Good afternoon. My name is Beau, and I will be your conference operator today. At this time, I would like to welcome everyone to the Cadence Q3 2023 earnings conference call. All lines have been placed on mute to prevent any background noise. After the speakers' prepared remarks, there will be a question and answer session. If you would like to ask a question during this time, simply press star, then 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, sir. Thank you, operator. I would like to welcome everyone to our Q3 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, and we disclaim any obligation to update them. In addition, we will present certain non-GAAP measures, which should not be considered in isolation from or as a substitute for GAAP results. Reconciliations of GAAP to non-GAAP measures are included in today's earnings release. For the Q&A session today, we'd ask that you observe a limit of one question and one follow-up. Now, I'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 Q3 of 2023. We exceeded our Q3 guidance on all key metrics and are raising our outlook for 2023. John will provide more details on our financials shortly. Notwithstanding the macro uncertainties, design activity remains strong, driven by transformative generational trends such as AI, hyperscale computing, 5G, and autonomous driving. Growing hyperconvergence between electrical and mechanical domains, systems and semis, and hardware and software is driving the need for tightly integrated co-design and analysis solutions. Additionally, trends such as growing number of 3D-IC and chiplet design and system companies building custom silicon are accelerating. In this rapidly evolving design landscape, the relevance of AI-driven design automation cannot be overstated, as it's enabling customers to accelerate their pace of innovation while enabling them to meet their targets more efficiently. Over the past few years, we focused initially on incorporating powerful AI algorithms in our core engines and then build our generative AI solutions on top of our software platforms. We are seeing growing momentum for our comprehensive JedAI generative AI platform, with an increasing number of customers adopting these solutions and achieving exceptional quality of results and productivity gains. While still in the early stages, sales of our Gen AI solutions have nearly tripled in the last year. Our solutions are enabling marquee AI infrastructure platform companies to deliver their next-generation compute, networking, and memory products. Last quarter, we had referenced our successes with NVIDIA and Tesla, and this quarter we are pleased to announce that Broadcom has accelerated the adoption of Cadence Cerebrus across multiple business units, achieving impressive quality of results. In Q3, we pioneered leveraging Gen AI's LLM capability to chip design, successfully collaborating with Renesas on accelerating functional specification to final design. This is a key step in demonstrating the potential of LLMs to automate the translation of natural language specification to final chip design and verification tasks, thereby boosting their quality and efficiency. We also renewed and deepened collaboration with some large semi and system customers in the 5G, AI, hyperscale, and connectivity areas. For instance, we strengthened our long-standing partnership with a global marquee systems company through a significant expansion of our EDA software, hardware, design IP, and system solutions. As the digital transformation in aerospace and defense accelerates, we continued our momentum by enhancing our core EDA and systems footprint with several customers, including at two market-shaping companies. Now, let me share some of the business highlights, starting with digital IC. With 11 new wins, our digital full flow, delivering the industry's leading quality of results at the most advanced nodes, continued proliferating with market-shaping customers. We are very pleased with the accelerating momentum of our flagship Cadence Cerebrus Gen AI solution, whose transformative results have led to its deployment at all of our top 10 digital customers and in about 300 tape outs to date. Imagination Technologies uses Cadence Cerebrus and our digital full flow on its latest 5nm GPU design in the cloud to achieve a 20% reduction in leakage power. Next, I will talk about our functional verification business, which had another strong quarter with 18% year-over-year revenue growth. Ever-growing system design complexity, coupled with the need for first-time right silicon, continued to drive strong demand for our Palladium Z2 and Protium X2 hardware platforms that provide industry-leading system verification and software bring up capability. Our hardware business had a record Q3, with close to half of the hardware orders, including both platforms. Highlights for the quarter include a major Dynamic Duo expansion with a top AI and automotive chip supplier, and a significant deal with the market-shaping data center chip company. Our flagship custom IC business continued to pave the way in analog innovation, delivering 15% year-over-year revenue growth. We are pleased with the reception of our AI-driven Virtuoso Studio solution, as several marquee customers adopted for their N2 and N3 designs. It has close to 1,000 downloads since its launch six months ago. Nisshinbo Micro Devices utilized the Virtuoso Studio custom IC design platform to gain a 30% reduction in turnaround time for routing analog blocks. In Q3, we continued investing in our IP business and closed the acquisition of the Rambus PHY IP assets. Customer reception has been overwhelmingly positive to the addition of their HBM and GDDR IP to our Star design IP portfolio. Design IP had a record booking quarter with strong AI and chiplet design activity, especially in the mobile, automotive, and hyperscaler verticals. In addition, we launched our Tensilica Neo NPU IP and NeuroWeave software tools to accelerate on-device and edge AI performance. Our system design and analysis business that is driving our expansion beyond EDA continued to deliver strong growth, increasing revenue by 20% year-over-year. On the PCB front, Allegro X AI has several successful engagements with market-shaping customers underway, and we announced OrCAD X, our next-generation AI-driven PCB design solution, enabled by Cadence OnCloud and targeting small and medium businesses. Our Fidelity CFD platform continued its strong momentum with customers in automotive, aerospace and defense, and industry verticals. In summary, I'm pleased with our team's continued innovation and execution. We are well-positioned to benefit from the tremendous opportunities ahead as we help customers design their differentiated products with improved quality of results, productivity, and shorter time to market. I did want to take a moment to comment on the unfolding conflict in the Middle East. The ongoing violence