. My name is Lisa, I'll be your conference today. At this time, I would like to welcome everyone to the Cadence second quarter 2023 earnings conference call. All lines have been placed on mute to prevent any background noise. Speaker's remarks will, in an answer session. If you would like to ask a question during this time, simply press star, then the number one on your telephone keypad. As a reminder that, please limit yourself to one question and one follow-up. I'll now turn the call over to Richard Gu, Vice President, Relations for Cadence. Please go ahead. Thank you, operator. I would like to welcome everyone to our 2nd 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. 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, CFO commentary, and today's earnings release. All forward-looking statements during this call are based on estimates and information available to us as of today. We disclaim any obligation to update them. In addition, we 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, I would ask that you observe a limit of one question and one follow-up. Now, I'll turn the call over to Anirudh. Thank you, Richard. Good afternoon, everyone, and thank you for joining us today. Cadence delivered excellent financial results for the second quarter of 2023, with strong, ongoing customer demand for our innovative technology. We exceeded our guidance on all key metrics and are raising our financial outlook for the year yet again, resulting in 14% year-over-year revenue growth and 19% non-GAAP EPS growth. John will provide more details shortly on both our Q2 results and the updated outlook for the year. With its unparalleled promise, generative AI is beginning to make a significant impact globally. Our dedicated focus on AI over the past several years, combined with our computational software expertise and invaluable data that lies at the core of AI, it uniquely positions us to deliver to this tremendous potential of this transformational technology. With escalating design complexity, increasing design starts, and a growing talent shortage, AI-driven design automation is crucial in empowering customers to fully realize their innovation potential. Our customers are increasingly adopting our chip, package, board, system, generative AI portfolio, as they are achieving exceptional quality of results and productivity benefits with these solutions. Customers are ramping up their R&D spend in AI-driven automation, opening up significant opportunities for Cadence. Our solutions are enabling marquee AI infrastructure platform companies to deliver their next-generation compute, networking, and memory products. For instance, in his COMPUTEX keynote earlier this quarter, Jensen Huang of NVIDIA noted that NVIDIA is a big Cadence customer and commented on the expanding strategic partnership between NVIDIA and Cadence to accelerate E DA, system analysis, AI, and digital biology. Cadence has successfully collaborated with Tesla on the development of their game-changing Dojo AI supercomputer. Tesla utilized a broad array of Cadence solutions across digital, custom analog, verification, 2.5D and 3D IC, and system analysis for developing Dojo chips and solutions. We are very excited to extend our partnership to Tesla's next-generation Dojo and FSD platforms. Our customers, like Tesla, are able to leverage the power of revolutionary Cadence Cerebrus generative AI technology to optimize the quality of results of their groundbreaking AI chips and related solutions. From a products perspective, we began by providing AI-driven solutions for core EDA applications, then expanded our AI portfolio to include system design and analysis, and plan to extend it to life sciences in the future. With AI as their underpinning, other generational trends such as hyperscale computing, 5G, and autonomous driving, continue to spur robust design activity across semi and system companies, creating ample market opportunities for our differentiated technology portfolio. Let's talk about our key highlights for Q2. In Q2, we deepened our long-standing partnership with a marquee electronic system company through a broad-ranging expansion of our core EDA, hardware, IP, and systems portfolio. Emulation and prototyping have become a must-have part of the chip tape-out and software bring-up flows, secular demand for our hardware platforms drove our verification business in Q2 to a 27% year-over-year revenue growth. Following a record 2022 and Q1 2023, our Palladium Z2 and Protium X2 hardware platforms delivered a record Q2, as market demand accelerated for these best-in-class solutions. With 14 new customers and 45 repeat customers, more than half the orders during the quarter included both platforms. Demand for our hardware solutions was broad-based, with particular strength seen in AI, hyperscale computing, and automotive segments. A global communication services leader successfully deployed the Z2 and X2 systems to significantly accelerate the development of their data center chips for internal use, including those designed for AI applications. Our hardware platform enabled them to accelerate their verification workload and software bringup, enabling first-pass silicon and software success. Verisium, our AI-driven verification platform that's built upon the JedAI database and nat ively integrated with our verification engines, is gaining traction at market-shaping customers. For instance, a large mobile chip company is working with us on developing a new Verisium regression optimization app, and a Japanese semi customer is actively deploying Verisium apps across its automotive SoC and already saw a 4x improvement in the identification of erroneous source code check-ins. Our digital IC business had another solid quarter, with 15% year-over-year revenue growth, largely driven by proliferation of our digital full flow, especially at the most advanced node at market-shaping customers. Our Cadence Cerebrus solution leverages breakthrough AI-driven technology to explore the entire design space and automatically optimize the digital full flow to deliver transformational results. Adoption and proliferation of Cadence Cerebrus accelerated, and with multiple new marquee wins, is now deployed at eight of our top 10 customers. A leading hyperscaler doubled their run rate through a major expansion that included our digital full flow and Cadence Cereb rus. Another market-shaping hyperscaler successfully used our digital full flow and Cadence Cerebrus to achieve a 16% leakage power reduction on their latest custom silicon. Socionext achieved 2x-3x better productivity with our new Joules RTL Design Studio through analysis efficiency and significantly reduced iterations between RTL and implementation. On IP, our scalable and profitable growth strategy continues benefiting from ongoing outsourcing trend, as well as the opportunities offered by expanding foundry ecosystem. Demand for our design IP was strong, led by our multi-year agreement with Samsung Foundry to expand the availability of our design IP portfolio for Samsung's advanced process technology. We signed a definitive agreement with Rambus to acquire their PHY IP asset, along with the talented team. The addition of their leading HBM, GDDR solutions, and SerDes IP enhances our established IP portfolio, providing complete subsystem solutions for demanding networking, hyperscaler, and AI applications. Our system design and analysis business continued its strong momentum