Advanced Micro Devices, Inc. (NASDAQ:AMD) J.P. Morgan 52nd Annual Global Technology, Media and Communications Conference Call May 21, 2024 3:45 PM ET
Company Participants
Jean Hu – Executive Vice President & Chief Financial Officer
Conference Call Participants
Harlan Sur – JPMorgan
Harlan Sur
Okay. Good afternoon, and welcome to — again, welcome to the second day of JPMorgan’s 52nd Annual Technology, Media and Communications Conference. My name is Harlan Sur. I’m the semiconductor and semiconductor capital equipment analyst for the firm.
Very pleased to have Jean Hu, Executive Vice President and Chief Financial Officer at Advanced Micro Devices here with us today. Jean, thank you for joining us this afternoon.
Jean Hu
Yeah, thank you. Thank you for having us.
Question-and-Answer Session
Q – Harlan Sur
Yeah. I think, one of the best places to start is, obviously, one of your customers, Microsoft, is having their Build event. And there were a couple of, I think, key announcements, product launches, using the MI300 GPU platform from AMD. I don’t know if you wanted to maybe spend some time maybe talking about that.
Jean Hu
Yeah. It’s really exciting. So, we announced today with the Microsoft’s Build conference, end-to-end partnership with Microsoft from, of course, AI PC to MI300. On the MI300 side, MI300X and ROCm software together actually power the Microsoft’s virtual machine both for the internal workload, the ChatGPT, what open source to use, and also external workload, third-party workload.
And Microsoft, actually said, right, from, MI300X and ROCm, it’s the best price performance to power the ChatGPT for inference. So that’s really a proof point for not only MI300X from hardware, how competitive we are, but also from ROCm software, the maturity, how we have worked with our customers to come up with the best price performance. It’s very exciting.
And on the third-party workload side, the Hugging Face, is also using Microsoft’s virtual machine powered by AMD’s MI300X. And Hugging Face has almost 0.5 million models, which you can all run on MI300X.
So, we have made tremendous progress not only from MI300X competitive in inference/training, but more importantly, software has been really critical investment we’re making. And today, we really can run a lot of models if they’re writing the models based on the open source ecosystem framework. We can run them out of boxes. And then, we also help the customers optimize their models to make it most efficient, provide the best TCO to our customers. So, it’s very exciting.
Harlan Sur
So, the Microsoft announcement, like you said, was in two portions, right? So, first is Azure. It’s just offering MI300X instances, right, to their public cloud customers…
Jean Hu
Yes, that’s third-party, yeah.
Harlan Sur
Exactly. And then, the partnership with OpenAI, right, they announced the Azure OpenAI Service, right, that allows customers to take advantage of prebuilt models, right, to quickly bring training and inference and bring their models to the market that also is using your MI300X platform, right?
Jean Hu
Yeah. Because the MI300 is powering the ChatGPT 3.5 and 4, all the Copilot, all the different version, the Team, Copilot, of those applications, it’s really one of the most important AI infrastructure in Microsoft Azure data center. So, we are really pleased with our partnership with Microsoft.
Harlan Sur
No, congratulations on that. We’ll talk a little bit more about MI300, but I did want to start off with — and thank you again for joining us today. I did want to start off with some of the near-term sort of business environment questions. Server shipment TAM forecast for calendar ’24 is sort of low mid-single digits sort of growth this year. You expect to grow your data center business this year by strong double-digits percentage points. Within that, it looks like your server business ex GPUs is growing kind of 25% to 30%, and implies 15% or better second-half versus first-half growth, right? You did talk about continued adoption of Genoa and improvement in enterprise demand dynamics. Like, what demand dynamics are you tracking, customer programs, adoption of Genoa, Bergamo, ramp of Turin that gives the team confidence on a better second half and strong growth in your server business this year?