and loss of innocent life is truly heartbreaking and a matter of global concern. The well-being of our employees and their families in the region is of utmost importance to us, and we continue doing everything we can to support them. Our thoughts are with everyone who has family, friends, and loved ones there, and we are helping out by providing humanitarian aid through the Cadence Giving Foundation. John will now go through the Q3 results and present our Q4 and updated 2023 outlook. Thanks, Anirudh, and good afternoon, everyone. I'm pleased to report that Cadence delivered another strong quarter of top and bottom-line results in Q3. All businesses contributed to revenue growth, and we completed more hardware installations in Q3 than we originally assumed. Here are some of the financial highlights from the Q3, starting with the P&L. Total revenue was $1.023 billion. GAAP operating margin was 28.6%, and non-GAAP operating margin was 41.1%. GAAP EPS was $0.93, and non-GAAP EPS was $1.26. Next, turning to the balance sheet and cash flow. Cash balance at quarter end was $962 million, while the principal value of debt outstanding was $650 million. Operating cash flow was $396 million, and we used $125 million to repurchase Cadence shares in Q3. Before I provide our updated outlook, I'd like to highlight that our outlook contains the usual assumption that 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 $4.06 billion-$4.1 billion. GAAP operating margin in the range of 30.5%-31%. Non-GAAP operating margin in the range of 41.5%-42%. GAAP EPS in the range of $3.48-$3.54. Non-GAAP EPS in the range of $5.07-$5.13. 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. As a result, for Q4, we expect revenue in the range of $1.039 billion-$1.079 billion. GAAP operating margin of approximately 31%. Non-GAAP operating margin of approximately 42%. GAAP EPS in the range of $0.85-$0.91. Non-GAAP EPS in the range of $1.30-$1.36, and we expect to use approximately $125 million of cash to repurchase Cadence shares. As usual, we've published a CFO commentary document on our investor relations website, which includes our outlook for additional items, as well as further analysis and GAAP to non-GAAP reconciliations. In summary, we are on track to deliver a strong 2023. I am pleased with our team's continued execution of our Intelligent System Design strategy strategy. With our updated outlook for 2023, at the midpoint, we now expect revenue growth of approximately 15%, non-GAAP operating margin of approximately 41.75%, a seventh consecutive year of greater than 50% incremental operating margin, and non-GAAP EPS of $5.10, a sixth consecutive year of high teen or better non-GAAP EPS growth. As always, I'd like to close by thanking our customers, partners, and our employees for their continued support. And with that, operator, we will now take questions. 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 now. We ask that you please limit yourself to one question and one follow-up question. We will pause for just a moment to compile the Q&A roster. Your first question comes from Charles Shi at Needham. Hey, good afternoon. Thanks for taking my question. I wanna ask you a little bit about the backlog. It looks like the backlog, compared with last quarter, was up. I mean, the September quarter kinda implies really good bookings for September quarter. Just wanna ask, do you see the backlog will continue to grow into the year-end? And 'cause you talked about the second half booking strength. I wanna see where it goes from here. Thank you. Yeah, Charles, thanks for the question, and thanks for remembering what we said last quarter. Yeah, we expect a very strong second half for bookings, and Q4 is exceptionally strong. But, so our expectations for bookings is very, very strong Q4. Thanks. Maybe I wanna ask one quick follow-up. You kind of raised your full year revenue outlook a little bit less than you beat the Q3 in terms of revenue. Kinda implies that your full year outlook you provided one quarter ago was largely accurate, but there seems to be some timing shift for the revenue. I mean, pulling in from Q4 to Q3, was that related to your comment about hardware installation, the timing of that? Thank you. That, that's right, Charles. You know, in hindsight now, I was a little too prudent in the Q3 guide with respect to hardware installations that were scheduled in China around the end of September. If you recall, in our guide, we assumed that those installations would fall into Q4. In actual fact, we completed those hardware installations, and the second half looks stronger than we thought this time last quarter. But you know, even with all of those hardware, we kinda beat our expectations in Q3, and Q4 is higher than we thought. Thank you. Thank you. The next now, Gianmarco Conti at Deutsche Bank. ... Yeah, hi. Thank you for taking my questions. I guess my first one would be, when do you expect to be giving out more AI KPIs, whether on contract value at risk or penetration rates? And just like any color you can provide us, and how can we quantify the AI tailwinds in your numbers, and whether we are going to see this, you know, coming through in bookings in some time? Thank you. Yeah, hi, this is Anirudh. Let me take that. So, you know, like we mentioned in the prepared remarks, we are seeing a lot of activity in AI, and that's a, you know, multiple customer and multiple verticals. So whether it's the system company designing their own chips or, of course, the semiconductor companies designing it. Or we mentioned this time, for example, Broadcom, which helps, you know, other companies design it. So we are participating in the AI kind of design process in all three ways. And last time we talked about, you know, NVIDIA and Tesla. And then on top of that, it's also applying AI to our own products. And then we have these extra generative AI products on top of our base products that also drives revenue. So the first part, which is, you know, build out of the AI infrastructure, whether it's with, you know, of course, large semi companies like NVIDIA or like large system companies like Tesla or companies like Broadcom, I mean, that's a big part of our business. We don't break that out specifically, because it's sometimes difficult to figure out exactly, you know, what part of customers' business is AI or not, and we don't want to be in that, kind of to try to guess, you know, what part of our, what the customers are using it for. But AI is a significant portion of, you know, design activity and the build-out that's going to happen for years. Okay? Now, there's a second part of our business in which we are selling AI products ourselves, you know, like, you know, like Cerebrus and Verisium and our JedAI platform, which has five main products. So in that segment, if our own software products and IP products are AI-enabled, so in that we did comment that even though it's early in the