in Q2, delivering 23% year-over-year revenue growth. With Moore's Law slowing down and chip complexity and cost increasing, companies are looking to multi-die 3D IC and chiplet-based architectures to achieve better performance and greater cost savings. In Q2, we expanded our collaboration with Samsung Foundry through the delivery of reference flows and package design kits based on our uniquely differentiated Integrity 3D-IC Platform, the industry's only unified platform that includes system planning, packaging, and system-level analysis in a single cockpit. Our multiphysics solutions, boosted by our optimality generative AI technology, leverage differentiated system simulation and optimization techniques to deliver superior results. Our CFD portfolio, that includes recently acquired high-fidelity simulation technology, won large renewals and add-on business with top aerospace and defense companies. We were pleased with the new wins and growing repeat orders for our multiphysics portfolio from customers across multiple end markets. In summary, I'm pleased with our Q2 results and the continuing momentum of our business. AI-driven automation in chip and system design offers massive opportunities for Cadence over the long term, that seamlessly align with our computational software core competence and intelligent system design strategy. We continue to invest in our world-class EDA system design and analysis, and AI capabilities to deliver cutting-edge innovation to our customers and partners. Now, I will turn it over to John to provide more details on the Q2 results and our updated 2023 outlook. Thanks, Anirudh. Good afternoon, everyone. I'm pleased to report that Cadence achieved strong results for the second quarter of 2023, driven by the broad-based strength of our business. Our customers are increasingly adopting our generative AI portfolio. They are achieving exceptional quality results and productivity benefits with these solutions. Here are some of the financial highlights from the second quarter, starting with the P&L. Total revenue was $977 million. GAAP operating margin was 30.7%. Non-GAAP operating margin was 41.8%. GAAP EPS was $0.81. Non-GAAP EPS was $1.22. Next, turning to the balance sheet and cash flow. Cash balance at quarter end was $874 million, while the principal value of debt outstanding was $650 million. Operating cash flow was $414 million, and we used $325 million to repurchase Cadence shares in Q2. We are increasing our outlook for the remainder of the year due to continued broad-based strength across our technology portfolio. Demand for our functional verification hardware solutions remained particularly strong, and as a result, our updated outlook for the second half of the year reflects approximately 15% revenue growth compared to the second half of last year. Before I provide our updated outlook for the year and our expectations for Q3, I'd like to highlight that our outlook contains our usual assumption that the export control regulations that exist today remain substantially similar for the remainder of the year. Our updated outlook for fiscal 2023 is revenue in the range of $4.05 billion-$4.09 billion. GAAP operating margin in the range of 30.2%-31.2%. Non-GAAP operating margin in the range of 41.2%-42.2%. GAAP EPS in the range of $3.35-$3.41. Non-GAAP EPS in the range of $5.05-$5.11. Operating cash flow in the range of $1.3 billion-$1.4 billion, and we expect to use at least 50% of our annual free cash flow to repurchase Cadence shares. A large number of hardware systems are slated for delivery in late September and early October. For the purposes of providing our outlook for Q3, which ends on September 30th, we thought it was prudent to assume that the vast majority of those hardware deliveries fall into October and Q4. With that in mind, for Q3, we expect revenue in the range of $990 million-$1.01 billion. GAAP operating margin of approximately 29%. Non-GAAP operating margin of approximately 40%. GAAP EPS in the range of $0.76-$0.80. Non-GAAP EPS in the range of $1.18-$1.22, and we expect to use approximately $125 million of cash to repurchase 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 delivered a strong Q2 and first half of the year. With the increase in our outlook, at the midpoint, we now expect revenue growth for the year to exceed 14%, which would take our three-year revenue CAGR to approximately 15%. Non-GAAP EPS growth of approximately 19%, which would result in an average annual growth rate of 22% over the past three years. 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. Thank you. At this time, I would like to remind everyone who wants to ask a question to please press star, then the number one on your telephone keypad. Please limit yourself to one question and one follow-up. We'll pause for a moment to compile the Q&A roster. Our first question comes from Jason Celino with KeyBanc Capital Markets. Great. Thanks for taking my question. John, Anirudh, good quarter. I think if we take a step back, you know, up 14% for the year, still pretty impressive. Sounds like hardware had another record quarter and was up 27%. I think some investors will still wonder, you know, could it have been even better? Maybe can you speak to any areas that maybe weren't as strong that you were hoping, or how do we kind of level set the performance? Yeah. Hi, Jason. Good question. You know, in general, you know, we manage our business for the long term. We are pretty positive with the results. You know, for the full year, like you mentioned, it's more than 14% revenue growth. Earnings are growing at 19%. Our strategy of doing EDA plus SDA plus AI with the computational software expertise. I think overall, we're pretty pleased with how all the businesses are performing and, you know, continue to drive on all fronts, working with customers and partners to deliver the right solutions. Yeah, Jason, as Anirudh says, we're very happy with, very pleased with the first half performance. If there's anything unusual, essentially, in the numbers for the first half, I think one unusual thing for me would probably be the operating cash is flat in our guide to last quarter. That's because, as Anirudh says, you know, we manage the business for the long term. There's an opportunity. We've had some opportunities to build inventory. We've had very strong hardware demand, so we need to buy inventory, and we were offered some larger discounts for payment upfront, so we embedded that into the guidance. It'll help us with gross margins in future years, but it doesn't help with operating cash for this year. Gotcha. My quick follow-up, the IP acquisition from Rambus, is it included in guidance? Maybe can you speak to strategic rationale? I guess, what goes into the decision build versus buy as it relates to IP? Thanks. Yes, Jason. everything we know is included in our guidance, but it's immaterial to us for the year. Yeah, it's a great opportunity for us to acquire a very good set of IPs and a talented team. You know, what is particularly good in this case is that it is a existing, you know, commercial operation. You know, sometimes we have opportunity to acquire teams from, you know, other semiconductor companies, but in this case, it was an existing commercial operation with key IPs like, you know, HBM and GDDR. We took that opportunity, and we're glad to, you know, partner with Rambus here. It really helps, you know, IP for AI and 3D IC with HBM and DDR