Advanced Micro Devices Inc at Deutsche Bank Technology Conference Transcript

The following is excerpted from the question-and-answer section of the transcript.

Question: Ross Seymore - Deutsche Bank Securities Inc. - Analyst : So I think it was just, what, last week you guys announced an AI-related acquisition. So AI is obviously a topic we'll talk about in many different ways, but the ZT Systems acquisition. Talk a little bit about the logic of that deal and seems like there's some nuance of what you were really going after in that with the engineers. So just talk a little bit about that. Mark Papermaster - Advanced Micro Devices Inc - Chief Technology Officer, Executive Vice President - Technology and Engineering Absolutely. Well, first, Ross, thanks for having me here at your conference. Excited to be here, and an incredibly exciting time at AMD. When you think about the announcement that we made last week in acquiring ZT Systems, it's the next stage in really our strategic growth of ensuring that we have the full complement of skills that we need to have not only the best AI hardware, not only competitive and leadership AI software, but the ability to integrate it and optimize it at the system level. And so ZT Systems represents exactly that. They're 15 years of experience with building some of the most complex heterogeneous system designs, integrating CPUs, GPUs, networking, advanced thermal management and cooling capabilities, as well as the kind of control software that you need to efficiently run these complex rack designs. So a very, very strategic addition for us and not a typical acquisition, because the goal for AMD is indeed to leverage the 1,000-plus so skills that have that design expertise. And what we did, Ross, was stated right up front that we will -- for the manufacturing side, Frank, the CEO of ZT Systems, will continue to run that 1,500-person manufacturing side, but that we'll be looking for strategic partners over time, of course, once we close. So the strategic impact for AMD is really one of accelerating our time to market, and optimizing that time -- that solution which is so critical going forward to have the hardware, software, and the system design co-optimize together.

Question: Ross Seymore - Deutsche Bank Securities Inc. - Analyst : And talk a little bit about the rising importance of systems. How did that come to be, and how does AMD expect to differentiate in its approach? Mark Papermaster - Advanced Micro Devices Inc - Chief Technology Officer, Executive Vice President - Technology and Engineering When you look at AI applications, they're incredibly demanding of high-performance compute. And so they demand the absolute best of silicon capability. Well, in AMD, we're well armed there. We are the leaders in chiplet technology. We're the leaders in bringing together high performance CPUs, GPUs, accelerators. And we have a strong network portfolio based on our acquisitions with Xilinx and Pensando. We've been building our software skills. And so that's critically important to actually bring that computation to bear. But again, when I go back to the demands of the most complex AI models, the foundational models, which really require massive clusters of heterogeneous systems, the optimization doesn't stop at that hardware and software of the compute engines. You need to optimize through the networking, through the connectivity, through the rack. And anything can become a bottleneck. If you have issues from wiring capabilities, if you have issues from a cooling standpoint, if you didn't fully integrate the networking in the most optimum way, then you are not delivering the most optimized system. So we, of course, partner with our system providers today. It's a serial process. We're designing that compute complex, and then we work with our system providers and continue that optimization. So that part doesn't change. But with the ZT design capabilities coming in-house, from the earliest conception of our next-generation AI-based processing complexes, we will take into account the system aspects. We'll be actually optimizing for all those facets that I just described and that is a game changer -- earlier time to market of an optimized system all the way through the rack implementation.

Question: Ross Seymore - Deutsche Bank Securities Inc. - Analyst : Is this something that is more cloud attuned than kind of enterprise adopters of AI from your perspective? And I know cloud's the most aggressive adopter of it. Does it really matter the type of customer? Mark Papermaster - Advanced Micro Devices Inc - Chief Technology Officer, Executive Vice President - Technology and Engineering Well, you said it right. The cloud, which are driving the foundational model training and inference, are the most demanding of that system and rack level optimization. And so they're the first customers that will benefit from this marriage of technologies that we will achieve upon close with the addition of ZT systems. But what happens -- I will give you an analogy to server systems today. So often, the biggest server clusters are at the hyperscalers, but that learning and then optimization comes right down into the on-prem and enterprise installations, which are deployed across the Fortune 500. You'll see a very similar trend here. The utmost of scale up, meaning the largest of the GPU compute nodes of the scale out, meaning the building of the largest clusters will be hyperscale. But all of that technology honing can be applied to ensure that enterprise class implementations that may not be running those massive foundational models, they're going to benefit equally from scale back systems in tune with their workload demands.