Jean Hu
Yeah. Great question. We are very pleased with our data center performance. If you look at the market opportunities, it’s the largest fast-growing opportunity. And we have been investing in data center, and the momentum you can see both from GPU side and the CPU side. So, when you look at our CPU business, we — in Q1, we saw double digit — a strong double-digit growth year-over-year. And in Q2, we’re going to see another strong double-digit year-over-year growth. All of those are have been driven by the ramp of Gen 4 family of processors, which including Genoa, Bergamo and others, the significant adoption in both cloud and enterprise customers.
I think fundamentally because our processors provide the best TCO for our customers. And, if you look at the market share in Q1, the third-party market share shows we are reaching 33% market share from the server CPU side. I think, we do expect the second half to be better than first half. The first one is in cloud. Cloud market demand continue to be a little bit mixed, but, since we are providing best TCO for our customers, we do see both hyperscale cloud customers and Tier 2 cloud customers continue to adopt our Gen 4 processors across the different workload, both external workload and internal workload. And we talk about we have almost, like, 900 public instance available globally for customer adoption. I think that’s really have been helping us to drive the growth.
Secondly, in enterprise, we actually start to see some demand improvement, because today, all the CIOs in enterprise, they are actually facing couple of challenges, right? The first is all their workload continue to be small. The data is small, application is small, so they do need to have a more general compute. At the same time, they need to start think about how they can accommodate AI adoption in enterprise. They are facing the challenges of running out of power and the space. If you look at our Gen 4 family of processors, we literally can provide the same compute with 45% less servers. What that means is if they adopt AMD’s solution versus our competitors, they actually can save CapEx almost by half upfront. And then, in addition, the operational cost that will be 40% less.
So, when you look at the TCO benefit we can offer, plus we have been investing go-to-market, we have been — have more feet on the street to talk to enterprise customers and show them the TCO benefit they have. So, we do see the acceleration of our effort is paying off. We talk about American Express, Shell, STMicro, some of the larger enterprise customers shifting to AMD solutions. So that’s just the beginning.
We do think in second half, with the demand improvement and our continued share gain in enterprise market, will also help us. Of course, as you know, we are very excited about the Turin launch, which is our Gen 5 server processors. It will extend the TCO benefit compared to Gen 4. So, we’re very excited about it. Of course, the revenue ramp probably is more in 2025, but the momentum, when we look at our competitive positioning, how we can provide the best TCO for customers, we feel pretty good about the second half.
Harlan Sur
Similar question that I asked on data center, but now focus on the client PC, right? You drove better than seasonal shipments in Q1. Guided for slightly better seasonal shipments dynamics in Q2. Full year, I think, we, in consensus, have your client business up about 25%. What metrics are you monitoring that gives the team confidence that PC client business will drive strong growth relative to the overall TAM growth?
Jean Hu
Yeah, appreciate your comment. It’s true that when you look at the first half, our PC client business are performing really well. We’re gaining share. And primarily, they are driven by our most recent generation of processors, Ryzen 8000. When I look at our Q1 performance, on the desktop side, we have strong year-over-year double-digit growth. On the mobile side, we actually almost doubled the revenue from the Ryzen 8000 processors. So, the way to think about it is we actually were the first to introduce NPU inside of a PC; the AI PC people talk about is with the Ryzen 7040. And we’re also the first to introduce NPU inside the desktop; that’s the 8000 series. So, the technology and product leadership that have helped us drive the significant demand.
I think, AMD has always been using the strategy is — to drive the top-line revenue growth through product technology leadership, and the team has been executing extremely well. And in the second half, I think we’re going to launch our next-generation AI PC Strix. You’re going to hear about it in the coming weeks. It’s a very exciting product and very competitive to power the AI applications in the PC market. We do believe AI PC is a very significant inflection point. It will potentially help the refresh the PC market. And so, overall, to come to your question is, we think generation over generation technology and product leadership will help us both on the commercial side and the consumer side to continue to gain share.