IPs. Overall, I think it's a good acqu isition, and we continue to invest in all our businesses, you know, including IP, so. Excellent. Excellent. Thank you both. We'll take our next question from Charles Shi with Needham & Company. Hi, good afternoon. Thank you for taking my questions. First, I want to ask about bookings. I have a follow-up on hardware. John or Anirudh, are you guys still seeing strong bookings potential in the second half? I definitely saw your bookings, implied bookings are actually already up in Q2. I think people are probably accustomed to, like, a $1 billion plus per quarter kind of bookings. When can we get back to that level? Do you still expect the second half bookings to be as strong as, let's say, maybe first half 2022? Thank you. Yes, Charles, great question. Yes, we'd expect a stronger second half for bookings. As we said last quarter, we had very few contracts expiring in the first half of this year, and we have more contracts expiring in the second half of 2023. We'd expect bookings to be higher in the second half compared to the first. When we look at backlog, we filed our 10-Q, by the way, so you'll see our backlog at the end of Q2 dropped from $5.4 billion to $5.3 billion. RPO, at the end of Q2, dropped from $5 billion at the end of Q1 to $4.9 billion. The current value of that RPO, the annual value, as you know, backlog and RPO is a combination of the annual value, multiplied by the time essentially that you've contracted with customers. Our current RPO is up from last quarter. It was $2.7 billion last quarter, it's up to $2.8 billion this quarter. We've improved the annual value, and that's typically what we focus on, making sure we're improving the annual value. Yeah, we're very, very pleased with the bookings performance for Q2. It was slightly stronger than we had anticipated or expected, second half, we think will be better again. Well, is it safe for us or for you guys to call maybe Q1 was probably the trough in terms of booking, and we are way past that going forward? Yes. Yeah, Q1 was definitely a low bookings quarter for us. Q2 was a lot stronger. Got it. Maybe a follow-up question around hardware. You kind of said for Q4, you're expecting a good amount of hardware revenue. Maybe it's parked in Q4, but when folks look at your full year guidance, your Q4 isn't really by a lot, they imply the guidance for Q4. Given you just said that the bookings are expecting relatively strong, I would think that the ratable part of the business should see a very strong sequential growth into Q4. And the layer on top of that, the hardware strength, you're expecting in Q4. Can you kind of reconcile what you guided for Q4 versus the commentary you made about hardware and the bookings? Thank you. Yes, Charles, I think you're referring to the step up from Q3 to Q4 in our guide. We're guiding about $1 billion of revenue in Q3, with a balance of just over $1.07 billion in Q4. Now, that's slightly exaggerated, the Q3 to Q4 step up. I mean, when we originally looked at the top-down forecast for the second half, there was a lower step up in revenue, mainly due to software increases in annual value in software bookings that we expect. When we looked at the hardware and the timing of when hardware deliveries happen, and there's so many that fall late in the quarter, we thought it was prudent to assume that those bookings, we should include them in our implied Q4 guidance, so to speak, rather than including it in Q3. I'm not really sure about the timing of those. Okay. Thank you. Okay, thanks. We'll take our next question from Vivek Arya with Bank of America. Hi, this is Blake Friedman. I'm from Vivek. just wanted to start out, if you could provide some insight on how you quantify benefits from AI. Just looking at the semiconductor landscape, there have been several AI-related design programs that started a few years ago. Would you say you've already seen the benefits in your financials, or should we expect even more growth acceleration in the future? If you would comment on the attach rate of your AI-enabled products to baseline contracts, that would be helpful. Thanks. Yes, so AI has multiple implications for us. You know, the first part is, you know, we enable the development of AI systems, right? It's more like a horizontal application. Like we talked about our partnership with NVIDIA, and there are other companies building AI systems. Like we talked about today, our partnership with Tesla, which is building both, you know, server-side AI and, you know, on the, on the car AI, and then other kind of data center companies. We are in a unique position to supply to all the, whether it's GPU or data center or automotive applications of AI, to do the AI build-out. That, I think, is still continuing. You know, there'll be more and more systems designed, and our tools and IP can play a key role in that. That's kind of the first application. I believe we are still in the beginning stages of that kind of build-out and monetization. Then the second part would be more vertical, you know, applying it to our own products. We have, you know, JedAI platform, which is with a unique position as a kind of a data platform for AI, and then five unique AI applications, all the way from analog, digital, verification, you know, package and board, and systems. I believe we have the most comprehensive product portfolio for, you know, chip package system design. That also, I think we are in the early stages, but we are seeing a lot of adoption of those kind of vertical applications. We are also using them internally. You know, we design our own chips for Palladium systems, right? Then, of course, we have a big application engineering team that works with customers. Not only we are providing solutions to our customers and partners on EDA and SDA, but we are also using them internally and seeing good benefits. The third part, which is more out in the future, you know, I think AI will also drive new kind of applications, and one of the biggest ones is definitely going to be life sciences. We are laying the groundwork for that, you know, with our open AI, and, you know, there's a lot of opportunity to apply their AI there in digital biology, which will pay out in the next, you know, five to 10 years. For all these kind of three big, you know, there's a horizontal play for building out the AI systems, GPUs and data center, other things. Vertical play of EDA and system, you know, both to our customers and ourselves, and emerging areas that will emerge in life sciences. Overall, I feel we are very well positioned to really capitalize on this mega trend. Yeah, Blake, to answer your revenue question, essentially, I mean, I think it's clear that it's showing up quickly in the hardware space. We feel on the software side, it'll probably take a couple of contract cycles for that to flow through. We're seeing strength in pockets on the software side. The software side, because it's recurring in revenue, will take a while to play through. You're definitely seeing the impact of AI in hardware, strong hardware demands. Got it. Helpful. Just quickly as a follow-up, hoping we can discuss your capital allocation policy as well. Just given the pretty solid cash position and significant cash generation of the company, is there any interest in allocating more cash towards share repurchases? Also, if you could comment on, you know, any interest in issuing a dividend in the future as well. Yeah, Blake, yeah, we