Quite an interesting week for supercomputing news, albeit a little AMD dominant though of course it’s hard to talk about anything GPU these days without Nvidia being mentioned in the same breath.

Remember Talaas? They had a fair bit of fanfare earlier this year with AI inference token throughput rates that were off the charts. AMD just bought them. So now Nvidia has Groq, AMD has Talaas. As I’ve said in the past, when a use case becomes sufficiently prevalent it ends up being baked into the silicon. LLM inference will be no different and that’s across consumer, edge and data centre. Or at least I think so.

When we released our scheduler selection tool last year, I didn’t think we’d need to make many changes. I mean, the HPC scheduler market seemed pretty mature, and companies weren’t exactly falling over themselves to create new ones now were they. Yea how wrong was I. AMD just dropped one too. ROCm Spur. Obviously, its targeting GPU scheduling as the primary use case, is Slurm compatible and of course written in Rust to keep up with the cool kids. Having said all that, I’m not sure what meaningful addition this brings to the table. Guess we need to update the scheduler selector tool again!

Want to do something with your GPUs that isn’t just 4 bit cat picture generation and needs real precision. AMD has always been supportive of this use case with Nvidia pushing emulation using the Ozaki scheme instead and still hoping to win the top trumps game. Looks like AMD isn’t messing about. Their native hardware FP64 support in MI430X GPUs weighs in faster than Nvidia’s Rubin GPUs even including Ozaki emulation. Crikey. I do wonder how much longer that CUDA moat will hold out.

The scientific community seems to agree with the new DOE supercomputers being AMD based.

Let’s talk CPUs for a minute. Nividia’s new Vera chips seem pretty great, just not quite as great as their marketing material would have you believe. I’d quite like to get my hands on one to see how it stacks up for financial risk analytics workloads rather than the nonsense of Agentic AI that people seem to think needs an insane amount of compute.

All the News in Depth

Cloud and vendor releases for Supercomputing & HPC (and AI too if you change the filters)

Vera is a pretty good CPU; shame they are marketing it as though it isn’t and resorting to fairly petty things.

AMD buys Talaas the AI inference ASIC company. Reuters give you the quick take but if you want meandering tale the ends with surprisingly little detail about Talaas but gives you lots of context then the Next Platform article might be more your speed.

AMD is also rattling Nvidia for real FP64 performance. It was never a question if you needed real non emulated FP64 but even if you can accept Ozaki emulated FP64 it looks like AMD still comes out ahead!

AMD has even dropped their own, Slurm compatible, scheduler. Honestly I’m not sure who this is targeted at or how it moves the game forward if at all.

HMx Labs Updates

We’re starting to look at what version 2 of the COREx benchmark should look like. Want to provide some input?

Benchmarks Should Represent Your Workload: COREX v2

This is your reminder that a benchmark is pointless if it does not represent your own workload. Period.

Flux by HMx LabsHamza

We’d also like to know which venue you prefer for HPC Club

HPC Club: Which Venue Did You Prefer?

What’s more important to you, a casual setting for the conversations or a better environment for the presentation?

Flux by HMx LabsHamza

Off Topic

Most open source projects you’ve heard of probably aren’t developed by lone developers tolling away under the midnight oil out of the goodness of their hear (though for sure that exists). No most of them are probably paid handsomely by big tech. Ever wondered why? This is a pretty solid take which I mostly agree with.

This was quite a good watch.. and I certainly agree that if you take away the noise then there really has been very little of note in the AI space lately.

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Some of the big chip manufacturers are making lots of noise about how great their silicon is on various benchmarks and attempting to bludgeon you into belief with chart crime and long words. Fortunately, we have some actual brainiacs calling them out on it too (not me).

So, this is just your friendly reminder that benchmarks are meaningless unless they genuinely reflect your own workload. It really is as simple as that.

Which brings me to COREx, our little financial risk analytics benchmark. The same absolutely applies to this too. Which is why we’re working on version 2. 

Financial risk analytics is not a homogenous blob. When I first created COREx, the next best thing was running the unit tests for QuantLib and this was certainly an improvement. 

But we can do better. 