Harlan Sur
Perfect. We did talk a little bit about the traction and announcements today at Microsoft Build relative to the MI300, but let’s talk a little bit more about AI and accelerated compute, right? Your team is executing extremely well, fastest product ramp in the history of the company, $1 billion in cumulative revenues just over the past two quarters. You’ve taken your MI300 calendar ’24 revenue targets from greater than $2 billion to greater than $3.5 billion to greater than $4 billion. Near term, the team has said that there’s supply constraint, right? Seems like demand is rising much faster than expectations. But Lisa said that off of the $4 billion revenue target for this year, that the team has supply commitments to drive revenues significantly above that amount, right? Is that still the case? And is GPU revenue upside from here just purely dependent on customer conversions from eval to qual to deployment?
Jean Hu
Yeah. First is, the MI300 ramp is really unprecedented. If you think about it, we launched MI300 December 6 last year. And since then, as you mentioned, in less than two quarters, we actually passed $1 billion revenue, and we also guided Q2 significant increase and each quarter sequentially for the rest of the year. And we updated the — like, $4 billion — more than $4 billion revenue for this year based on what we have qualified and backlog, the orders at the point when we did our earnings announcement. So, we have more than a 100 customer engagement ongoing right now. Lisa talked about the different customers at a different stage of engagement from a POC to qualification, lab production to ramp. So, all those customers — the customer list include, of course, Microsoft, Meta, Oracle, those hyperscale customers, but we also have a broad set of enterprise customers we are working with.
Overall, if you look at the AI accelerated demand, it continue to exceed everybody’s expectations. I think there are more demand for GPUs, and our team is working very hard with our customers to continue to go through those kind of full process to scale our customer, to make sure they ramp into the production. So, we do have more than $4 billion supplies secured, especially in second half. We are absolutely working hard to continue to drive the customers, help customer to ramp into production.
Harlan Sur
Your data center GPU competitor has laid out a multi-year roadmap, increased cadence of new products, and also more finely segmented out their product line, right? I think, we and investors, are wondering, when the AMD team is going to provide us more visibility on their roadmaps. And I think Lisa said that we should see new products being introduced towards the latter part of this year. Is that still on track?
Jean Hu
Yeah. I think, Harlan, I will highlight first how AMD got where we are today. If you think about the AMD, since Lisa and Mark Papermaster joined the company, has been trying to build a high-performance compute company. So, not only we have been investing in CPU, and on GPU side, we have been investing in GPU for many, many years since the ATI days. And if you look at our GPU roadmap, we have been investing in GPU from MI100, 250, 200 to today.
So, the approach has always been multi-generational, multi-year roadmap from AMD’s perspective. And the MI300X ramp, the success software side and hardware side is really reflection of long-term investment that we have been making. So, I think, from our perspective, that background — back drop is really important. And when we work with our customers, both companies are investing significant resources. So, you should expect the customer relationship is about multi-generation. And we actually get very significant feedback from our customers about not only MI300X, the next generation, and the generation after next.
The other thing I would say is, AMD has been doing the chiplet architecture for a long time, literally almost 10 years. The success of our server CPU roadmap, it’s because generation over generation, it’s about a chiplet design. That really gave us a lot of flexibility to expand our roadmap and accelerate our roadmap. That also helped us. We tend to be more conservative from announcing roadmap perspective, but you should expect us to have a very competitive roadmap. I think, stay tuned, and we will have a preview of our roadmap in the coming weeks.
Harlan Sur
Okay. Perfect. I feel like the part of the expansion in your data center GPU business outlook this year has been two dynamics; first, unlocking better supply availability, but secondly, faster time to production conversion by your customers as they migrate their software stacks over to your platform, right, thanks to several new iterations of your ROCm software framework. What is the AMD team doing here to continue to sort of close the gap on software, AI frameworks, and just accelerated compute ecosystem development?
Jean Hu
Yeah. Great question. Software is so important in this market. The ROCm software AMD has been investing, initially, it’s in HPC market. So, when you look at MI100, 250, and the MI300A, it’s ROCm software. Between the MI300A and the ROCm, we are powering the most advanced frontier model in the hyper HPC market. So, last two years, we have made a significant investment and the progress in the ROCm to support AI. That has been tremendous, and the ROCm 6.1 actually extended our support for broad library models, tools, and also ecosystem. That has been the reason a lot of models, if you’re writing based on open source framework, you actually can run your model out of a box using MI300. And that’s also why with Microsoft, we can work together closely to really co-optimize the performance to the point to be the best price performance MI300 machine.
