Good afternoon and thank you for joining the SMART Global Holdings Second Quarter Fiscal 2024 Earnings Call. My name is Kate and I will be the moderator for today's call. At this time, all lines are in a listen-only mode and will be until the question-and-answer portion of the call. I would now like to turn the call over to Suzanne Schmidt, Investor Relations for SMART Global. Suzanne, you may proceed.

Thank you, operator. Good afternoon and thank you for joining us on today's earnings conference call and webcast to discuss SGH's Second Quarter Fiscal 2024 Results. On the call today are Mark Adams, Chief Executive Officer; Jack Pacheco, Chief Operating Officer; and Ken Rizvi, Chief Financial Officer. You can find the accompanying slide presentation and press release for this call on the Investor Relations section of our website. We encourage you to go to the site throughout the quarter for the most current information on the company. I would also like to remind everyone to read the note on the use of forward-looking statements that is included in the press release and the earnings call presentation. Please note that during this conference call, the company will make projections and forward-looking statements, including, but not limited to, statements about the company's growth trajectory and financial outlook. Forward-looking statements are based on current beliefs and assumptions and are not guarantees of future performance and are subject to risks and uncertainties, including, without limitation, the risks and uncertainties reflected in the press release and the earnings call presentation filed today as well as in the company's most recent annual and quarterly reports. The forward-looking statements are representative only as of the date they are made and except as required by applicable law, we assume no responsibility to publicly update or revise any forward-looking statements. We will also discuss both GAAP and non-GAAP financial measures. Non-GAAP measures should not be considered in isolation from, as a substitute for or superior to our GAAP results. We encourage you to consider all measures when analyzing our performance. A reconciliation of the GAAP to non-GAAP measures is included in today's press release and accompanying slide presentation. And with that, let me turn the call over to Mark Adams. Mark?

Thank you, Suzanne, and thanks to all of you for joining us today for our Fiscal 2024 Second Quarter Earnings Call. We delivered solid financial results in the second quarter and continued to make great strides in our transformation into a provider of high-performance, high-availability solutions that enterprise customers need to deploy AI on-premise, at the edge and in the cloud. As one of the few players in the industry with decades-long experience in high-performance compute and specialty memory, SGH is uniquely positioned to help companies manage the complexity of AI implementation at scale. As a total solution provider, we offer our customers and partners innovative technology-agnostic hardware configurations, software that manages AI systems for maximum output and availability, and a professional services suite that enables our customers to achieve best-in-class performance and reliability. Let me summarize our operational results for the quarter. Revenues totaled $285 million in line with the midpoint of our guidance range. Although non-GAAP gross margin was at the lower end of our guidance due to a higher portion of hardware mix, we achieved non-GAAP earnings per share of $0.27, which was above the midpoint of our guidance through better operating expense controls. We exited Q2 with a strong balance sheet. Cash and short-term investments totaled $466 million. Now let me start our business line review with the Intelligent Platform Solutions group or IPS. Our IPS team offers a robust solution set of industry-leading hardware, advanced cluster management software, and best-in-class professional services. This solution portfolio enables our design, build, deploy and manage solutions framework for HPC and AI applications on-premise, at the edge and in the cloud. In Q2, IPS revenue came in at $141 million, up 19% from our prior quarter, representing 50% of total SGH revenue, thus making IPS the largest component of…