Question: Ross Seymore - Deutsche Bank Securities Inc. - Analyst : So that is enough on, at least, unless you want to talk about it more on the ZT side of things. Let's talk about the Instinct side. The MI300, you guys have ramped that amazingly fast. The people debating what the number ends up being this year, but going from basically zero to somewhere around $5 billion over the course of a year or so is pretty impressive. Talk about what the biggest challenge is in the next-generations of product. I know the race never ends. But as you go to the next gen of that, the 325, et cetera, et cetera, where does AMD start to differentiate or continue to differentiate in that roadmap? Mark Papermaster - Advanced Micro Devices Inc - Chief Technology Officer, Executive Vice President - Technology and Engineering Well, let's start with the differentiation that we have right now. How did we get that differentiation? We listen to our customers. That's a hallmark of AMD. We are able to collaborate extremely well, listen to our customers. When they saw what we had done with the MI250, which powers the largest supercomputer in the world today with the Department of Energy Frontier System at Oak Ridge, and LUMI and other installations, we earned the trust and understood their requirement. And we're able to show our agility and pivot the next-generation design that we have for HPC for supercomputers, called MI300A over to MI300X, AI optimized for the most demanding inference and training applications. REFINITIV STREETEVENTS | www.refinitiv.com | Contact Us consent of Refinitiv. 'Refinitiv' and the Refinitiv logo are registered trademarks of Refinitiv and its affiliated companies. AUGUST 28, 2024 / 8:15PM, AMD.OQ - Advanced Micro Devices Inc at Deutsche Bank Technology Conference And in fact, for inferencing, we've been differentiated because we have up to 192 megabytes of HBM3 memory on that starting point. And so, in fact, by the way, I'll mention that we did publish MLPerf results. And you'll see today this came out and you'll see the competitive stance of MI300 on that standard benchmark. So where do we go in our roadmap going forward? What's our strategy? One, we've embraced an annual cadence. If you think about data centers, typically they've been on an 18- to 24-month type of cadence. But AI systems are on an annual cadence. And the reason is that the innovation on the models and the model size, the number of parameter of the models and what the capability of what those foundational AI models can do is dependent on the growth of the compute engines. To support that expanded parameter growth, it has to be more efficient or energy alone. Just the power would gate the advancement of AI and the industry. And so it is a necessity to have a much more rapid cadence and we embrace that. And so what you should expect from AMD is we're leveraging all of the know-how that we've had for years, supplying the industry leading edge, high-performance computing. Being the leader in chiplet, we are increasingly going to leverage that to hit that annual cycle. We have the MI325 enhancing to HBM3e, which we have come into production next quarter. We're on track with the MI350. And both the MI325 and the MI350 family will stay in that same socket that we have, that same baseboard, the UBB. So it's an easy adoption cycle for our customers. We're not demanding a new system infrastructure, but we're adding a doubling of memory capacity with 325. So that differentiation we have on inferencing, we expect to persist with the MI325. And then with the MI350, again, dropping right into that same system infrastructure with ease of adoption, we're going to have the next generation of our GPU compute engine. And that's going to have new math formats. That's going to support FP4 and FP6. It's going to yet leverage not only the same socket, but that same HBM3E memory. So it's a plan of how do you get customers a significant increase in capability every generation but work closely with them and make it easy for them to consume these new capabilities. And then beyond that, with the MI400 family, which will be for the year following 2026, really, really exciting advancements across the board. Again, great partnership with our customers, and even more focus on the networking capabilities and system optimization. Because by the time we come out with the MI400 family, assuming successful close of ZT System acquisitions, we'll have thumbprints all over that in terms of even further system optimization.

Question: Ross Seymore - Deutsche Bank Securities Inc. - Analyst : So today, I believe your solutions are -- largely have a leadership position on the imprint side, a little less so on the training side. Talk about what gives that advantage or disadvantage. And perhaps more importantly, looking forward, what side are you actually focusing more on between those two, if it -- it might not be an either or. Mark Papermaster - Advanced Micro Devices Inc - Chief Technology Officer, Executive Vice President - Technology and Engineering Well, it's certainly not an either or. We've targeted the Instinct family squarely at the most demanding applications of both inferencing and training in the AI space. We did lean in, of course, upfront on inferencing with MI300, and the reason is we were the new entrant to actually bring competition to this market. And it was important that we establish ourselves where we had a clear differentiation. Our chiplet capabilities and prowess, and the ability to have a leadership memory capacity as well as bandwidth was where we wanted to lead into market. And it's proven out to be very beneficial. It's providing immediate total cost of ownership advantages to our customers, and it's a commitment that we'll maintain throughout our roadmap. So as I said a moment ago, you'll see us very focused on, I'll say, staying on the torrid pace that our customers demand. But training, where we are certainly competitive from the outset with MI300, training, no doubt is a harder task because you need to take additional time, additional time to hone the networking capability, the scale out capability as you build clusters. You need to spend the time on the communications library, the software which is managing how the GPUs are working close knit across the build out of that cluster. And that's exactly what we've done. So we are working with initial implementations on training. We're tuning the training, so we're not waiting for the future roadmap of Instinct. We are starting now to bring training to bear, as well as inference, which of course, is the production instances that we have out there today.