So, the importance of us to move forward is to continue to scale because we have more than 100 customers. We have a broad set of different workload. We need to scale our model with open source ecosystem. That have been evolving very quickly. And, also, secondly is we do have the approach at AMD’s end-to-end AI. So, the ROCm as a single software platform will support the AI PC, the GPUs, and eventually, the edge side of AI applications and the server CPUs and also multi-generation GPU roadmap. So from that perspective, broadening the support and deepening the support are what we’re doing. And as you can see, we not only invest organically, we also did some small acquisitions to really expand our software capabilities.
Harlan Sur
Great. Why don’t we see if there are any questions in the audience? If you have any questions, raise your hand. We have one right up here. While we’re — it’s going to take some time. So, before he asks a question, let me ask my next question is, when we talk about AI, compute, silicon and hardware, it’s typically focused on cloud and hyperscalers, right? But interestingly enough, right, a majority of customer specific and proprietary data actually resides on prem. Your enterprise customers would like to keep the proprietary data on prem, run their AI workloads on prem. The team is actually starting to prime the enterprise markets with MI300. You announced the plethora of OEM server partnerships recently. What’s the strategy for targeting the enterprise markets? And how is this sort of modulating your sort of future product portfolio?
Jean Hu
Yeah. We actually — if you look at over 100 customers we have engagement right now, there are a lot of enterprise customers. The approach we’re taking is not only we want to make our hyperscale cloud customers successful, we also want to seed our enterprise customers, because we do think AI is going to be everywhere. And you’re absolutely right, when we talk to our enterprise customers, they do start to think about that question. Do I do it on premise? Do I send it to cloud? So that is a strategic approach they have to think through, and typically, they will come to us basically saying, how should they deploy AI? I think, we are uniquely positioned is because on the server side, we’re working with our customers. We’re helping them with how they deploy servers. So, it become like a significant leverage for us and frankly, on the commercial PC side, right? And so, AI PC, the server side and the GPU side, that’s a part of our go-to-market model right now. It’s — we actually can leverage that to work with the enterprise customer across our different platforms.
And, of course, ROCm software is really important because ROCm is open source by nature. And the customers, if they can write their model based on the open source framework, it actually saves them more money. Yes. And, from a TCO perspective, that’s what we’re really trying to approach, it’s consistently try to provide our customers best TCO. We do think that’s something we can continue to drive the engagement with enterprise customers.
Harlan Sur
Perfect. Okay. We have a question here.
Unidentified Analyst
Yeah. Hey, Jean. NVIDIA has — they have the China version of their, like H200 — I mean, the H20 and then the L420 — L4, et cetera. Does — in your $4.5 billion guidance — oh, sorry. Number one, do you have kind of like a similar China specific SKU? And number two is, if you do, is it included in your guidance? Like, how do we think about your — that China opportunity that NVIDIA has and whether you have this — a product for that — whether that’s in your guidance or not? Thank you.
Jean Hu
Yeah. So, when you look at our current revenue, the China exposure is almost nothing. It’s very limited. I think the way to think about it is China is important market. It is a large market, but we definitely want to make sure we’re compliant with the export control. I think, the export control has been changing a lot, and — but, for us, the one of the advantage we do have is because we do have a chiplet architecture, and, if we needed to design a model or design something for unique to meet the export control, the China standard, we absolutely can do that. The way I always say is, you should expect us to focus on all the market opportunities. We’ll prioritize it. Right now, today, we’re really focused on make sure our U.S. customers and those enterprise customers get to the GPU supplies we have, but we absolutely think China is important market for us.
Unidentified Analyst
But that’s not in the guidance (indiscernible)?