process, our revenue from our own AI products has almost tripled from a year ago. So we are very pleased with that progress. So I just wanted to highlight that and also say there's another part of AI, which is the build-out of infrastructure, which is more difficult to predict, yeah. And, Gian, I would just add to that, you know, when Anirudh calls out that, you know, the revenue from those products has almost tripled in the space of 12 months, we're not reclassifying any revenue. This is direct revenue attributable to those five products that we have in our JedAI platform. Right. That's, that's really good. Thank you. I just have a follow-up, perhaps, talking a little bit on China. If you could comment on whether there is any impact from the, you know, the entity list and, and the new, the new rules coming into place. And also, if you have any visibility into Chinese customers, into trying to understand whether you actually know, whether they're designing at more mature versus advanced nodes. I feel like there's been a lot of conversation, around whether there is a way to track, you know, whether EDA tools are being used in China for, for mature versus advanced nodes. You know, any color that on, on, on this it, it would be great. Thank you. Yeah, that's a good question because there were a lot of, you know, recent reports on some of the changes in regulation. So for us, you know, there's not that much difference. You know, most of the regulations were targeted at some chip companies or manufacturing companies. As you know, we are in the design process, so those regulations, the latest round, it doesn't have a, you know, a big effect on Cadence business. Now, there are some companies added to the entity list, you know, so we monitor that carefully. But since we are so diversified geographically and, you know, in terms of customers, you know, that's not a significant impact either. And all our guidance that we just gave includes the impact of all these regulations that were announced recently. Of course, we carefully follow all U.S. regulations, but the latest change is not that material to our business. Yeah. Got it. Thank you. Thank you. We go next now to Harlan Sur at J.P. Morgan. Good afternoon. Thanks for taking my question. You know, macro conditions in the semiconductor industry are still fairly muted, right? We're, we're close to a cyclical bottom, but recovery seems more gradual than expected across many different end markets, right? Accelerated computing and AI are strong. Auto, industrial, enterprise, service provider markets, still relatively soft. So across the metrics that you track, renewals, hardware buys, IP take rates, is the team seeing any signs of hesitation or pushouts across your different customers or different businesses? Yeah, Harlan, that's a good question. You know, like we mentioned last time, you know, we still see a lot of strong design activity. And I would say compared to like three months ago, I would say the activity is similar, you know. Like you mentioned, some segments are going through tough times, and then some segments, like accelerate computing AI, have a lot of growth. But overall, as you know, these products, you know, that our customers are designing, you know, take several years to develop, and we are part of the R&D cycle. So what we see is the customer is still investing in R&D for building out products for the future, and we are glad to, you know, partner with them. So, I think I would say that largely the environment is similar than it was like three months ago. Yeah. Yeah, absolutely. And on the hardware side, we're producing hardware as fast as we were all year. And you can see in our Form 10-Q that we filed today, that, you know, the value of finished goods in our inventory was less than $10 million at the end of the quarter in Q3. So demand is really strong still, and we're just producing the hardware as quickly as we can. But we're expecting a very strong Q4 as well for our IP group. I mean, they're delivering a number of silicon solutions to our customers in Q4. And I think that sets up a really strong quarter for that group, but we were expecting that all year. Yep. No, appreciate the comments there. You know, one of your large AI SOC customers recently laid out their future roadmaps, right? And given the complexity of all these next generation AI compute workloads, right, they're actually accelerating their chip roadmaps. So new GPU chip every year versus every two years, which was their prior cadence. And then on top of that, they're starting to segment their product lines, right? So not only accelerating roadmaps, but more chips per product family. I've got to believe that other competitors in this space are doing exactly the same thing. Are you guys seeing this step up in design activity? Obviously, much higher productivity is required. So how is this all being sort of reflected in the business momentum and your visibility? Yeah, good point. I mean, like, like you said earlier, you know, the macro environment is, is challenging, you know, especially some of the segments are, are weaker, some are stronger. But, you know, design activity is very strong. And especially, I would say in, in two verticals for the future, you know, for the future of the semi and the system business. And, you know, at least the two very, very strong verticals in terms of design activity is data center and AI, and then automotive, given the- Mm-hmm ...electrification and, and the massive transformation that's happening. So if you look at even, you know, you know this anyway, you know, Harlan, if you look at for the next, you know, three, four years, you know, these two segments will grow significantly. You know, the whole AI-driven data centers- Yes ... and automotive. Because they are growing so fast, first of all, the cadence of those, you know, end customer products is increasing. And also, you know, they need to be more and more efficient given the design activity and complexity is going up. So there's more design activity and also use of AI to accelerate and be more productive. Mm-hmm. And even we are using AI internally to be more productive ourselves. So definitely for these two big, big verticals, and this is a multi-year trend, you know, this is not a, And you mentioned some of our large customers we are very fortunate to work with. You know, we always say we want to win with the winners, and we always focus on the leading companies in the data center and AI space, and also now in the automotive space. So that activity is strong, and I, I expect that, you know, to continue. Yeah. Yeah. Well, thank you. Thank you. We go next now to Gary Mobley at Wells Fargo. Hey, guys. Thanks for taking my question. John, your upfront license revenue year to date has averaged around, around 17%. I think typically it's 15%. Given where you're at in the verification of hardware product cycles, Z2 and X2, and the conversion of the