Specifically, I feel the difference between real time risk and end of day risk needs to be better captured as does the difference between market risk and portfolio risk.

That’s just me though, so before we run headlong into this, I’d love to get some input from you too. 

I have a question for the HPC Club regulars amongst you. 

Especially if you came to the last event at The Crypt and have been to previous events at Notes Café. Simple question. Which venue did you prefer?

We broke with tradition a little for the last event to allow us to have a remote presenter (I hope you’ll agree it was worth it), but if we stick to our general rule of in person only for the next event, where would you prefer we hold it?

Personally, I think The Crypt was amazing for the presentation. Having decent audio, a big screen and seating setup for a presentation made a huge difference. But I also like the really casual nature and easy conversations that happen when we hold it at Notes.

Which did you prefer?

AI infrastructure made lots of noise, mostly I guess because its earnings season, IBM and partners claimed quantum advantage and the EU wants to join the AI party.

Let’s talk quantum advantage first though because I’m sure you had enough other outlets pushing AI news down your throat last week. IBM and partners, announced quantum advantage for several use cases with IBM’s 156 qubit Heron. The claims here are fairly impressive with validation of the quantum compute using other trapped ion systems from Quantinuum and the classical compute comparison done using Fugaku which held the number one spot on the Top500 in 2020 and is still ranked at number 9.

HPC Wire seem to concur that we’re close to utility, if not there already, for quantum computing too.

I’d love to provide some kind of independent commentary on the above, but this is really hard to do. Unlike, say AI, where it’s pretty easy to validate its capabilities for yourself. the same cannot be said for quantum computing. Even if you had access to a real quantum computer. The amount of work, and level of both domain knowledge and math required simply places it out of reach for most people. I would like to answer this question though for a use case that we work with extensively. Financial risk analytics. So, we’re working on that, stay tuned for more.

Its earnings season on Wall Street and of course because the biggest companies work in AI infrastructure which is the most super of supercomputing you’re probably impacted if you have to purchase any kind of compute let alone a new supercomputer. 

My condolences if you’re in that position. 

The news is not easy to decipher. On the one hand, we have worsening credit spreads on corporate bonds for AI infrastructure companies and Oracle being downgraded to just above junk bond status. On the other hand, we have stellar earnings and increased investment into AI infrastructure from the hyperscalers.

In the midst of this, the EU has decided to enter the fray with EuroHPC putting out RFPs for AI gigafactories, or in normal parlance, new supercomputers.

Have a good week all.

All the News in Depth

Cloud and vendor releases for Supercomputing & HPC (and AI too if you change the filters)

IBM and partners claim quantum advantage

HPC Wire also seems to think real use of quantum may be closer than we think

Intel is increasingly looking like its back from its near death experience even if its CPUs don’t quite hold up to its x86 competitors

CoreWeave financing looks increasingly shaky

Oracle downgraded to BBB rating

More circular financing? Nvidia backs OpenAI’s to the tune of $250B

And the EU wans in on the action too

HMx Labs Updates

Is finding developers who understand memory management getting too hard? I’m not just asking as a theoretical conversation starter but because we need people who can and there are still lots of systems in financial services that need these skills

HPC Software Engineer Wanted

We’re still looking for a software engineer who can write code that manages its own memory… Know anyone?

Flux by HMx LabsHamza

Want to accelerate your HPC network (people you know rather than packets on the wire)? For less than the price of a sushi dinner? Read this

Want to Learn HPC and Build an Amazing Network?

The HPC Leadersip Institute, 2026 Edition is taking place at the Barcelona Supercomputing Centre again this year in September.

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Off Topic

I like Alberta, she’s funny. Makes a valid point here too, that I’ve also made in the past is a much less funny way

The whole AI is a scary cyber hacker story from the last week or so is getting out of hand, here’s a good sane take on it all from Cal Newport. Search for it on your podcast app of choice or put up with the ads on YouTube. “The Real Story Behind OpenAI’s Rogue Model”

Codeberg approves the change to ban AI Slop code. I’m wondering if we need to move our private repos off GitHub at least and wondering about Codeberg or internally hosting Forgejo.