look at that all the time in terms of our cash allocation policy. In Q2, we used $325 million on stock repurchases. $200 million of that was due to an accelerated share repurchase. The timing of that was timed deliberately to coincide with our merit and promotion cycle. You might have noticed as well in our guide that, you know, expenses take a step up and margins slightly down second half compared to first half. That's because our pay rise and promotion cycle kicks in on July first at Cadence, that's typically when we do our stock refresh for employees in the company. Because we grant a lot of stock at that time of the year, we in our stock repurchase approach, we want to make sure that we're offsetting the dilution first. Then, ideally, we want to reduce that share count over time. You know, we've talked about dividends with the board from time to time, but we think it makes most sense to use our excess cash for stock repurchases. Our policy is essentially to use at least 50% of free cash flow to repurchase shares, repurchase our shares, and that should more than offset dilution, see the share count continue to decline over time, and gives us enough to grow the business. Great. Thank you. No worries. We'll take our next question from Jay Vleeschhouwer with Griffin Securities. Thank you. Good evening. Business question first, then a technology question as the follow-up. Anirudh, as you know, for the last couple of years, we've often spoken about how semiconductor companies and systems customers have become increasingly alike. The question though, is: in what important ways do they remain dissimilar in terms of sales cycles, conversion of RPO to revenue, services requirements, account profitability? Anything you care to mention that continues to distinguish those two classes of customers? Jay, I mean, like you also written, right? I mean, the semi companies are becoming system companies, and system companies are becoming semi companies. And, you know, some, you know, traditional semi companies are, you know, much more system companies now with software and, you know, a lot of traditional system companies are doing a lot of semi. You know, one of the several big semis are done in system companies. There are a lot of similarities. You know, you're asking in terms of differences. I mean, I guess one key difference has to be that the system companies, by definition, have hardware and software together. You know, you are a system company because you have software and also have electrical and mechanical together. I mean, a good example is a car, right? It's a merging of electronics and mechanical, it's a merging of hardware and software. For that reason, I think, you know, like the strength we talked about in the hardware business, a lot of it is not just for chip design, it is for software bring up. We are seeing that in AI applications. You know, a lot of the software has to be built along with the hardware. Even for, you know, even for, you know, NVIDIA, which is traditionally semi company, has a lot of software, of course, with CUDA. A lot of the data center companies that are doing their own chips have a lot of software. I think the enablement of software becomes key. The other thing is this merger of electrical and mechanical. That's why our whole investment, you know, in System Design and Analysis, in thermal simulation, which is a big thing for data centers and cars, you know, electromagnetics, you know, CFD. The key thing I think is unique, is different, is hardware plus software and electrical plus mechanical. Now, in some cases, we do, you know, strategic services for some system companies to get them started, and I think that's also a unique difference. Sometimes we will provide, help them to get going with chip development. I would say, Jay, these are probably three big differences compared to. It's good to see the growth in the semis too. You know, we are happy to have a whole new market with system companies, but we still love our all our semi customers, and they're doing phenomenal, you know, and we are partnering with them in all kinds of ways. Okay. As the technology follow-up at DAC two weeks ago, there was a quite interesting presentation by Cadence at the conference related to AI, and it was the use of a very interesting new with regard to productivity or where productivity is going to come from in future for EDA. That term used by Cadence was task abstraction. A new kind o f abstraction from the decades of abstraction we've seen in EDA for the last, well, many years. How are you manifesting that new concept of abstraction in terms of product development, packaging, all those sorts of things going forward, since that term seems to be very much a critical part of your thinking going forward for EDA productivity? Jay, you know, if you step back, right, you look at, you know, fundamental innovations, of course, we talk about a lot of things, you know, if you look at mathematics or computer science, I mean, there are two big innovations. One is abstraction, the other is parallelism. In the history of EDA is moving up the abstraction layer, right? From all the way from polygons, to transistors, to gates, to RTL, and also parallelism. You know, the last 10 years, you know, I think if you look at EDA, history of EDA, it started with abstraction first, as you know, and then in the last 10 years, it went back to more parallelism with use of cloud computing and CPUs. With this AI, there is opportunity to do more abstraction, you know, move even higher level. You know, basically, the real opportunity is to automate mundane tasks, right? What was done by the user can be done by the AI engine. Abstraction will provide, in the end, a lot of automation and productivity improvement. We are seeing that, you know, we can apply it to even technology, design technology, co-design, you know, DTCO with leading foundries. We can apply AI to, you know, design of floor planning and, you know, higher level functions, which were previously manual, applied to 3D IC partitioning with Integrity. Overall, this theme of applying AI, doing more abstraction, doing more of the mundane work, and let the user focus on higher level tasks and be more productive, is only the beginning of that and is enabled in all these aspects, you know, digital verification, system design, and so on. Okay. Thank you. Our next question comes from Ruben Roy with Stifel. Thank you. Anirudh, if I could start from where you left off there, I had a question similar to Jay's, but I was wondering, I think you mentioned that Cerebrus with AI was deployed at eight of your top 10 customers. I'm just wondering today, can you talk about how AI is being used? Is it mostly place and route, or are you seeing some of these other areas being implemented in leading-edge designs? Whether it's, you know, packaging or even, you know, some of the, you know, floor planning, etcetera. You know, how far along are we? It's getting pretty pervasive. I mean, the first thing I'm assertive of now, you know, compared to, like, two years ago, you know, we started on this journey two, three years ago in terms of working with Cerebrus and our customers. You know, one thing I am positive now is that, you know, a few years from now, almost all our customers will be using these tools because it's almost like a irreversible trend. You know, for Cerebrus or place and route was the first one in some ways, so it has, you know, a lot of