backlog there, how do you see that upfront revenue trending, you know, looking into next year? And related to that, you know, how would you see the influence on overall growth next year? Yeah, great question, Gary. I mean, we're, we're always watching that carefully. As, as you know, last year, the upfront piece ticked up to 15%. This year, I, I think in the Form 10-Q, if you look over on a rolling four-quarter basis to the end of Q3, it's at 16% now. But I take your point, it's probably closer to 17% for the first three quarters. But, but I think that's a reflection of the strength of, of, of hardware on the ratable and recurring part of the business. Although that's 84% of the trailing 12-month revenue. If you look at our guide at 40/80, I mean, we're assuming essentially about a 13% growth rate on a recurring revenue line for the year, but that's consistent with like over a three-year CAGR basis is about 13% as well. Okay. Of course, we're not guiding next year. Understood. Understood. All right. But I suspect that we're not going to get any more AI metrics out of you, Anirudh, but maybe if you can just give us a sense of where we're at in the commercialization of the five different AI tools. Have those started working their way in the baseline license renewals, or are they still on a per design basis? And maybe it gives a sense of where you expect them to cut into, you know, baseline licensing activity. Yeah, Gary, that's a good point. So we are watching that carefully, of course. And as you know, like, these JedAI and these five major platforms are new products that our customers, you know, should engage with us on, and they run on top of our existing kind of leading platforms. So, you know, it depends on the customer. I would still say we are still in the early stages of the adoption of these AI products, because as you know, any of these new software tools take years to fully deploy, right? I mean, this is what happened in digital or, you know, in any major kind of platform releases we do. So even though we are, like, two years into it, I think it'll still take some time to fully deploy these products. And what we have said in the past is, as typically, you know, at least in my experience with digital, you know, like about seven, eight years ago, it took, like, two contract cycles for them to fully deploy, okay? So that's still three, four years to go. You're probably, like, two, three years into it and still three, four years to go. Which is a good thing in my mind because, you know, this is natural progress of deployment. Now, it depends on the customer. You know, some customers are adopting them in a much bigger way, you know, especially, like in the previous discussion, you know, the new kind of AI designs or hyperscalers. You know, there is, like, a improved Cadence of design activity, so they are adopting them maybe a little faster than some of the other verticals. So it just depends on, some are still on, like, you know, try it on few designs or, or few groups. But we have seen some pretty broad, kind of deployments, and that helps our overall engagement with that particular customer. So, so that's what I would like to say, Gary, that I think it's still early, but what good thing I think we mentioned in the prepared remarks, that all top customers are now fully engaged, and some of the results are truly remarkable. Actually, I was talking to one major customer recently, and they are getting, you know, like, 8% to 10% power improvement from Cerebrus, okay? And we have mentioned several of these in the past also. I mean, that's a huge improvement. You know, sometimes that's equivalent or roughly equivalent to a node migration. You know, typically you go from one node to another, you may get, like, 10% to 15% PPA improvement, and you're getting close to that or, you know, roughly, you know, 2/3 of that from better AI tools. So the value is there, and, you know, that's what we are focused on, make sure the products really provide value, and then work with the customers in the pace of deployment that they want to see, because it's a natural process to try some and then deploy. But some of them are doing it much faster, like I mentioned. Yeah. Thank you both. Thank you. We go next now to Jay Vleeschhouwer at Griffin Securities. Thank you. Good evening. For my first question, I'd like to ask a variant of the EDA market environment question. So on the one hand, what are you seeing in terms of unscheduled new business? That is to say, intra-contract, new or expansion business that could be construed positively. On the other hand, how concerned are you about the evident deceleration of semi-R&D growth? It's still reasonably good, better than four or five years ago, but so much slower than it's been. A lot of that can be attributable to Intel, but still, how are you thinking about, you know, those two different dynamics? And then I'll ask the follow-up. Yeah. Hi, Jay. Good question. I mean, we're just watching it carefully. You know, like you said, like we said earlier, I mean, design activity is still strong, but of course, the macro environment is challenging. You know, it's like natural—even though the customers realize that, you know, they need to invest in R&D for the future, if, you know, the revenue is impacted because of macro situations, you know, that decision become a lot more prudent, you know? But so this is just natural, you know, business process. But in general, you know, still the large customers and the big segment, they're all investing in R&D. Design activity is still strong. And then we just have to see... You know, we had a good Q3 in terms of bookings, like we mentioned, so we'll see what happens in Q4, and that will also give us a better idea, you know, going forward. Yeah, Jay, as you know, a lot of our customers come back and purchase add-ons during the course of their baseline contracts. And with the teams releasing significantly new business, new products from the different R&D groups, the customers have an intent to come back and keep purchasing. So they don't wait. When we launch AI tools, they don't wait for the baseline renewal to come up or to expire to purchase them. They'll purchase add-ons, and they'll purchase a few licenses and then hopefully proliferate more on the contract renewal. And as you know, we have a lot of contracts that come up for renewal in Q4. Understood. For follow-up, I'll ask about some interesting Cadence management comments at last month's CadenceLIVE event up in Boston. So there was an interesting comment about the role of AI as, quote, "De-risking schedules," in addition to the design exploration use case. And what's interesting there is historically, you know, schedule risk or completion risk has to do more towards the back end of the process, you know, for example, physical verification. So to the extent that more of that risk mitigation moves up earlier in the process, do you think that there