Lastly, the family and I are hoping to get away to the alps again for a spot of downhill biking so I’ve been watching the incredibly talented Danny MacAskill with them.

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Psst. Over here. Come closer. I have something to show you.

At the risk of sounding like a scammer, what if I told you that there’s a way that you can be in a room filled with centre directors of national labs, heads of supercomputing and HPC people so smart it will make your head spin.

What would you give to be in that room? For three days. To be able to pick their brains and learn from their experiences.

You’re probably thinking of numbers with four or five zeros at the end? It probably should cost that. But it doesn’t. It will cost less than good sushi dinner. Yea seriously.

To cap it off you also get to visit the most beautiful supercomputer in the world. And its not just me saying that. It’s official.

By now you’re wondering what kind of scam this is and expecting me to give you my wallet address to send me some bitcoin right. But you’d be wrong.

Just go sign up on the Barcelona Supercomputing Centre website for the HPC Leadership institute. Officially they aim to teach you about things like procurement, TCO modelling, investment cases. And they do. But you’ll come away with much more. Including a network of peers that most people would literally pay thousands for.

I attended last year and am tempted to go again, honestly, it’s worth it just to visit Mare Nostrum and be in Barcelona with fellow HPC NErDs for a few days. 

7^th to 10^th September.

HPC Leadership Institute - Edition 2026

HPC Leadership Institute - Edition 2026

BSC-CNS

Is it just me, or is it actually getting hard to hire engineers how to write code that has to manually manage memory?

We’re still hiring for this role. 

I’ve had the odd conversation with some our clients too who seem to be struggling similarly in hiring for roles that demand memory management.

Curiously even developers who have worked with C++ for years, but only ever used smart pointers, seem to struggle.

Maybe this will be a dying breed of programmer, alongside COBOL developers.

Anyhow, we’re still hiring and if you know someone who knows how to write code that expect to manage its own memory, point them my way please!

LinkedIn Job Post

HMx Labs hiring HPC Software Engineer in London Area, United Kingdom | LinkedIn

Posted 9:23:04 AM. Despite the big talk from the like Messrs Altman and Amodei and product hype from Codex and Cursor…See this and similar jobs on LinkedIn.

LinkedIn

Finding the real supercomputing news this week and picking it out of the AI haystack was harder than usual. Which is odd because AMD released its Zen6 CPUs and MI4000 series GPUs.

In a week filled with news about increased spending from OpenAI and Google, the OpenAI and Hugging Face saga and declining OpenAI revenues, what would normally have been a fairly exciting release seems to have been almost lost.

The press release from AMD focuses on its Helios rack scale product but honestly, for those of us that aren’t hyperscalers or neoclouds (in other words most of you reading this) the more interesting part is the chips inside and putting them in your own standard 19” racks not rebuild your entire DC. Unless of course you’re about to replace your supercomputer at a national lab 😉

This is especially true because AMD are still producing GPUs with native FP64 that hasn’t been crippled. You know, stuff for doing real work 😁

I know what you’re thinking though, CUDA. You can’t use AMD. No idea how well this stuff works yet, but they also launched ROCm.ai to try and bridge that gap.

Nvidia being Nvidia though, couldn’t let AMD have the news cycle to themselves and released a few more details about Vera Rubin. We’ve been talking about that for so long, can’t we just get on with it and release it widely please! Maybe no one has any space left to install them (if Ed Zitron is correct).

Not exactly new, but Next Platform has an interesting piece this week too about using AI for quantum error correction. I’d say something snarky about this, but I will hold fire till we complete our literature review of using quantum computing in financial services (specifically for risk analytics). If that goes well, we may have something more interesting to talk about and if it doesn’t then I guess I have more ammunition for my snark cannon. Or more work to do!

In other news, we had our first full week at HMx Towers with Sahana having joined us as our new Strategy and Partnerships lead. We still have an open engineering role though, know anyone that might be interested?

All the News in Depth

Cloud and vendor releases for Supercomputing & HPC (and AI too if you change the filters)

AMD gives us new Zen6 CPUs, MI4000 series GPUs, including some that can do real FP64 work!

