My only guess is they have a parallel skunkworks working on the same thing, but in a way that they can keep it closed-source - that this was a hedge they think they no longer need, and they are missing the forest for the trees on the benefits of cross-pollination and open source ethos to their business.
but then stopped
Do you expect them to be able to capitalize on the AI fad so much (and quickly enough!) that it's worth dropping the ball on projects they're now doing well in? Or perhaps continue investing into the part of the market where they're doing much better than nVidia?
oof
But management at AMD should be above petty team politics and fund both because at the company level they do not care which solution wins in the end.
They very much plan to compete in this space, and hope to ship $3.5B of these chips in the next year. Small compared to Nvidia's revenues of $59B (includes both consumer and data centre), but AMD hopes to match them. It's too big a market to ignore, and they have the hardware chops to match Nvidia. What they lack is software, and it's unclear if they'll ever figure that out.
The margins on supercompute-related sales are very high. Simplifying, but you can basically take a consumer chip, unlock a few things, add more memory capacity, relicense, and your margin goes up by a huge factor.
So, again, it's not at all clear that AMD being in the compute GPU game is the automatic win for them in the future. There's plenty of companies that killed themselves trying to run after big profitable new fad markets (see: Nokia and Windows Phone, and many other cases).
So let's examine that - does AMD actually have a good shot of taking a significant chunk of market that will offset them not investing in some other market?
Meanwhile CUDA supports anything with Nvidia stamped on it before it's even released. They'll even go as far as doing things like adding support for new GPUs/compute families to older CUDA versions (see Hopper/Ada and CUDA 11.8).
You can go out and buy any Nvidia GPU the day of release, take it home, plug it in, and everything just works. This is what people expect.
AMD seems to have no clue that this level of usability is what it will take to actually compete with Nvidia and it's a real shame - their hardware is great.
the hardware is already good enough, people would be happy to use it and accept that's it's not quite as optimized for DL as Nvidia.
people would even accept that the software is not as optimized as CUDA, I think, as long as it is correct and reasonably fast.
the problem is just that every time i've tried it, it's been a pain in the ass to install and there are always weird bugs and crashes. I don't think it's hubris to say that they could fix these sorts of problems if they had the will.
It's a pure business decision based on simple math.
If the estimated revenues from selling to the underserved market are higher than the cost of funding the project (they probably are, considering the obscene margins from NVIDIA), then it's a no-brainer.
Oof x2
For years I want to get off the Nvidia train for AI, but I'm forced to buy another Nvidia card b/c AMD stuff just doesn't work, and all examples work with Nvidia cards as they should.
Now the only thing they need to do is make sure ROCm itself is stable.
"Support" means that the card is actively tested and presumably has some sort of SLA-style push to fix bugs for. As their stack matures, a bunch of cards that don't have official support will work well [0]. I have an unsupported card. There are horrible bugs. But the evidence I've seen is that the card will work better with time even though it is never going to be officially supported. I don't think any of my hardware is officially supported by the manufacturer, but the kernel drivers still work fine.
> Meanwhile CUDA supports anything with Nvidia stamped on it before it's even released...
A lot of older Nvidia cards don't support CUDA v9 [1]. It isn't like everything supports everything, particularly in the early part of building out capability. The impression I'm getting is that in practice the gap in strategy here is not as large as the current state makes it seem.
[0] If anyone has bought an AMD card for their machine to multiply matrices they've been gambling on whether the capability is there. This comment is reasonable speculation, but I want to caveat the optimism by asserting that I'm not going to put money into AMD compute until there is some some actual evidence on the table that GPU lockups are rare.
As a total outsider it seems to me that maybe one of AMD's big problems is they just aren't set up to take advantage of the global talent pool in the same way Nvidia is.
Read an article about it recently, but when trying to remember the details / find it again just now I'm not seeing it. :(
In rational world their stock price would collapse if they don’t focus on it and are unable to deliver anything competitive in the upcoming year or two
> of the market where they're doing much better than nVidia?
So the market that’s hardly growing, Nvidia is not competing in and Intel still has bigger market share and is catching up performance wise? AMD’s valuation is this highly only because they are seen as the only company that could directly compete with Nvidia in the data center GPU market.
Nvidia could always just half their prices one day, and wipe out every non-state-funded competitor. But Nvidia prefers to collect their extreme margins and funnel it into even more R&D in AI.
You’re right about that but it seems that it’s pretty clear that not being in the compute GPU game is an automatic loss for them (look at their recent revenue growth in the past quarter and two by in each sector)
IBM and Microsoft made OS/2. The first version worked on 286s and was stable but useless.