will be a spending share shift within the totality of EDA spend, perhaps some from the back end, more towards the front end, where you play with a lot of your tools? Hey, Jay, I would say that it should lead to more design activity if we are able to reduce risk in the design process. I mean, as you know, this is the history of EDA, you know, history of automation, even for the last 20, 30 years. You know, I remember in the old days, in the 1990s, we would take, like, five years, you know, and 500 engineers to design some big chip, and now that takes, you know, six to 12 months and, you know, maybe 50 engineers. So that's, like, 100 times more efficient than 25 years ago. And I think AI can, as you know, provide the next generation, next level of improvement in productivity and risk mitigation. I mean, part of it is also risk mitigation. So then I think it should lead to more design activity, especially by the system companies. Now, the shift of front-end to back-end, I mean, I think back-end is still a complicated process and, you know, so I think even though some of the things can be pulled up front using AI or using, you know, hardware platforms, I still think the back-end design process requires, you know, a lot of work. So I would expect it affects all of them. And then the other thing we are trying to do on the front end, as you may have noticed, is really incorporate LLMs, you know, like our partnership with Renesas, because a lot of the front-end process has been less formal. You know, the back-end process, you know, especially once we have RTL, then we go to gates, we go to GDS, it's a very formal process, very structured process. But the front end of the process, especially verification and specification, has been less formalized, and I think AI and LLM can help formalize that, which definitely, like you said, can minimize the risk. But I think activity should still be strong in both front end and back end. And our goal anyway is to make the design easier, so more customers and more people can do them. Thank you, Anirudh. Thank you. We go next now to Jason Celino at KeyBanc Capital Markets. Great. Thanks for taking my question. Maybe first for John, you know, on the Q4 guide. Apologies for asking this again, but so folks might be wondering tomorrow, I guess, why aren't we seeing more upside to the guide for fourth quarter? Where might be some conservatism or what, why we be overlooking in terms of the setup? Oh, yeah, Jason, as you know, your question probably emanates from the fact that, you know, we beat by $23 million in Q3 and raised by $10 million, but that was mainly due to a prudent guide for Q3 with respect to certain hardware installations. I think overall, we've taken the quarter up by or the year up by $10 million at the midpoint. But I think there's because it's expected to be a strong bookings quarter and a particularly strong quarter for our IP Silicon Solutions group, that, I mean, they're having... They're going to have an excellent Q4, but we're expecting that all year. I think if there's upside, it'll probably come from that group. Okay. Okay, no, that's fair. And then just my quick follow-up on backlog. You know, I know you've got some weird comps because of the hardware stuff, but when might we see, like, year-over-year growth again? Or I guess if we stripped out the hardware-related backlog, I don't know if there's any way to share what type of growth you might be seeing. Yeah, I think just to give you a bit of color on that, I think if you recall, at the end of last year, our backlog included about 28 weeks of lead time on hardware. I think we're down to an 8-10-week range now on lead time for hardware. So, of course, you know, we've eaten some backlog as a result of that. But I think we topped out essentially in the middle of the year. You know, we're expecting the second half to be stronger for contract renewals because the number of contracts expired in the second half. In Q3, you saw backlog starting to tick back up again. We'd expect it to tick back up again in Q4 because we have a strong bookings quarter, or we're expecting a strong bookings quarter. The one I'd look for really is the annual, the kind of CRPO is the one I track because I'm looking at the annual value. And I think when you compare the annual value at the end of this year with the annual value of backlog at the end of last year, the thing to remember is the fact that there'll be so much less hardware in it, I would expect, because we have the production capacity now to deliver on the hardware. Okay, perfect. Now, super helpful. Thank you. We'll go next now to Vivek Arya at Bank of America. Thanks for taking my question. I appreciate it's early for a 2024 outlook, but, Anirudh, I was hoping that you could give us some color, you know, given that your model is 85% recurring. So just conceptually, what is the likelihood Cadence can maintain this kind of mid-teens growth rate? And what would make 2024 different or similar to 2023 from a growth perspective? Yeah. Hi, Vivek. You know, like, like before, you know, we, you know, in Q3, you know, we don't comment on, on the next year. You know, we, we are diligent. We want to make sure we finish out the year, see what Q4 looks like, and then we'll be glad to share, you know, our assessment in, in our next, you know, in the, in the full year, in the February earnings call. And that's what we have done in the past, and that has worked out well, right? Okay. On the IP side, I think, John, you mentioned that you're expecting a strong quarter for IP in Q4. I was wondering how much would your two recent acquisitions contribute to that? And just longer term, do you think IP as a category over or under grows EDA, and does that influence your growth prospects? So both kind of near and longer-term question on the IP business. ...OK, but, let me take the first part of that, and then I'll hand it over to Anirudh for the second part. I think in relation to the IP business, like I say, we're expecting a strong Q4 for that group. But, I mean, if you look at the guide we've given for the year, essentially, we're guiding to 14% to 15% revenue growth for the year, which means Q4 over Q4 is going to grow kind of between 15% to 20%. Now, largely, that's due to the strength of our IP business in Q4. Do you want to talk about the longer term? Yeah, I mean, as you know already, you know, more customers are outsourcing, you know, their IP needs, and we have always, you know, participated in that. And we have always said, you know, we want to participate in that in kind of a star IP portfolio so that it's more and more profitable. And the profitability of our IP business has improved over the last few years. And so I think we are overall, you know, happy with the profitability of the IP business. So now we're trying to see, okay, what other areas can it grow and maintain profitability? And I think the areas that are emerging, which are