And HPC Wire’s take on the release

What about that CUDA moat? Yea AMD’s been working on that… 

Nvidia wasn’t going to let AMD take all the news attention though and provided a few more insights into Vera Rubin

Using AI for quantum computing error correction

HMx Labs Updates

We finally hired someone for our open strategy and partnerships role!

Sahana Christie Joins HMx Labs

We’re excited to welcome Sahana to the HMx Labs team! She’s new to HMx and also to HPC but brings with her a wealth of experience in strategy, comms and business development.

Flux by HMx LabsHamza

We still have one open engineering role though

Hiring: HPC Engineer

We’re looking for another HPC software engineer! Know someone that might be interested? Fancy pointing them my way please? This video was brought to you by the letters H, M and X and the number 42. Have a good weekend everyone. 0:00 /0:03 1× Apply on LinkedIn

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Off Topic

AI spending seems to be accelerating still...

Even Google wants to spend more since it sold more cloud

Even though AI still can't make any money, even with ads

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HPC is about the people. So, I’d like to introduce someone new, Sahana Christie, who has joined us recently. Not only is she new to HMx Labs but also to HPC.

She’s had a bit of a whirlwind start with us. I onboarded (and met for the first time in person!) her on a Monday afternoon at Heathrow airport as we both waited to board our flight to Hamburg for ISC 26. A baptism of fire perhaps. One she needed a well deserved holiday to recover from and she jetted straight off to Japan once we arrived back at Heathrow later that week. As I caught a taxi home, she casually walked across the terminal and boarded another flight 😄

Sahana has a strong background in strategy, business development and communications, words that I barely understand let alone know much about so we’re incredibly excited to have her and help us in this space.

We’ve made a deal where I’ll teach her about NUMA placement of workloads and L3 cache optimisation and she will explain to me what people mean when they say things like “align synergies to create additional stakeholder value” and “collaborate on go to market strategies to capture additional opportunities”. I think she’s got the short end of the stick 🤣

I guess sometimes HPC means high performance career.

Apologies for the picture, I didn’t one of the real Sahana so you get a lego version instead for now.

There seems to be concern that Nvidia is going to slip on its delivery of its Kyber NVL144 racks, even as Jensen continues to promise that the roadmap is intact and on track. There’s a couple of interesting things here. Specifically, it’s not the production of Vera CPUs or Rubin GPUs that’s in question here, it’s the production of the NVL144 rack and the additional interconnects this entails.

Firstly, this gives competitors like AMD and their Helios rack or Google’s TPU architecture a bit of leeway to make inroads into Nvidia’s market. Critically, what’s going to be important here is not the performance of a single GPU but the scale out capability of the entire rack.

Which brings me to my second point. 

The first supercomputers, such as the Cray One used its own integrated circuits designed specifically for it, the evolution and market dynamics of integrated circuits (of which you CPU is one) meant that later supercomputers, such as El-Capitan, were built on integrated circuits provided by companies dedicated to building them such as AMD and Intel. It was companies such as Dell, or HPE that then took those CPUs coupled them with cooling, networking, racks etc and created a supercomputer. Cray disappeared and became part of HPE.

Nvidia is now creating not only the silicon, but the entire rack. I’m not sure if that’s the silicon manufacturer eating the ODM but it does mean we’re returning to an era where the same company is creating the silicon, the interconnects, the rack design and even part of the cooling infrastructure. I wonder how this plays out.

Talking about interconnects, Marvell has released its Teralynx 100 kit.

TSMC is taking its massive profits and investing not only in additional capacity but also the USA. I guess if you’re biggest customers are spending like crazy now is the time to expand.

And coming back to what the ODM now do, they seem to be turning to integrating other accelerator options, specifically quantum, into their offerings with both HPE and Dell offering something in this space and placing quantum computing firmly in the realm of your next accelerator as opposed to your next data center.

All the News in Depth

Cloud and vendor releases for Supercomputing & HPC (and AI too if you change the filters)

TSMC invest further in the USA and plans for greater expansion, or see Next Platform more their more in depth take.

Where’s that Kyber NVL144 gone?