adoption. It is extending to, like I mentioned, you know, this, working with foundries, working with, you know, floor planning, higher level functions, verification. In the end, I do believe verification will have a most profound impact within EDA, on AI will be on verification, because it's an unbounded NP-complete problem, right? You can do more and more verification, you're never done. That's why you see us investing heavily in Verisium. You know, we are the first to apply AI to verification. We talked about a couple of examples with customers in the prepared remarks. The other thing, is, you know, areas that traditionally haven't had a lot of automation, like package and PCB. With Allegro X AI, you know, that area has not seen automation for like 20, 30 years. For the first time, it's possible with AI. In system simulation. The system area, now EDA by its nature, has had a 30-year history of optimization and automation. It was not with it was more with classical techniques and now with AI. If you look at the system area, like CFD or electromagnetics, you know, they could barely simulate stuff, forget optimizing it. Not only now we can simulate things, you know, because our algorithms are faster and we are also accelerating them on GPUs and all to give massive speed up on system simulation. Now, for the first time, you can simulate a very, very high fidelity simulation of the whole car. On top of it, you know, Optimality and AI, you can do the design of the car or the shape of the wing, which is what in the end, the user wants, right? They just don't want to simulate. All this applies exactly to this big market of SD&A. I think that's a huge opportunity, and we're already seeing that. Like, even with the, some of the, you know, car companies we work with, we can optimize the shape of the wing. You know, that affects performance, like for a racing car, if we're using AI. We already have pretty promising results, and we will talk more about that in the future. I would say that, first of all, I think it will be deployed across all these platforms. It started with PNR, but already we are seeing a lot of potential. In the end, in EDA, the huge potential will be verification. The other area I'm very optimistic is system simulation and AI. Thanks very much, Anirudh, for that. quick follow-up for John, just on operating margin, down a little bit in Q3 with what sounds to me like hardware, you know, kind of strengthening towards the end of the quarter and obviously into Q4. How are you thinking about that? Or how should we think about operating margin and, you know, sort of the moving parts between Q3, you bumped it up a little bit for the full year. If you can help us out on how you're thinking about operating margin in the context of hardware attach rates going up, you know, as you exit the year, that'd be helpful. Thank you. Yeah, no worries. Great question. As you saw, I think the first half was we were roughly just under 42%, I think, for non-GAAP operating margin. For the second half, the guide essentially implies 41%-42% operating margin. It's slightly down as it has been the last few years in the second half compared to the first half, but that's because July 1st is our merit cycle. That's when we do pay raises and promotions. Generally, pay increases, you know, the vast majority of our expense base is people and engineers. About 90% of the employees are engineers. Pay increases, impact us from the first day of Q3, and that step up in cost is really the headwind you're seeing from Q3, when you compare Q3 and Q4 combined, or second half, compared to the first half. Now, I've exaggerated that a little bit by being prudent with the Q1 or Q3 guide on the hardware side, because there's a number of hardware systems that are scheduled to be delivered in late September. Late September is a holiday period, sorry, late September, early October is a holiday period in China and other parts of Asia. I'm just worried that some of those will slip to Q4. I've assumed the vast majority of them slip to Q4 in the guide, just to be prudent. That, of course, is impacting, the operating margin that we're showing in the guide for, Q3. I think if you look at the second half as a whole, generally, it's 41%-42% for the second half, when you take out the impact of that prudence. Got it. It makes sense. Thank you, John. Thanks. We'll take our next question from Blair Abernethy with Rosenblatt Securities. Thanks, gentlemen, and a great quarter. Just wanted to dive in a little bit on China. You know, the growth this quarter on a year-over-year basis was quite strong. Anything you'd any color you could give there on the, on what's driving that and how this continues would be helpful. Secondly, just on back on the hardware side, John, just you've commented in the past about your production capacity ramping up. Just wondering where you're at midyear here and how lead times are doing? Yeah, I'll start first, then John can comment on the inventory. Overall, China, you know, we are pleased to see, you know, continuing strong design activity in all kinds of, you know, end markets, also good strength for hardware business. We've also had a good hardware business, China. You know, particularly in Q2, I would say there was a lot of strength from mobile vertical. You know, a lot of companies, you know, some big system companies designing their own chips. Also automotive, especially EV automotive in China, was particularly strong. I mean, China is, just like the rest of the world, is pretty diverse market, and we play in all aspects of it, but those two verticals were pretty strong in China. John, you want. Yeah, and, in terms of your question in relation to lead times, I think, at the start of the year, you know, we ramped up production capacity because lead times had exceeded 26 weeks, and we thought, "That's going to hurt us when we're competing for hardware business." We put a big dent in that in Q1. We ramped up production capacity. We've kept it at those levels for Q2 and intend to keep it at the higher production levels throughout the rest of the year and going forward. We're bringing down that those lead times. Our goal is to try and get it down into the 10-13-week kind of time frame. We're not there yet, though. I mean, when, in terms of the guide that I've given you for Q3, even with prudence and all in, but like, let's say, if I took the prudence out, that we don't need a dollar of Q3 hardware bookings to meet those numbers. We're slightly over the 13 weeks, probably around the 15-week mark, in terms of what we have in backlog right now to deliver. We won't actually get through all of the hardware orders that we have in backlog in Q3. Demand is still strong. We are reducing. It's probably around the 15-week mark now, but I'd like to get that down to 10 to 13 weeks. Okay, great. Thank you. Actually, just one more question on the hardware, if I can? You know, the Palladium Z2 and the Protium X2 have been out in the market now for a bit of time. When can we expect to see, you know, next generation versions? Yeah, it's been only out for two years, you know. You know, our last system, it was like, I don't know, five, six years between between launches, and I think this one has been out two years. Even when we launched Z2, X2, even Z1 and X1 were doing great. Right now we are pretty pleased with these systems, and we also can, you know, We keep improving the software. I mean, that's the hardware part of