Jean Hu
I don’t think we’ll give that comment, right? Our guidance was based on, at that very particular point of Q1 earnings call, how we look at comfortably the backlog and everything. And at that point, it’s really focused on largely U.S. customers.
Harlan Sur
Your competitor surprised all of us last earnings when they told us that 40% of their profile is inferencing, right? And it’s high-performance, I mean, full-blown GPU inferencing, right? It’s not any of their sort of lowered-SKUs. It’s full-blown GPU inferencing. And from that perspective, I mean, as the team rolled out the MI300 platform, that was always how the team led, right, which is, we have the best TCO, performance, cost, power perspective from an inferencing perspective. And I think that the Microsoft Build announcement, right, with the Azure Open AI Service is using your MI300 primarily for the inferencing engine, right? And so, if you think about your design win — so it’s clear that inferencing is becoming a bigger and bigger part of the pie because your customers now are starting to deploy, right? And so, is it fair to assume that most of your engagements on MI300 is for inferencing-type applications?
Jean Hu
I would say we actually engage with our customers on both inferencing and the training. If you look at our Q1 revenue, we have actually quite broad customers, including inference and the training. I think it’s probably more indexed to the inference, just because when we come into the market, we’re late to market. When we enter the market, inference is actually taking off, right?
Harlan Sur
Yes, that’s right.
Jean Hu
Initially, it’s trending and then inference taking off. We’re coming to the market with a lot of inference opportunities. And secondly, you’re absolutely right, MI300X, today has the best inference performance. The TCO benefit for the customers, that absolutely is also one of the drivers. But, to us, when we think ahead, both training and inference are important to us. We do have the roadmap to address both opportunities.
Harlan Sur
On the server side, over the past year, we’ve seen at least five or six ARM-based server CPUs being introduced: NVIDIA Grace CPU, next-gen Graviton, Cobalt, Axion from Google, and a couple of others, right? How is this push on custom and merchant ARM-based CPUs going to impact the server CPU opportunity, you think, for the AMD team?
Jean Hu
Yeah. I think we work with our customer closely. I would say when customer think about things, it’s not about the architecture of ARM or x86. For them, it’s really about performance per watt and the performance per dollar, where you can get the best performance and the TCO. So, when you look at our today’s server processor roadmap, the Gen 4 and the Gen 5, which is coming up, is, with the Gen 4, we actually have all different skills, right? Genoa that can run very complex workload. And the Bergamo, which is tailored to cloud-native workload. And if you look at the customer adoption of Bergamo, which is probably more competitive with ARM, we see significant adoptions. Meta, we talk about it. It’s across Instagram, WhatsApp, and also Facebook, it’s all Bergamo, right?
Harlan Sur
Yeah, that’s right.
Jean Hu
Because it actually provide the best TCO. I do think, fundamentally, that’s what’s most important, is, the performance. So, I think the merchant versus ASIC, it’s always — in semiconductor industry, there’s always that phenomena. You always have a certain portion of the silicon will be like ASIC or customer solution. I think, it’s — again, it’s about the TCO, if a customer think there’s a TCO benefit to do a ASIC. But so far, we feel like really, our line of product portfolio and the technology leadership will continue to be able to provide a very significant benefit for our customers.
Harlan Sur
Going back to the PC space, competitors — some of your competitors are showcasing new ARM-based CPU platforms. They’re tallying their strong power efficiency. The SoC-like architecture, right, which makes it a lot more flexible. I would argue you’re getting the same benefits with your Ryzen x86 platform. But the AMD team does have the ARM architecture expertise, right? It’s a part of core Xilinx. It’s part of the Pensando portfolio. You have the GPU. You have the MPU. You have the AI blocks and other accelerator IP. If the OS vendors, if the PC ecosystem really wants to expand the CPU architecture base to ARM aggressively, would AMD participate?