Marvell ups its game in supercomputing interconnects

Quantum is firmly establishing itself as the next type of accelerator

Not quite the point, but this is good example of hybrid AI/Classical workflows establishing themselves

HMx Labs Updates

HPC is like Poker. You always need to know who’s bluffing

HPC is like Poker

My funniest conversation from HPC Club: HPC is like poker!

Flux by HMx LabsHamza

Compute futures and markets I suspect would be amazing for HPC and supercomputing. We have them. Sort of. Sadly not in any way that’s actually useful to the people that need to consume the compute

Compute Futures are Here. Sort Of.

We now have compute futures, something I’ve been wanting for year. But they suck.

Flux by HMx LabsHamza

Off Topic

Layered silicon!

AI Rewrites can work?

Open source is getting harder and harder

Want some cheap GPUs? Almost.

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I have been talking about compute futures for a long time. Since before it was trendy. Before AI drove compute demand through the roof. World famous financial exchanges and back street prediction markets alike are now offering compute future. And I am… underwhelmed.

Why? Surely, I’ve been wanting a way to trade compute and now I finally have it, right? Wrong.

What we have today is the ability to speculate about the price of compute. I understand this is one side of what financial markets offer. It’s not the side that I care about. What I am, and always have been, looking for is the side of financial markets that are used by people that actually care about using the underlying commodity. Not just betting on derivative.

Details are rather scant on Kalshi’s new compute futures and given that half the information I’ve read about it doesn’t even understand the difference between a futures contract and a forward I’m not going to hold my breath that this becomes something useful for anything other than speculation.

If what you really care about is actually buying and consuming compute and want financial markets for all the benefits they bring to that, we still have several unsolved problems that everyone is trying to sweep under the rug. Who care about physical delivery or settlement if all you want to do is provide a cool new replacement to meme coins.

I don’t need to provide the world with another thing to bet on. I want to provide something that has real utility for those us that need to use that compute.

This means solving problems like delivery. No one that is serious about consuming large amounts of compute today is buying a futures contract on a prediction market because their use of that compute will be tied to some very specific APIs and network connectivity. We have nothing even approaching a standardised way to consume compute let alone arranging actual delivery.

It also means solving the fungibility problem. The performance of the same cloud VM type across regions can vary by over 20%, the difference in performance across vendors is even greater. A compute future for a H100 is a completely nonsensical product if you actually care about using that compute and not just speculating on the price of it. And no, the solution here isn’t to make everything homogenous. It’s to know how to have the right exchange rate. An exchange rate that varies by workload.

I’m not just ranting about this either. These are problems that not that hard to solve. We are doing our little bit (see ORB and FLOPx). Doesn’t make it any less frustrating.

HPC is like poker.

I don’t recall how exactly this conversation came about, but that was the opening claim. As per the rules of HPC Club, I won’t disclose who said it, but that person is welcome to claim credit here 😄

“HPC is like poker. You start of thinking it’s about the cards but then realise it’s about the people.”

The idea being, of course, that with HPC it’s not really about the hardware specs, how many GPUs you have or the scheduler you run. It’s about understanding and enabling the users to run the workloads they need to. That wasn’t my response though.

“What, you mean  you need to able to figure out who’s telling the truth and who’s bluffing when they ask you for 256 GPUs?”

I think this bit just as true!

P.S: HPC Club is great to pick up free swag too 😁 🥳

The supercomputing theme for last week seems to have been heterogeneity. Which is kind of fun because we talked about that at HPC Club last week too!

We seem to be heading towards an ever increasing diversity of compute options with both Meta and DeepSeek announcing their own accelerator for AI last week. This comes on top of Meta having already announced its intention to tape out its own ARM based CPUs earlier this year too. Being an AI player or a hyperscaler in the 20s requires your own silicon it would seem. I wonder how long that will last.

I guess it’s just as well then, that startup ZML launched its hardware agnostic LLMD that promises to run your inference across five different options including CUDA (of course), ROCm and Google’s TPUs. Interestingly, they also chose to target Apple Metal for their initial release. I guess they see a chunk of LLM inference heading to local use and this being valuable in the consumer as well as data centre space?