Thanks, Mark. I will focus my remarks on our non-GAAP results, which are reconciled to GAAP in our earnings release tables and in the investor materials on our website. Now let me turn to our second quarter results. Total SGH revenues were $285 million at the midpoint of our guidance and non-GAAP gross margin came in at 31.5% at the low end of our guidance, primarily driven by a higher mix of hardware revenues. Non-GAAP diluted earnings per share was $0.27 for the second quarter, which was above the midpoint of our guidance and helped by better operating expense controls. In the second quarter, our overall services revenue totaled $49 million, down from the $55 million in the year-ago quarter. Product revenues were $235 million. Second quarter revenue by business unit was as follows. IPS at $141 million, Memory at $83 million and LED at $60 million. This translates into a sales mix of 50% IPS, 29% Memory and 21% LED. Non-GAAP gross margin for SGH in Q2 was 31.5%, down from 32.1% in the year-ago quarter, driven primarily by lower memory volumes that were partially offset by improved mix in IPS. Gross margin was down sequentially from 33.3% in the prior quarter, primarily due to a higher mix of hardware revenue. Non-GAAP operating expenses for the second quarter were $63.2 million, down from $64.6 million in the first quarter, primarily due to lower variable expenses and cost reduction actions. Operating expenses were also down from $68.7 million in the year-ago quarter. Non-GAAP diluted earnings per share for the second quarter of 2024 was $0.27 per share compared to $0.24 per share last quarter and $0.87 per share in the year-ago quarter. An adjusted EBITDA for the second quarter of 2024 was $33 million, or 12% of sales, compared to…

Thanks, Ken. As we are still in the early innings of fully operational AI infrastructure being deployed at scale for most enterprise customers, we are seeing an accelerating need by the market for a trusted adviser to help with the challenges of deploying this new AI infrastructure. Our 25 years plus of HPC and memory expertise and deployment know-how position us to become a leader in this market by working to solve our customers' most challenging AI infrastructure needs. As our transformation continues, I want to thank our global team members for their efforts this quarter. We feel we are well-positioned for the exciting market opportunities ahead. Operator, we are now ready for Q&A.

Absolutely. We will now begin the question-and-answer session. [Operator Instructions] The first question comes from the line of Quinn Bolton with Needham & Company. Quinn, your line is now open.

Hey, guys, congratulations on the nice results and outlook. I guess I want to start on the IPS business and Mark maybe just get your thoughts kind of demand across the customer base between large CSPs, Tier 2 CSPs and enterprises where you may be seeing some of the greatest demand for new deployments as you look out into the second half of calendar '24 and then I've got a couple of follow-ups.

No problem. Thanks, Quinn, for the question by the way. Yeah, so when we think about how our view of the market is, it's based on obviously our kind of executive engagements with the three segments you talked about. Obviously, the early investors in the market were the large hyperscalers of which, obviously one's a big customer of ours. And then you have the two other segments you mentioned, large enterprises that are -- kind of have an infrastructure requirement in place for AI to enable their future success. And then you have these Tier 2, what we call Tier 2 CSPs, which are companies that have the infrastructure themselves to offer services that would lead for AI implementations at a number of different types of verticals, so to speak. So those three segments are how we look at the market. And I would say that the early investors, as I mentioned, were hyperscalers. However, what we've seen a major uptick in is twofold. Large enterprises are evaluating their AI strategy, and then in that strategy really is, do they do it on-prem in their environment, do they do it in a co-location model where they use an outsourced data center provider for the space and power, and do they have someone like Penguin come in and help them deploy? Or do they actually partner with someone in some type of JV structure or co-investment structure for a future build? And we're seeing all of those different models, but the level of demand signals from those type of customers on the enterprise side is very high. And then in addition to that, the hyperscalers are largely building to their own requirements. The Tier 2 CSPs are largely investing in infrastructure for enterprises who don't have access to their own infrastructure,…

Excellent. Second question I had you mentioned sort of AI at the edge and seemed to kind of highlight your Stratus offering. I'm wondering, are there opportunities for AI at the edge also in the traditional sort of Penguin business, where you may be setting up larger clusters to run LLMs or other AI infrastructure? So it's not necessarily just a high-reliability deployment, but you may also just say, hey, we've got to get the inferencing as close to the end user as possible. And you could see some pretty large deployments for inferencing equipment, rather than say just training, which I think some of your traditional deployments may have been more focused on.