strong, are this whole chiplet-based design and 3D-IC, and which are used for a lot of AI and hyperscaler applications. That's also the reason, you know, we bought the PHY assets of Rambus, you know, which is the HBM and GDDR-based IP. So I feel now that our IP portfolio is in the right areas, and also the use of this in automotive and hyperscaler and AI IP. And most of these markets are evolving into chiplet-based and 3D-IC-based designs, which also have certain new IPs like UCIe and other things. So as a result of that, we are investing more in our IP business, as you saw, and then, you know, we expect a strong Q4, and then we'll see what happens in 2024. Just to clarify, the contribution from acquisitions is likely to be immaterial for this year. So the strong Q4 that we're expecting is really from organic business. Thank you. Thank you. We go next now to Ruben Roy at Stifel. Thank you. Anirudh, I wanted to ask if you could maybe talk a little bit more in detail about the collaboration with Renesas and kind of incorporating generative AI, LLM to chip design. I think you mentioned you know, some expectations for quality improvement, efficiency improvement. I would think that, you know, longer term, you'd be thinking about productivity improvement as well. Are those milestones, you know, that, that you're expecting to have answers about within the next year or two years? It, it sounds like this is, you know, sort of a longer-term collaboration and, you know, sort of testing going on today. Just wondering, you know, sort of what you're thinking about timeframe in terms of incorporating some of these types of tools into chip design. Along with that, you know, just the final part is: would you consider this a leading-edge design that Renesas is working on? Or, or if you could talk a little about the type of design, that'd be great. Thank you. Yes, absolutely. So, I mean, we are very pleased with the collaboration with Renesas, and I think they have a whole initiative, if you, if you follow them or if you look into the, you know, AI for their design process. And we are glad to be, you know, a very close partner with Renesas, as we are with, with other companies, right? So we just wanted to highlight Renesas this time, and the col- collaboration is, is broad-based. I think they're using almost all of our AI tools, you know, whether it's Cerebrus for digital or, you know, verification, you know, Verisium and other tools. And also we are doing some, you know, new collaboration with them on LLM, like we mentioned. And, you know, the LLM collaboration is fairly, you know, broad-based. It can be applied to any kind of design. You know, especially Renesas has a range of design, all the way from advanced node to mainstream nodes. You may know all this already, but the key thing, you know, one benefit of AI is that, you know, there is a—Of course, the quality of results can be better, you know, productivity can be better, but there are other benefits which are also true for large, kind of global companies like Renesas. And the two that I would like to highlight, which came to, you know, the forefront with our partnership with Renesas. One is, you know, all these large companies have geographically diverse teams, right? It's not that the team is only in one location. Typically, they are in multiple locations. So the good thing with AI is that, you know, and we can, we can do, you know, in a lot of cases, design better than, than a human can do. But also it depends on the starting point, right? So if you have a geographically diverse team, not all teams are, are super experts. So if the AI tool is same or better than your best team, then the, the reason to deploy it is that wherever, you know, just by the nature of, you know, human productivity, there's a variation across the organization. You know, the results can be even greater in your teams, which are, were historically not performing as, as well as you would like. And the other thing is also true in terms of experience, and this will happen, I believe, in AI, in other industries as well, but it's definitely happening in chip design. You know, so if you have three years experience doing chip design versus 20 years experience in chip design. Okay, with AI, you know, that gap is narrowing. So, you know, less experienced engineers can be almost as productive as more experienced engineers. So apart from like, productivity and quality of results benefit, it has this other kind of almost, workforce management benefit for large organization like Renesas, because they have organization in multiple locations and also a wide experience range from, you know, young engineers to experienced engineers. And this we are seeing in other companies as well. And I think the what is also interesting is that the companies that adopt these AI tools first and faster will benefit more, you know, versus their peers. So we are seeing that the fast-moving companies, and Renesas is definitely one of them. Then we talked about, of course, Broadcom, we talked about NVIDIA, we talked about Tesla, and there are so many other kind of great large multinational companies we have the privilege of working with. There are more than one. There's a whole workforce development benefit of AI, which is actually quite profound. Yeah. That's very helpful. Thanks for all that detail, Anirudh. I guess just a quick follow-up. I mean, it sounds, you know, from what you're saying, this should be incremental. I mean, EDA has grown nicely. If you look at the core EDA growth over the last several years, you guys like to call out the three-year CAGR. But from what's going on here, we should assume that this would be incremental on, you know, sort of the way you've seen EDA growth. Would you—can you comment on that, you know, as you think about, whether it's software renewals or adding, you know, add-ons, as John talked about, you know, over the next 12, 18, 24 months, would you say this would be incremental to sort of that, you know, mid-teen growth that the EDA tools have been growing at, you know, over the, over the last three years or so? Well, I would comment on that. That's just, I think our style at Cadence is to be patient with our customers, and we'll go at the pace that they're ready. As Anirudh said earlier in the call, you know, we expect to proliferate our AI tools across our entire customer base over about two contract cycles. And some are adopting more rapidly and embracing the AI tools. Some are adopting the AI tools in add-ons, but they might be, you know, shaving back their configuration somewhere else. That tends to be a false economy because they'll just come back and purchase more add-ons later. So to get the full effect, it probably takes a couple of contract cycles, but we're very, very pleased with the start we've made. Very helpful. Thank you, John. Thank you. We go next now to Josh Tilton at Wolfe Research. Hey, guys. Thanks for squeezing me