In many ways, the situation with Nvidia and CUDA today reminds me of Intel and MKL in the 2000s. If you were locked into the Intel + MKL ecosystem, it may have been a little painful over the last five years or so watching AMD surpass Intel in both performance and cost per calc. If you experienced that level of lock in, that is no doubt driving some of the desire we see today to gain independence from Nvidia and CUDA. I think that’s great. I would love to see an open ecosystem where it is easy to avoid vendor lock in. Let’s not kid ourselves though.

Cross platform compute is not easy and it’s not cheap. While you may be kicking yourself if you’re locked into Intel CPUs today, you were in a fantastic place for 20 odd years. You might be surprised to hear me advocating for voluntary vendor lock in. And I’m not really. What I am saying is to make your choices carefully. The alternative is not free and sometimes, provided you understand what you’re letting yourself in for, the vendor lock in can be preferable.

If you missed HPC Club last week and want to catch up on what the team at Lawrence Livermore National Lab had to say then you’ll be glad to hear you can watch it online, the details for that and the rest of the supercomputing news from last week in depth is below.

All the News in Depth

Cloud and vendor releases for Supercomputing & HPC (and AI too if you change the filters). Google has a new network optimised, Intel Xeon Emerald Rapids based, VM type with the C4N.

Meta wants to make its own accelerators too now, having already decided that it needed its own ARM based CPUs earlier this year.

DeepSeek, with possibly a stronger reason, has also decided to make its own

ZML’s accelerator independent LLMD goes live giving us a fighting shot at being able to run our code on at least some of these accelerators without lots of rework and their own press release.

You know when there’s an outage how it’s always DNS? Well, HPC has its own rule, it’s always the data. Anyone that’s been working in supercomputing for a minute already knows this of course but it’s fun to see all the AI kids learning that lesson too.

HMx Labs Updates

If you missed HPC Club last week but really want to know what the clever people at LLNL are up to with HPC and agentic workflow, you can watch their presentation online.

HPC Club: Supercomputing, Agentic AI & Finance with LLNL

That’s a wrap on HPC Club with Lawrence Livermore National Lab. Amazing presentation from Vanessa and Dan on Flux Framework, Agentic workflows tied in with their use in financial services.

Flux by HMx LabsHamza

We’re still hiring

Hiring: HPC Engineer

We’re looking for another HPC software engineer! Know someone that might be interested? Fancy pointing them my way please? This video was brought to you by the letters H, M and X and the number 42. Have a good weekend everyone. 0:00 /0:03 1× Apply on LinkedIn

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Off Topic

Linus Torvalds and The Primeagen on AI written code

I like Ed Zitron but this feel pretty spot on to me

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One of the things I love most about HPC Club is its ability to enable cross domain and interdisciplinary conversations. And Vanessa and Dan exemplified this perfectly by turning their experience operating El Capitan, one of the world’s largest supercomputers, to financial services at our last event.

Financial services and academia have historically been seen as distinct. The very personification of high throughput computing versus classical high performance computing. But they’re converging.

And the financial services community may also be one of the last to admit it.

Most people still have the impression that financial services run only embarrassingly parallel compute (P.S: I really don’t like that term). This was true in 2000. Today the answer is far more nuanced. From 2008 or so with the increase in portfolio risk analytics a lot the demand for compute in banking has been made to fit the mould of HTC and the systems that were already available. If someone had handed the quant team a MPI manual, things would look quite different!

The arrival of LLM inference has served only to increase that pressure. Topological awareness and inter node communication are starting to become as important as high throughput rates.

We are also operating in a world that is increasingly heterogenous. The introduction of CUDA meant dealing with CPU vs GPU compute. Although it’s been almost twenty years, honestly even this level of heterogeneity is not well solved today. Yes, it works. Yes, it can be well optimised. Not it’s not commoditised and easy to do. It should be.

Not only do we now have an increased variability in CPU architectures with the large scale adoption of ARM, RISC-V on the horizon and AMD taking centre stage from Intel in the x86 world, we are looking at an increasingly varied accelerator space. This means not only GPUs alternatives from AMD, Google’s TPU, wafer scale accelerators from Cerberas to name a few but also quantum and neuromorphic computing muscling in. These challenges are not unique to either academia or finance.