it, but we're always improving the software and compile times that go on top of these systems. There is ongoing software rhythm to them anyway, independent of the hardware. Overall, I mean, there's phenomenal performance by the team and we really appreciate all the support from our customers and partners. Yeah. Great. Thanks very much, guys. Mm-hmm. We'll take our next question from Joe Vruwink with Baird. Great. Hi, Devgan. Let me begin a bit of a leading question. You're now talking about second half revenues growing 15%. The multi-year CAGRs are closer to 15%-16%. There's things on the horizon, and not next couple of quarters, not trailing, but longer out, just in terms of how your customers are acting and also what Cadence is offering, that would seem to be better than what you've experienced, both in terms of R&D intensity and your potential wallet share. The question is: you know, instead of this 15% rate of growth being the high end of what historical growth rates have been, do you think we're maybe seeing a resetting of the overall base case for growth rates and what might be available to the company going forward? Well, first of all, I would say, you know, 15% growth rate and 19% EPS growth is an amazing performance of any company. We are very proud of the team to deliver this. In terms of, you know, design activity and R&D intensity, I mean, that is strong, if not getting stronger. Of course, the overall, you know, microenvironment as tough as it has been, you know, last year and this year, but we do see a lot of semi and system activity. That's not any different than before, but we have to carefully monitor how things go in the future, of course. Overall, you know, we are pretty pleased to see the design activity. Yeah, Joe, you'll see it in we publish our CFO commentary. In the second page of the CFO commentary, you'll see we track three-year CAGRs, that we're really trying to grow the accounts through a complete contract cycle. Most of our customers do three-year baseline contracts, and then they do add-ons throughout the year that co-terminate with those baseline contracts. We think the three-year CAGR is a good metric. If you look at the revenue growth rate on a three-year CAGR basis, it's continuing to decline. Now, it's certainly the pace of acceleration seems to have slowed down this last two years in the kind of mid-teen mark. Our focus is on driving revenue growth, profitable revenue growth that we're using. We generate huge amounts of cash flow, and we aim to use more than 50% of that cash flow to buy back shares and reduce share count. We're trying to drive that non-GAAP EPS higher and be disciplined with our stock-based compensation. You'll see our stock-based compensation has consistently been around 8% of revenue, and our non-GAAP EPS CAGR, it's been 20% or higher for the last five years. With this 19% rate that we're on now at the midpoint of the guide, that has us on track for 22% EPS growth on a three-year CAGR basis for 2023. Our focus is really on bottom line. We care about EPS and growing EPS for investors and growing profitability. Revenue growth is a means to an end, I guess, in that respect, but we're very, very pleased that it's continuing to increase. Okay. thank you for that. One AI question I think is a follow-up on Jay Vleeschhouwer's questions, but just the point about, you know, it seems like maturity and, certainly customer experience, reference ability, you know, it's greatest in the back-end areas, it's greatest around Cerebrus. When you think about the pace of adoption on the things you've introduced into markets since last fall, do you think it's any quicker or slower than the experience with Cerebrus so far? So, like, is there any reason that debug and verification would not be a prime candidate for your, you know, underlying technology? I'm just wondering if you can maybe compare and contrast the, adoption curve. That's a good question. May I would say that the adoption curves are... At this point, I would say they are similar. You know, especially Verisium, as I said, verification is a big area. Now, they're easier in some sense that there is already a proof point that the customers have seen with Cerebrus, so they are confident in our ability to deliver overall AI solutions. Same thing with, like, Allegro X, you know, Virtuoso Studio. But also, you know how it is in this business, right? The customers have to try the things, and, you know, they try it on some design, then they do broad adoption. That's always there in new areas as well, like with Verisium and Allegro. I would say overall, it is similar, and there's a lot of interest. I mean, the amount of interest in other AI solutions, apart from the original ones like Cerebrus, is very high. I would say the rate at this point is similar of adoption. Yeah. This is going to take some time, which is okay. You know, it's a natural process of trying and deploying. Now, some areas, you know, it's faster, like hardware, because of the nature of the revenue recognition, but overall, the adoption is great and moving along. Great. Thank you very much. We'll take our next question from Gary Mobley with Wells Fargo. Hey, guys. Thanks for taking my question. I wanted to ask about the commercialization of the, you know, five different tools under the JedAI umbrella. I wanted to confirm something. First of all, are those products in baseline license renewals with customers, or are you licensing those on a per-ship design basis? Have the tools made their way from price discovery phase to general availability? Yeah. Hi, Gary Mobley. These all are new to products, so they're not in previous contracts. All of these products have to be, you know, purchased, and they can be purchased with the renewal or outside of renewal, as you know, in add-on business. They are not part of existing contracts with customers. You know, we have different business models in which we introduce these products, just like our base products. As we talk to customers, some of them are in very wide deployment. I think I gave example in the prepared remarks on one hyperscaler. We had a very, very wide deployment of some of these AI tools. Some are in the early stages, but these are all new products versus what was there in previous contracts. Got it. Got it. Thank you for that, Anirudh. I wanted to ask about what you're signaling with the acquisition of the PHY business from Rambus. I know you went through a period of time where there was a decision to maybe refocus some of the energy, some of the investments from the company away from IP into areas like SD&A. now you're making an acquisition to, you know, some aspect of your IP business. I'm wondering if you can give us an update on how you view the IP business as it fits with the overall business in terms of investment and effort? Yeah, IP is an important segment of our business. It's like having, you know, five kids, right? We love all the five kids, you know, all five lines of business. One of them is, you know, very young and growing, like SD&A, growing 20%+. That's great, but that doesn't mean we don't take care of all the lines of business. IP, this was a great opportunity to get a right team and IP, which is synergistic, useful for AI and 3D IC. I think at the right time, we will make investments in all lines of business, and we have done so, you know, like with Virtuoso, you know, with digital. We want to make sure all lines of business are competitive, yeah. Got