in. Can you hear me? Clear. Great. My first question is just, how does the Q4 hardware pipeline look, compared to kind of some of the strength that you saw in the first three quarters of the year? And given that you mentioned that the macro is still challenging, is there any extra conservatism in the Q4 guide to account for the potential for maybe some hardware to slip into next year? Yeah, it's a great question. That pipeline is very strong. I mean, the hardware demand just continues to amaze me, that it's just tremendous. Those products are that verification group is just performing at a really, really high level and such in such a consistent fashion through probably eight quarters now. But, so very pleased with that. You might have noticed that we kept the same range on the guide from last Q3 from Q3, the same range, because we thought there's probably a broader kind of a array of potential outcomes with the amount of business that we expect to sign in Q4. We're expecting a strong bookings quarter in Q4, and there is a strong pipeline for hardware. But like I said, in relation to the AI question, that, you know, we're very patient with our customers. We'll go at their pace, and naturally, if something slips from Q4 to Q1, it goes from this year to next year, or, or vice versa. You can have stuff that customers are planning to buy in Q1, happen in Q4 as well. But, but I think we've accounted for that in the guide. Everything we know is in our guidance. Super helpful. Then, just a follow-up, obviously on AI, can't not touch it. But as that business of yours triples, are you seeing the drive or the want to adopt these AI tools, causing more of your users to make full flow decisions when maybe this has been more of a best-of-breed market, historically? Yes, absolutely. That's a very good point. Because the AI tools, you know, our AI tools will run on the, on the full flow by nature, whether that's digital implementation, or it is on, in verification. And of course, we believe we have best-in-breed tools anyway, on the base. You know, it's like, you have to have the full flow, the basic engines to be best in class, and then add AI on top of them, which is best in class. But it is, it is helping the underlying tools. So when our customers are doing more AI tools, it also, and also, as you know, we have commented in the past that the AI tools by nature use a lot of underlying tools. So when Cerebrus runs, for example, you know, which is our AI tool for digital implementation, which is one of the most difficult tasks in chip design. So it will typically, the customers will use them on like, you know, one run of Cerebrus will typically run on 10, 20 machines, okay? And each of them could be like 32 CPUs or 16 CPUs. So they are using a lot of compute, and also they're using a lot of underlying licenses. So it could be like, you know, 10 instances of Innovus, which Cerebrus is running. So and then it is also, you know, synthesis, place and route, and sign-off, like in case of digital, and then, you know, logic simulation, you know, formal verification, hardware in case of verification. And same thing with analog. It's not just Virtuoso, but it's Spectre. So, the—it's definitely a full flow is enabled, but also, typically it requires more instances. Because, you know, we're doing AI-based design or AI-based intelligent search of the design process, so it will require multiple runs. You know, typically, instead of one or two runs, it may require, you know, 100 or 200 runs. But the user were doing that manually, you know, in a sequential manner, and we can do that automatically in a more parallel manner. So it definitely helps, but it's still worth it because you get much better PPA, and it, it's like using more compute and more software, more automation, instead of more human effort, and we can do it faster and a better PPA. Yeah. Super helpful. Thank you. We'll go next now to Joe Vruwink at Baird. Great. Hi, everyone. Sorry to belabor the backlog questions, but, I suppose I'm going to. If we rewind two years ago and look at Q3 and the Q4 of 2021, current RPO then, went up by, I think, nearly $400 million sequentially. Is that maybe how you would start to frame just renewal values that are coming due and what you could potentially look to build on? And then second part of my backlog question, and it gets back to, to Jason's question on just the, the changing composition of hardware and software. Just given what Cadence has been able to do on production capacity and, and ramping there, does that change the relationship in terms of what needs to be sitting in backlog at year-end in order to support some sort of next 12-month revenue expectation? Hi, Joe. You know, great questions there. But, yeah, I guess the way you profiled last year's growth, a large portion of that growth would have been, of course, the hardware we weren't able to service at the time. And the reason I called out the lead times was, you know, end of last year, that backlog and current year, or the next 12-month backlog, if you like, contained about 26, 28 weeks of lead time for hardware. That's down to about eight to 10 weeks now. So, I guess, to answer the second part of your question there, that, you know, when you get to the end of this year, because we've ramped up on the hardware production, you'll need less to be in backlog. There'll be less need for revenue to come out of backlog for next year's revenue than there was for this year. But, and like I said, we've kept the production levels at the same level all year. So every quarter, we ratcheted it up in Q1, and we've maintained that production level to try and reduce those lead times because we think we're more competitive with customers. I mean, I was impressed this time last year, people were waiting, you know, over six months for our hardware solutions. You know, we'd be silly to assume that that would continue. It's important to get the lead times down to 8-10 weeks, and I think that's more normal, kind of, more normal level to get to. But yeah, very, very pleased with the progress we've made so far this year. And again, I mean, we're not really talking about next year, but we've got a very busy Q4 ahead of us. Great. Thanks, John. If I can squeeze one more in, I think we're about to lap the OpenEye acquisition. I just wanted to see how that generally has tracked relative to your original expectations, and maybe just get an update about how Cadence is thinking about the opportunity from the Molecular Sciences group and the role you can play in life sciences looking forward. Absolutely. You know, we are super excited about that. You know, we're super excited about molecular design and the future. It's almost like, you know, where EDA was maybe 20 years ago. You know, before I talk specifically about molecular design, I want to tell you in terms of our product strategy and how that is synergistic and similar to. So I see a lot of activity