It's against this backdrop that Vanessa and Dan from Lawrence Livermore National Lab presented Flux Framework and the use of Agentic AI in HPC and supercomputing. All wrapped up with is application to a domain that new to them: Financial services.

Like I said, a perfect example of cross domain collaboration.

The full presentation is now available on YouTube. Links on the HPC Club website.

HPC Club is today!

Quick reminder that it is taking place in Farringdon and not Canary Wharf like most of the previous events. The nearest station is Farringdon which is on the Elizabeth and Metropolitan lines (both of which have air conditioning!).

We are sold out but there is a wait list. We occasionally get a few people drop out on the day so do sign up to the wait list if you wanted to come along. If you really need to be in the room and forgot to book your spot, give me a shout 😆

See you this evening folks! 

Lessons from LLNL in Supercomputing & AI - July 2026 - HPC CLUB

HPC Club event on CPUs, GPUs and silicon diversity. Join us for an evening of discussion and networking with industry experts. 26 November 2025 @ 17:00, Canary Wharf, London.

HPC CLUB

You’d have to have your head buried pretty deep in the sand to have not heard the news that Meta is contemplating becoming the newest neocloud. Are they young enough to be a neocloud? Or do they just get to be a regular cloud selling a higher proportion of GPU compute? 🤔

That’s not the interesting bit. The interesting bit is watching for what happens next. We’ve already seen SpaceXAI (whatever it’s called this week) decided to resell their compute capacity to Anthropic and Google. Those deals happened pretty quickly, holding up the narrative that since approximately the end of 2025 there has been a strong demand (and increasing prices) for GPU compute. How quickly, and to whom, any Meta’s spare capacity gets sold may well prove to be a bell weather for how deep the demand for GPU compute (and by association, AI) really is. All against a backdrop of reduced tokenmaxxing and increased adoption of open weight models.

It goes without saying, I really don’t envy anyone having to make the decision on new hardware (especially GPU) purchases right now. At least in terms of trying to guess which way prices are going to go (even if the short-term trajectory is still upwards). Just to make it even harder though, there’s a very valid and interesting question around how much longer we will even need GPUs.

We have a few HPC heavyweights talking about a pattern that plays out over and over again in computing and specifically with CPUs. As a type of compute becomes more prevalent, the ability to perform it (in hardware) on the CPU follows. We saw this with floating point math, media encoding and cryptography, it’s only natural that mixed precision vector math follows right? We can hope. And it’s not like there isn’t prior art in the supercomputing world. I’m looking at you Fugaku and LineShine.

Right now, the demand for silicon seems so insatiable that even the master of supply chain economics, Apple, has put up prices. South Korea is doubling down with large investments into new plants so we can hope that eases supply issues. In about 5 years.

The real constraint to datacentre growth though has always been the utilities it is plumbed in and hooked up to. Interesting then, to see the impact its having on consolidation in the utility markets. You think something looks mature and highly optimized and then the demand increases tenfold overnight, I guess that wakes people up.

Lastly (and most importantly 😉), its HPC Club on Wednesday 🎉. I think we have 2 places left which is pretty unusual so close to the event. See you there!

All the News in Depth

Cloud and vendor releases for Supercomputing & HPC is a bit delayed this week. Our application for tracking seems to have run into a bug. That’ll teach me to vibe code it. Back soon!

Meta to become the latest neo cloud or the in depth Next Platform take

Of course we may not need GPUs too much longer

CPUs or GPUs, assuming we keep demanding the compute perhaps South Korea will be able to produce it or at least the memory that goes with it

Its really not secret that datacentre growth is constrained by (and has been forever) utilities. Interesting to see them starting to consolidate even further though

HMx Labs Updates

HPC Club is this week!

HPC Club – 1 Week to go

One week to go and only a handful of spots left.

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Hiring: HPC Engineer

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Off Topic

Not exactly off topic for this week I guess, Ed Zitron on Meta selling compute

I’m not sure why Dario’s comments from some time ago are being discussed so heavily right now? Well I have some ideas but that’s a whole another 500 words so I’ll keep them to myself.

Besides, Alberta is funnier than I am so just watch this to get some idea.

And just as I start thinking we need to do something in quantum space it gets all weird

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