I think that's right. So you really -- you kind of -- your question really embedded the answer, which is we are now developing solutions and investing in development for future integration into our solution roadmap for providing just that. As you mentioned, if you look at kind of the prior spend in AI, it was more training versus inferencing. And training is never going to go away because when you think about large language models, there's going to be a bunch of large language models that people use to then extract their own version of what they need from that large language model. So the training piece will go away, I think, as a percentage of the whole inferencing will obviously take on a greater share in the future. And with that, as you noted, the more speed and information availability there is closer to the decision-making that could make or break someone's competitiveness. And so the solutions we're thinking about are how do we not just, as you said, leverage the platform, but how do we develop and offer our customer base the highest performing, highest reliable systems where there might not be IT resources in that environment? And that's a key part of our strategy. But you could see a day where we might be designing small cluster platforms or single cluster platforms with these platforms from a cost and a reliability and a performance perspective that allows them to be in these end markets, something like oil and gas, maybe on a rig, maybe at a retail store, maybe at an ATM, maybe at a healthcare regional office, what have you. It's just these are the way we're thinking about AI. Clearly, AI at the edge has got a bright future. It's just so early. I mean, AI in general is early. So we're investing for tomorrow as we think about that solution platform we're developing.

Excellent. And then just one last quick one on the memory outlook. You called for growth to be high-single-digits. We've heard from a lot of folks in the memory industry that pricing for both DRAM and NAND is moving up pretty quickly here, especially after the earthquake in Taiwan. Wondering as you look at that high-single-digit, is that mostly ASP growth? With units still pretty muted, are you starting to see a unit recovery, but pricing benefits may come in future quarters? Just how you're thinking about units versus ASP? And I'll go back in the queue. Thank you.

Yeah. Let me just -- before I get to the specific, I just want to highlight, if you go back and look at memory cycles, unlike the pure play semiconductor companies, we made money through the cycles, okay? And we do that because we have a differentiated business. And we also see that if you go back and plot this out, we're kind of slower on the front end of feeling the pain of the downturn. And on the back end, our recovery is a little bit slower because of these inventory corrections of select inventory that customers may be sitting on or are holding back from in terms of how they look at acquiring memory. So we are starting to see pricing benefits in our business overall, and we're seeing corner cases of demand requests. I would say that our demand has been somewhat flat of late, but that's better than declining over the last couple of quarters. And if you look back at the last earnings call, I suspected, I projected that my view of the world was that we could probably start to see some more demand in our Q3, Q4 timeframe, because I just thought it was going to be a little slower. And we're starting to see that turnaround. It's just, it's not here in the Q2 numbers. And I think in Q3, we're starting to see a little bit more of a demand, and I think we'll continue to see that through Q4 and early fiscal year '25.

Yeah. And Quinn, just to highlight Mark's point there in terms of the margins, and you can look at our operating margins for this business, even in Q2, which was a softer quarter here, off margins were just above 7%, and we're starting to see some expectations for growth. That's what we guided to here for Q3 sequentially, for the memory business as well.

Perfect. Thank you.

Thank you. The next question comes from the line of Kevin Cassidy with Rosenblatt Securities. Kevin, your line is now open.

Yes. Thank you for taking my question and congratulations on the quarter. Can you talk a little more about, with IPS, you said it would be flat to up depending on at least one order. And does this include services? And is this part of what the guidance for gross margin being 1.5% one way or the other? Can you just give a little more details on that?

Yeah. So thanks, Kevin. Thanks for the question. I'm going to start and let Ken jump in. As we said originally, if you go back to our Q1 earnings call, we saw a stronger second half, and that's, in fact, what we see playing out. And part of these engagements, the margin move-around is kind of muted. It could be mixed issues. It could be hardware early configurations that we then convert services to. And if you look at all of that, we're in a good place. The margins will move around, as you said. I'll let Ken kind of quantify that a little bit, but margins will move around in our business a little bit. But let's not forget, gross margins are up from 19.5% three years ago to where we are today. And if a margin moves around a point in a quarter, it's primarily because of mix of maybe hardware deployments in a quarter and then future quarters where software might be stronger or services might be stronger. And that's just the nature of the business we're in. Very pleased with the team's execution and very confident that we'll continue to see good progress there.