Jean Hu
Yeah. I think I would not comment on very specific things, but you’re absolutely right. AMD, the way to think about is, it’s high-performance compute. The building blocks you mentioned, those are exactly the advantage of this platform. We’re actually the only company who can cover all those areas from just every building block you just said. We also — from a business model perspective, we also have two business model. If you look at our gaming console business, it’s a semi-customer business for generations and the future generation to come. So, business model wise and IP wise, we can do both, right? So, we definitely have the capability and the IP blocks to work with our customers. It’s really what the customers need.
Harlan Sur
On the embedded markets, very diverse end markets, industrial, auto, infrastructure, test and measurement, given your strong market share position here, Xilinx is in a good position to catalyze EPYC CPU attached or Ryzen CPU attached to the FPGA. But from a near- to mid-term perspective, I mean, the team did start seeing the weakness in embedded second half of last year, much like a lot of your peers. You seemed pretty confident on a return to quarter-on-quarter growth in embedded in the second half of this year. Given your lead times, you are probably booking into the second half of the year. But is that what’s driving the confidence? Is that you’re already starting to see the bookings inflection in the quarter?
Jean Hu
Yeah. I think, as you know, Harlan, Xilinx, it’s the best franchise in the FPGA business. We have seen the market share and the continued design win share gain from Xilinx business, especially combined with AMD, not only on the FPGA side, on the embedded processor side, we’re gaining tremendous design win share. Of course, those businesses tend to take time to ramp.
Coming back to the near term, I think everybody here knows these industrial, automotive, communication are going through a deeper inventory correction cycle. For our business, we can see quite a mixed demand, right? Aerospace defense is still to be okay. Communication, not only it’s inventory correction, but also you are facing — the CapEx spending are quite limit. So, those are the two extremes. And then, in the middle, you have industrial and automotive, it’s quite mixed. We do feel first half will be the bottom. I think the inventory correction has to be quite steep. But the second half, our view is the recovery is quite gradual.
Harlan Sur
Got it.
Jean Hu
So, it’s not a V-shape recovery. It will be slightly going up. Q4 probably is better than Q3. Overall, if we look at the design wins we get, we feel quite confident about the longer term. The embedded business will continue to be a significant share gainer and continue to drive growth.
Harlan Sur
Embedded x86 CPU, that’s about $6 billion to $8 billion per year market opportunity. AMD has very small CPU share here. So given you’ve got Xilinx in the portfolio, can you give us an update on the synergy unlock? I mean, what is the AMD team doing to aggressively drive higher AMD compute attached to all of those Xilinx sockets?
Jean Hu
Yeah. That’s one of the best revenue synergies that we have between AMD and Xilinx. I think, you’re absolutely right. Embedded processor business, traditionally, it’s just not a priority for AMD because the server market, the PC, the GPU. But, because of Xilinx acquisition, we have the natural leverage on the go-to-market side and the customer side. We actually have been seeing significant design wins in that market from both security market, networking market, communication market, and we do feel like, we can continue to get a design win momentum. The revenue will probably show up in 2025 and beyond, but that’s one of the very significant revenue synergies we see from the combination of two companies.
Harlan Sur
And then finally, you guided gross margins 53% for this quarter. As you move into the second half of the year, you have several dynamics, right, which I think should contribute to a better gross margin profile. Embedded is going to start to gradually recovery. Data center will drive strong growth. Looks like we, in consensus, are modeling the team exiting this year about a 150 basis points higher in gross margins from the June levels. Is that how we should think about the trajectory from here? Any other puts and takes to think about?
Jean Hu
I would say the major driver in the second half is actually data center business, right? Because data center is growing so much faster than other business. That will be the major driver for the sequential margin expansion each quarter for the second half. Of course, if embedded business come back, there will be additional tailwind. But right now, the way we think about embedded business, will be more gradual recovery, and the major driver of gross margin expansion in second half is to continue the data center strong growth.
Harlan Sur
Jean, thanks for the participation today. Always appreciate the insights. Thank you.
Jean Hu
Yeah, thank you so much.
Harlan Sur
Thank you, Jean.
Jean Hu
Yeah. Thank you.