it. Thank you, Anirudh. We'll take our next question from Andrew DeGasperi with Berenberg Capital Markets. Hey, DeGasperi, thanks for taking my question. I guess the first one I have is on the individual segments. I noticed the IP business in Q2 came down a bit, and also system analysis, slight deceleration. Just wondering if there's anything you would call out for those two, and I have a follow-up. Yeah, sure. Thanks, Andrew. In relation to IP, we've always been expecting more IP to be delivered in the second half compared to the first half. It's actually the opposite of 2022. I think we called that out on last quarter's call as well. We're expecting a stronger second half for IP, and IP can be a bit lumpy at times because it's based on the timing of deliveries. On System Design and Analysis, that we're very pleased with the strength of the growth there. Again, I mean, all of our businesses are growing strongly. I think when I look at the second half and the 15% that we expect our total revenue to grow compared to the second half of last year, I think all of our businesses and are growing double digits in that outlook. Got it. In terms of the guidance, if I were to look at the high end of the range for the top line, specifically, what exactly would assumptions would we have to make for you to get there or even exceed it? In other words, is there a potential for surprises, positive surprises on that front? I'm certainly very confident in the second half guide, but I'm now confident also in the Q3 guide. I was less confident when I saw all those hardware deliveries time for kind of the final week and the final few days of Q3, and I didn't want to take the risk of including those in the Q3 guide. For the second half, I'm very confident in the second half. As we as we reduce the lead times on our hardware, we found that we've certainly seen the demand for our hardware strengthen, and we've strong demand across the growth across all lines of business. As Anirudh said, I mean, design activity is very strong. I guess, you know, to the extent that we can continue to reduce those lead times and deliver hardware earlier, that's certainly a track to the higher end of the guidance range, because with hardware, of course, you get revenue upfront. On the software side, revenue takes longer to kind of play through because of the recurring revenue profile. Understood. Thank you. We'll take our next question from Harlan Sur with JP Morgan. Hi, good afternoon. Thanks for taking my question. The fact the full year is playing out as you expected, right, with the stronger second half in front of you, your semiconductor, your systems customers continue to drive strong chip packaging, system design, activity, and roadmaps, especially in the area of accelerated compute and AI. When you combine this with your pipeline, your renewal visibility, you guys have already said your second half bookings will be strong. Does the team believe that it can grow its backlog for the full year? In terms of backlog, we don't guide bookings, but I don't think it's unreasonable to expect our backlog to end the year higher than here, where we are here. Our focus is really on growing the annual value of that backlog. You know, a three-year software contract worth $10 million a year will add $30 million to backlog into RPO, and a two-year contract worth $12 million a year will add $24 million to backlog in RPO. If it's a choice between those two options with one customer, we'll typically take the $12 million a year, because $12 million a year is better than $10 million a year, and it'll be a lower booking number, a lower RPO number, but it'll show up in the current RPO. Like I said earlier, that, I mean, if you look at our Q2 backlog compared to Q1, it dropped down from $5.4 billion to $5.3 billion. If you look at our Q2 current RPO, that's the amount of our RPO that we expect to turn up in revenue in the next 12 months. At the end of Q1, with a higher backlog number, that was $2.7 billion. At the end of Q2, with a lower backlog number, that's gone up from $2.7 billion to $2.8 billion. Our focus is generally on the annual value, but I think I understand where your question is coming from, though, because first half was quite light for bookings. We expect the second half to be stronger. I do think that it's, like I say, not unreasonable to expect RPO and backlog to increase from here. No, I appreciate that. Then for Anirudh, you know, all of the leading-edge chip companies are moving to this chiplet, stack die-based packaging architecture. The system's customers are adopting these very, very complex board designs, right? Here you guys benefit with Allegro, Integrity, Clarity, Celsius platforms. Can you just give us a rough sense on the revenue contribution from advanced packaging and board design, simulation, verification? Is it near 10% of revenues? Roughly, how fast is this subsegment growing on a year-over-year basis? Yeah, that's a good observation, of course. I mean, there's a lot of chiplets-based design activity and it started in HPC, you know, the high-performance computing, AI. I think it will permeate to, you know, other parts, other verticals as well. Also all the leading foundries, as you know, are now leading with their 3D IC kind of solutions. You know, it shows up in different parts in our business. It definitely shows up in SD&A, because SD&A, you know, System Design and Analysis, includes both the Allegro and all the system analysis stuff, Clarity, Celsius. That's why you are seeing very, very strong growth. I mean, that's a very, very strong growth number, I would say, especially on a ratable- Mm-hmm ... revenue model, right? If you're growing 22% this quarter, you know, 20% plus for last several years. A lot of it is driven by this 3D IC chiplet, because the system market is interesting, right? The thermal market and the electromagnetic market, traditionally. A lot of the new growth is this intersection of chip and system, which is by nature, 3D IC and chiplet. We have a lot of customers buying, you know, thermal solutions, especially targeted for chiplets, because that's the big thing, or electromagnetic targeted for chiplets. We definitely see that in SD&A, and then we continue to see that in our regular business, you know, like Virtuoso or Innovus- Mm-hmm ... and digital. I still think this is still early inning. You know, it's still the, you know, baseball analogy, still the second, third inning for 3D IC, and it will become the dominant technology. I mean, of course, the 2 nm and 1.4 nm, all that will be critical, but they will be all integrated on chiplets and interposers going forward. What I feel, what I think what is important to remember, you know, of course, a lot of people talk about chiplets and 3D ICs, but we are uniquely positioned. Not only for chip implementation, but also for package design. We provide the leading, we are the leading software provider for package design with Allegro, and all the thermal and system analysis tools. I think Cadence is, I believe, very uniquely positioned to benefit from chiplet and 3D IC. Well, thank you for the insights. We'll take our next question from Gianmarco Conti with Deutsche Bank. Hi, Anirudh and John, and thanks for taking my questions. The first one is, I know you've touched on this a little bit. Could you share some more color on the usage of AI tools in system companies this quarter? Are any of the new wins related to AI tools