Yeah. And Kevin, if you look at the margin, we provided a little bit more room here in Q4, and part of that's just around the timing of not only the hardware deployments, which we've talked about in the past, and making sure we get the appropriate customer acceptance and the like, and those can move between quarters. That's why we outlined that. But if you look at the margin for Q4 and the guidance, we have both point-in-time services and ongoing managed services. And we just wanted to have a little bit more flexibility. My assumption is most of the street will probably end up near the midpoint, but that gives us a little flex around that.

Okay. Great. Thanks for that color. And maybe, as you're saying, your engagements are increasing, can you talk more about the potential for expanding your customer base for IPS in particular?

Yeah, absolutely. I think, Kevin, as you know, this is a business that we've talked about repeatedly was -- is a business that we've said it's got customer concentration and can be lumpy. We've invested very heavily over the last fiscal year here the last nine months to 12 months on bringing on new go-to-market resources. And to be very honest, I'm super pleased with the progress we're making there in terms of, again, managing major accounts and getting the executive engagement to go market our capabilities to these large enterprises and Tier 2 CSPs. The amount of proposals that we have generated continues to increase with the opportunities we're seeing and we're looking forward to get on a path where those convert into bookings and revenue over time. You think about we get them booked, but again, we have to then go off and then map that out against supply chain confirmation of what we can do in our configurations. And then we talk about deployment schedules and the like. And so I do want to call something out, because I don't think I've done a good enough job in prior calls. We don't think about our customers like in a buy-sell relationship. That's not our business. And I know it's hard because we used to be a memory module company only and it was very much -- the industry is very much to be transactional. But our transformation that we repeatedly talk about in the market is one of not just going from memory to AI infrastructure and HPC. That's not where it stops. It really is in terms of how we think about our customer relationships more in terms of clients and engagements, because we're with them for a while. We're not just selling something and disappearing.…

Okay. Great. Thank you.

Thank you.

The next question comes from the line of Thomas O'Malley with Barclays. Thomas, your line is now open.

Hi. This is Scott on for Tom O'Malley. I wanted to touch on the services line. So it looks like services down ticked pretty meaningfully in the quarter. Should we think about this as sort of the new run rate level or do you expect that it ticks back up? Thank you.

Yeah. So I think as we look at Q4, I would expect the services to tick up. And as we've highlighted before, within that basket of services that we have, there are kind of point-in-time services, design, implementation, and the like. And there are managed services that we have. And so we had fewer point-in-time services here in Q3. I would expect that number to tick back up here, sorry, in Q2. I would expect that number to tick back up in Q3. And that was embedded in our guide.

Thank you. That's helpful. And then one more, if you could touch again on CXL? Could you just give us an idea of when you see the market inflecting more meaningfully there and then the types of customers that you see interested, whether that's AI or more general purpose?

Why don't I take the first part of that and I'll let Jack talk about more the productization and the revenue. So if you talk to leading technology executives and engineering executives on the AI kind of performance curve and AI infrastructure, by far at the top of the list is latency and performance issues caused by the lack of bandwidth and availability to memory from the GPU and CPU. And there's an immense amount of capital going into investing in early-stage companies as well as some of the larger companies who are investing in solutions that help solve this bandwidth issue. Like if you look at the analogy I like to use is if you think about sharing storage in a network, you can do that today, you can't do that in memory. So eventually you'll have the capabilities. I think it's within CXL 3.0. Out in the future, you'll be able to spool memory, but that's not enough. The transport layer of memory is another issue that people are trying to tackle with optical transport layer with CXL on top of it for just maximizing the speed. High bandwidth memory is not the only solution. And there will be other solutions as it relates to how we can enhance the throughput and the latency and the overall systems performance of the compute by having more innovative hardware solutions like CXL and like optical transport integrated into such a solution. But I'll let Jack talk about kind of the market dynamics around when we see that starting to be a meaningful contributor.

Hi. Yeah, as Mark mentioned, right, we talked -- he talked about the end of kind of this calendar year, we expect to see some meaningful shipments in CXL. And so both, we will be shipping it into kind of your standard server companies. We also were in conversations and we're sampling a lot of different folks in AI as well that want to have more memory in their AI servers. I mean, as HBM grows, you need to put more and more normal memory in your server. And to do that, you start running out of room at the DIMM slots decrease the faster you need to run this memory. So the only way to get that additional memory is really to use CXL and try to pop more memory into that server. So we're seeing opportunities in both phases of the market.