Question: Ross Seymore - Deutsche Bank Securities Inc. - Analyst : So I actually lied. One more question on the hardware side. Do FPGAs play any role in this, on the data center infrastructure side? Mark Papermaster - Advanced Micro Devices Inc - Chief Technology Officer, Executive Vice President - Technology and Engineering They do. Our FPGAs, or adaptive compute as we call it, are actually one of the fastest ways to tailor and to customize based on a known workload that our customers have. So we already have and are working with major customers in terms of hyperscaler deployments which can allow tailoring in terms of workload flow, network management, and actually storage optimizations.

Question: Ross Seymore - Deutsche Bank Securities Inc. - Analyst : So on the -- sticking within the EPYC side of things, talk about the architectural choices that your customers want you to make as far as the core count side. So kind of Bergamo versus Genoa. How do you see the market moving? And from a business perspective, we're moving towards pricing per core count versus pricing per chip per se. I know they end up at the same place. But just talk about the reasons economically why that could be a good thing for AMD. Mark Papermaster - Advanced Micro Devices Inc - Chief Technology Officer, Executive Vice President - Technology and Engineering Well, there's been a very significant shift in the driver of how you configure your x86 server systems. VMware did shift their pricing schemes. And it turned out that having a more performance CPU and the efficiency, energy efficiency that you get with more performance CPU, and now the licensing costs that you get, lower licensing cost if you have a more performance CPU are, in fact, really driving a major driver of our Genoa sales for those that are leveraging that type of virtualization capability. So it, moreover, underscores how demand is driven by workloads. Just like data centers today are heterogeneous across CPU and GPU, when you look at CPU alone, it's not one type of server that makes sense for most customers. Again, for those virtualized environments, you want -- Genoa's perfect with that high performance 96-core CPU that gives you that TCO advantage. But you mentioned Bergamo. It's really our native cloud optimized workload. So where you have cloud native and don't need necessarily the highest performance of CPU, but you want the most efficient. And so we go from 96 to 128 cores, very, very efficient. And so throughput systems, things like recommendation engines, those are workloads that really excel. Beyond that, we've further diversified. We have stacked V-Cache for where you might have high performance or database workloads, where we really increase the cache size of the CPU and we have telco optimized. So again, the diversification of our EPYC CPU product line is really a result of listening to our customers and making sure that we have the diversification to match where their workloads are.

Question: Ross Seymore - Deutsche Bank Securities Inc. - Analyst : So just to front run the AIPC topic and get the competition side out of the equation in both ways, is there something inherent in the ARM architecture, you believe, versus the x86 architecture that is an advantage, whether it's on power consumption, performance, whatnot, that changes the game, versus an x86 to x86 competitive environment that we've seen more predominantly over the last, say, 20 years? Mark Papermaster - Advanced Micro Devices Inc - Chief Technology Officer, Executive Vice President - Technology and Engineering We don't see that the instruction set architecture is a differentiator at the end of the day. I mean, we love x86 because there's a massive install base. It's a CPU architecture that we've been able to hone microarchitectural implementations over decades to every bit of performance out of it. And the software tool chain that is out there and the familiarity of applications development make it a superb play. Yet, we offer ARM across our portfolio. It's in our adaptive embedded compute. It's in various controllers we have. That -- end of the day is we're about providing the best solutions for our customers. You look at Zen 5 that we're rolling out now. We just brought it out in our PC market with a strict point. What do we do with Zen 5? We widened the execution pipeline. We added AVX-512, full physical implementation. And you might think, well, that's for more like server, and that's for those vector calculations and floating point calculations. But what we have is the capability to also excel with AI because the core of the AI is, in fact, multiply accumulate, which we performed very, very well and we added FP16 in Zen 5. So we'll continue to evolve the x86 architecture to excel at the workloads needed across PC, embedded in our data center customers. And we also were an ARM ecosystem -- not the ARM ISA -- there are differences there, but more it's the ARM ecosystem. Where does it play and where that's an advantage. Like our embedded road map will persist and continue to partner closely with ARM in those markets. In the PC, we'll see. Now it's a dual ISA play. So we're going to leverage x86 where that's best. But again, we are not married to ISO. We're married to the best experience we can provide our customers.

Question: Ross Seymore - Deutsche Bank Securities Inc. - Analyst : Do you think there's any, from a CTO perspective, any kind of cost trade-offs that you have to hit? You just said you're going to add -- on top of everything you're going to add all this functionality. Is the price of the end device just going to go up and it's going to be a higher end -- establish a new higher end PC or when you're thinking about the roadmap, does cost come into the equation as well? Mark Papermaster - Advanced Micro Devices Inc - Chief Technology Officer, Executive Vice President - Technology and Engineering Well, the outset, it will be a higher price tier for the highest capability of AIPC. So where our Strix Point with 50 TOPS capability is positioned in the higher tier from an ASP strata. But it won't take long before the AI enablement is really end-to-end across the PC portfolio, across the industry.