for system customers? How can we think about the acceleration of usage, not just leading nodes, but in the broader design space, even at more mature nodes? I think investors are thinking, what next when taking the current use cases of the next two, three years, where the cost trade-off might not be as imperative as per se in the GPU market. I imagine, is this a function of better price discovery matched with higher adoption/proven use cases? Yes, I think the application of AI is, as you know, has both horizontal and vertical components, right? Horizontal is building out the AI infrastructure. Those in the beginning tend to be, you know, advanced node GPUs and also system companies. The system companies we mentioned, of course, one of them is Tesla, right? That's a, you know, they have a server-side chip. I mean, they have talked about this, which is Dojo, and then also in the car, right, with Full Self-Driving. That, I think, is a pretty, you know, pretty remarkable use of AI that's only going to grow with other companies doing this, other auto companies doing similar things. We have several customers, you know, which are hyperscalers, which are building their own silicon for AI. I mean, this is well-publicized also, you can guess who they are. We are continuing to work with them, and we had several meaningful expansions in Q2 linked to AI chips done by, you know, these large hyperscale companies. Now on the vertical side, it can applies to our all of five main product portfolios for AI, that, like we talked, which are built on JedAI. Those, that application in EDA and SDA is not node dependent, because that can be in all nodes. Even the very horizontal AI application, I think it started at advanced node, but it will go to mainstream nodes because of edge computing. You know, the edge computing doesn't need to be at 3 nm or 2 nm. The, especially the vertical ones, when we put it AI in Virtuoso or Allegro or, you know, verification, these can be applied across all the nodes, not just the advanced node. The potential, the benefits are there, we are seeing are independent of the nodes, you know. To just to give you example, you know, like in some cases, you know, depends on the design, and on some cases, we can get like 10%-15% PPA benefit from AI. If you go from 1 node to another node, sometimes the benefit is 10%-15%. You're getting as much benefit from better AI algorithms as moving to a new node. It also improves the efficiency at your current node. I think in terms of applying it to EDA and system design and analysis, that will be node independent. Got it. Just a follow-up on hardware. Could you talk about the renewal cycles for hardware? When do you expect a customer to come back and buy a newer generation of Protium or Palladium? If it's in line with the EDA cycle, I need to enhance for three years. Yeah, that's a good question. Typically what we see, hardware purchases are tied to their design cycles and sizes of the chips, not necessarily tied to our, you know, when we introduce our new systems. You know, that can help, you know, when we go from Z1 to Z2. Typically, you know, any big customer will typically buy hardware every year, because of they are doing more designs or the design size is going up. If the design size goes up, they need to consume more hardware. That's why this hardware business has been so good over the last, you know, four or five years, because it's not a, you know, one-and-done kind of purchase. You need to buy multiple times as you do bigger and bigger chips and more chips. We have multiple lines now, Palladium and Protium, so it makes it much less cyclical than you would expect or what it was like two years ago. There's a secular demand for hardware capacity, or emulation capacity. That's, it's a pipeline business. Unlike our software business, where you know when the existing contract expires and you know the renewal opportunity comes up, typically, we see... You know, in the past, we used to see a hardware customer come back and purchase a new system, maybe, you know, 2.5, three years after the first system. Now they're purchasing new systems regularly because, like I say, demand is, is really, really strong, and there's just a secular trend in that demand for growth and emulation capacity. Got it. Thank you. Our final question comes from Joshua Tilton with Wolfe Research. Hey, guys. Thanks for sneaking my two questions in here. The first one, I want to go back to the, to the full year guide. I know that you guys mentioned that you expect, I think, hardware to grow 15% year-over-year in the second half. What about compared to the first half? Are you still baking in any conservatism in the hardware guide relative to the strength in hardware that you saw in the first half of the year? Joshua, just to correct that, the expectation for 50, 15% growth in the second half is comparing second half versus second half for total revenue at Cadence, all our businesses. We expect all of our businesses to grow by double digits in the second half compared to the second half of last year. Some more, some are stronger than others. In relation to hardware specifically, we've seen strong demand pretty consistently for a couple of years now. In Q1, we ramped up production capacity because lead times had gone over 6 months. We tried to address those, and it certainly helped with improved demand in the second quarter, and we're seeing more opportunities in the pipeline for the second half. That gave us comfort to raise the guide for the second half of the year. It is a pipeline business. Typically, people only put their opportunities into the pipeline about a quarter before they intend to purchase. In some cases, you might get visibility, you know, four to six months in, but it's a pipeline business. Right now, we have strong backlog for hardware, and that's fed into our decision to increase our guide for the second half. There is potential for that demand to continue. If we're going to keep production capacity at the levels we're at right now, because we expect that demand to continue into the future. Thanks for for clarifying that. Just my second one, in the prepared remarks, I think you guys used the word full flow and Cerebrus in the same sentence. Are you seeing a dynamic where maybe your AI tools are driving more of your customers to want to choose to go full flow with Cadence? Yes, absolutely. That's a very good observation. I mean, one trend that is driving full flow adoption is, you know, advanced nodes. When you move from seven to five to three to two, that, you know, because things get more complicated and we architected this, you know, years ago to be, you know, full flow. That helps. Secondly, that helps is AI orchestration or Cerebrus, because it can give better results if the AI engine is able to optimize all aspects of the flow. There is a natural tie-in to that, which is great for us. You know, this is a fabulous thing, you know, and the same thing in other areas as well, like verification. Both these trends are accelerating the deployment of full flow, advanced nodes and AI. Thank you very much. I will now turn the call back to 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. With a world-class employee base, we continue to deliver on our innovation roadmap and delight our customers and partners. On behalf of our board of directors, we thank our customers, partners, and investors for their continued trust and confidence in Cadence.