That's very helpful. Thank you.

Thank you.

The next question comes from the line of Brian Chin with Stifel. Brian, your line is now open.

Hi. This is Denis on for Brian. Thanks for letting us ask a few questions. So regarding IPS, how has interest in generative AI over the last year or so changed the customer acquisition into eventually product delivery rollout process? Has it become lengthier or more complex? And then you mentioned you have these options like on-prem, co-location or co-investment. How does the customer's choice of one of these three impact either the timeframe for a rollout or kind of your business in general?

Yeah, that's a great question, and let me just kind of step back a little bit. I remain convinced that we are in the super early innings of AI. And all the noise around sales of GPUs and the like, yes, that's a catalyst or a metric for what's ahead. But I would tell you that I think large-scale enterprises are still really crafting their strategy on AI. I don't think -- I think a lot of those GPU sales went to people in the middle who were building the infrastructure. And I don't think the large-scale enterprises really have fully defined how AI is going to change their business and give them a strategic advantage. So why I say that is this is all playing out real time in front of us. In addition, this is a brand new architecture for any enterprise outside of the big hyperscalers who have been in this for a few years. But, I mean, there are companies who are household brand names in the industries they compete in that really are struggling with even how to design a data center or how to develop the right solution and why you would do a versus b. And so when I think of what your question is getting at is, what is this doing? It's actually made, I think, adoption more of a longer-term process. But I also think, as I mentioned earlier in this call, what I have validated through my executive engagements with our sales organization is large enterprises are starting to get it. They're starting to understand that there is a gap between what they have done from an information technology perspective and the capabilities they will need to deploy AI successfully. And that gap is really the opportunity for a Penguin. And so, from our perspective, yes, it might be a little bit longer, there might be more of an education curve, but that's also leading us to get more sticky and really be able to identify the value that we can provide our partners, our clients that need our help in deploying AI. And I think that's where you sense the confidence and the optimism for the second half of our fiscal year.

Great. Thank you. And then for my follow-up. So, we recently heard about memory price increases, both DRAM and NAND from all of the big memory suppliers. If prices were continue to increase, how would you foresee this impacting your future gross margins?

We're not going to forecast more than we normally do in a given quarter. So Ken's kind of giving you the forecast. I will say a couple of things. I think any such benefits that you've alluded to normally will show up in our top line revenue. But as we've been clear on, on prior calls, our gross margins will trickle up or down depending on which way pricing goes. Why is that? Because when pricing moves, our value add doesn't change and our customers realize that. And so, ironically, when our revenues go down, our margins stay pretty stable, maybe even trickle up a little bit just because of the math of fixed value over a declining revenue stream. And the reverse is true. We might see impact down a point or two or whatever as recovery happens. I don't sense that happening overnight. I don't sense that's something that's going to change the business dynamics. Because more often than not in this type of pricing recovery market, the revenue gain and gross margin dollar contribution mutes out any of the gross margin percentage impact.

Yeah. And what I'd add to that is as we see revenue start to grow, both from units and ASPs over a period of time, where we will see that at the bottom line is an improvement in operating income percent. And you can see that just in the past couple of years, this business, for the memory-specific business, was running at op incomes north of 10%, and we're below that now. So as we start to see unit demand improve as well as ASPs, that should flow to the bottom margin.

Great. Thank you.

Thank you.

And team, at this time we do not have any further questions registered in the queue. So I will turn the call back over for any final remarks.

Well, great. Thank you all for joining. Before just closing out the call, I just wanted to let you know that we have plans for an upcoming IR Day in the next few months or so and details will be coming to you soon. In the meantime, look forward to seeing you at shows and NDRs and the likes. And thanks again for joining today. Have a great week.

That concludes today's call. Thank you all for your participation. And you may now disconnect your lines.