in our main products, which, you know, I would describe as like a three layers, you know, three layers. So the middle layer is actual, you know, software products that we have, which are like either you're doing, like, EDA design, or they're doing system simulation, or they're doing finite element, or computational fluid dynamics, or molecular simulation. So that's the middle layer of the cake. Below that is this new emergence of, you know, computational hardware, which is, you know, special-purpose hardware. Like we had in the past, we had special-purpose hardware with Palladium, which is our custom chip, but now we use FPGAs for Protium. We have, of course, x86-based, you know, Intel and AMD CPUs, and then recently, a lot of activity on GPUs, you know, especially with NVIDIA GPUs and accelerated computing. So that's the bottom layer of the cake. And then the top layer of that three-layer cake is AI orchestration. You know, AI can provide this new level of automation and productivity, and doing what was typically done by humans. It can be done with AI, like we talked about Cerebrus or Verisium. So this three-layer cake is central to our product strategy. So the middle is simulation, which is physics-based, biology-based. The top is AI orchestration, the bottom is computational hardware. And then this can be verticalized across multiple verticals, whether it's EDA and chip design, whether it's package design with, you know, Allegro X AI, whether it is Clarity and Optimality, whether it's CFD with Fidelity, and more importantly, like you asked, with biosimulation. So the reason we acquired OpenEye is that gives that critical middle layer of, you know, physics-based biological simulation, which are very few companies that can do that. But then we can add to it AI-based drug discovery and computational hardware with GPUs. So as you may know, the OpenEye has a Orion cloud-based platform. It already runs on GPUs, giving significant speed up for biosimulation. And then recently, and we'll talk more about in the future, we expanded our collaboration with one major, you know, top five pharmaceutical company to do traditional and AI-based drug discovery on top of OpenEye and Orion platform. And so I think this thing in the future, if you go forward, and I mentioned in the last time also, you know, the application of AI also, I think, is gonna go into three steps. So first step, application of AI is gonna be in building out the infrastructure. Like we talked about, of course, great companies like NVIDIA and Tesla and now Broadcom. So the build of infrastructure, and there's so many other hyperscaler companies, as you know, they are all building out AI infrastructure. So that's the first phase of AI adoption. The second phase of AI adoption is applying AI to our own products, you know, like Cerebrus and JedAI and Verisium. We talked about that today also, and that's going pretty well, and we talked about the progress in the last one year. And that, I think, will still take several years to go. And then the third phase of AI adoption is AI applied to areas that were not automated in the past, okay? So I think that in—you know, that may take longer, you know, maybe five years plus, but that has to be driven to digital biology and life sciences. I mean, there's a huge application of AI, and to do that properly, we need that three-layer cake, and we need AI on top. We need biosimulation, which OpenEye brings, and then computational hardware with our leading compute platforms. So I'm very opportunistic, you know, about the future. Now, it will take some time. You know, this does not happen in a quarter or two quarters, but it's right to invest for the future, and it is synergistic with the other parts. So, you know, a lot of the biosimulation is similar to what we do in circuit simulation or CFD and things like that. But overall, I would like to say still in the early innings with biology, you know, and biosimulation and OpenEye, but it's a good start, and we are investing in it for the future in a controlled way, of course. You know, we are always, you know, financially disciplined, but I think the potential is there in the future for it to emerge as one of the big areas. Yeah. That's great. Thanks very, very much, Anirudh. Thank you. And our final question comes from Andrew DeGasperi at Berenberg. Thanks for fitting me in. Just had two quick ones. I know most of them were answered so far on this call, but first, on the margin, maybe could you lay out, John, in terms of the guidance for the year, I know you put down slightly the top end of the range for the operating margin on non-GAAP basis. Just wondering maybe if you could lay out what the puts and takes are there. Is it revenue mix? Is it the recent acquisitions that you made that might have sort of crystallized that number? And without you know having you two answer the second time, but like in terms of investments that you're making for next year, is the pace of call it hiring gonna change at all based on what you're seeing right now? Great questions, Andrew. The, yeah, in relation to the, the margin, you know, the recent acquisitions are, are more dilutive to, to this year, so we're, we're picking up more expense. We're picking very, very little revenue. We're picking up expense immediately, and that kind of narrowed the range on the, on the margin outcomes for us. But, or at the midpoint of 41.75, I think it works out to be about $5 and $0.10 on non-GAAP EPS. In relation-- What was the second part of the question? Sorry, I've forgotten the second part of the question. No, no worries. It's just on the in terms of hiring, just in terms of how you're thinking about it- Yes ... so far. Yeah, I mean, it's great we continue to attract top talent to Cadence. You may notice, though, in our Form 10-Q, we did some restructuring. In August, we initiated a restructuring plan to better align our resources with our business strategy, and we incurred about $12 million in costs comprised of severance payments and termination benefits in relation to headcount reductions. But I would kind of categorize that as a bit of housekeeping in preparation for next year. Understood. Thank you. Thank you. I'll now turn it back over to Anirudh Devgan for closing remarks. Thank you all for joining us this afternoon. Our strong execution of the Intelligent System Design strategy and customer-first mindset continue to drive growth as we expand our portfolio with new innovative AI-driven solutions. We are proud of our inclusive culture and focus on enabling sustainable innovation and honored to recently be named to Newsweek's America's Greenest Companies 2024 list. On behalf of our board of directors, we thank our customers, partners, and investors for their continued trust and confidence in Cadence. Thank you. Thank you for participating in today's Cadence Q3 2023 Earnings Conference Call. This does conclude today's call. You may now disconnect.