The second version worked only on 386s and was quite good, and even had wonderful windows 3.x compatibility. "Better windows than windows!"
At that point Microsoft wanted out of the deal and they wanted to make their newer version of windows, NT, which they did.
IBM now had a competitor to "new" windows and a very compatible version of "old" windows. Microsoft killed OS2 by a variety of ways (including just letting IBM be IBM) but also by making it very difficult for last month's version of OS/2 to run next month's bunch of Windows programs.
To bring this back to the point -- IBM vs Microsoft is akin to AMD vs Nvidia -- where nvidia has the standard that AMD is implementing, and so no matter what if you play in the backward compatibility realm you're always going to be playing catch-up and likely always in a position where winning is exceedingly hard.
As WOPR once said "interesting game; the only way to win is to not play."
I'm curious about this. Sure some CUDA code has already been written. If something new comes along that provides better performance per dollar spent, why continue writing CUDA for new projects? I don't think the argument that "this is what we know how to write" works in this case. These aren't scripts you want someone to knock out quickly.
If the put their stuff as OpenSource, including firmware, I think they will win out eventually.
And its also not a guarantee that Nvidia will always produce the superior hardware for that code.
This brings back memories of late 90s / early 00s of Microsoft pushing hard their proprietary graphic libraries (DirectX) vs open standards (OpenGL).
Fast forward 25-years and even today, Microsoft still dominates in PC gaming as a result.
There's a bad track record of open standard for GPUs.
Even Apple themselves gave up on OpenGL and has their own proprietary offering (Metal).
They won’t be able to do that, their hardware isn’t fast enough.
Nvidia is beating them at hardware performance, AND ALSO has an exclusive SDK (CUDA) that is used by almost all deep learning projects. If AMD can get their cards to run CUDA via ROCm, then they can begin to compete with Nvidia on price (though not performance). Then, and only then, if they can start actually producing cards with equivalent performance (also a big stretch) they can try for an Embrace Extend Extinguish play against CUDA.
Worked fine for MS with Excel supporting Lotus 123 and Word supporting WordPerfect's formats when those were dominant...
Windows NT wasn't really relevant in that competition for much longer, only XP was finally for end consumers.
> where nvidia has the standard that AMD is implementing, and so no matter what if you play in the backward compatibility realm you're always going to be playing catch-up
That's not true. If AMD starts adding their own features and have their own advantages, that can flip.
It only takes a single generation of hardware, or a single feature for things to flip.
Look at Linux and Unix. Its started out with Linux implementing Unix, and now the Unix are trying to add compatibility with with Linux.
Is SGI still the driving force behind OpenGL/Vulcan? Did you think it was a bad idea for other companies to use OpenGL?
AMD was successful against Intel with x86_64.
There are lots of example of the company making something popular, not being able to take full advantage of it in the long run.
Good enough CUDA + New feature x gives them leverage in the inevitable court battle(S) and patten sharing agreement that everyone wants to see.
AMD' already stuck its toe in the water: new CPU's with their AI cores built in. If you can get a AM5 socket to run with 196 gigs, that's a large (all be it slow) model you can run.
For CUDA, it is not just AMD who would need to catch up. Developers also are not necessarily going to target the latest feature set immediately, especially if it only benefits (or requires) new hardware.
I accept the final statement, but that also means AMD for compute is gonna be dead like OS/2. Their stack just will not reach critical mass.
It's annoying as hell to you and me that they are not catering to the market of people who want to run stuff on their gaming cards.
But it's not clear it's bad strategy to focus on executing in the high-end first. They have been very successful landing MI300s in the HPC space...
Edit: I just looked it up: 25% of the GPU Compute in the current Top500 Supercomputers is AMD
https://www.top500.org/statistics/list/
Even though the list has plenty of V100 and A100s which came out (much) earlier. Don't have the data at hand, but I wouldn't be surprised if AMD got more of the Top500 new installations than nVidia in the last two years.
https://en.wikipedia.org/wiki/Embrace,_extend,_and_extinguis...
People writing CUDA apps don't just want stuff to run, performance is an extremely important factor else they would target CPUs which are easier to program for.
From their readme: > On Server GPUs, ZLUDA can compile CUDA GPU code to run in one of two modes: > Fast mode, which is faster, but can make exotic (but correct) GPU code hang. > Slow mode, which should make GPU code more stable, but can prevent some applications from running on ZLUDA.
The hardware may be great, but their software ecosystem is utter crap. As long as they stay the unchallenged leader in hardware, I expect Nvidia will continue to produce crap software.
I would push to switch our products in a heartbeat, if AMD actually gets their act together. If this alternative offers a path to evaluate our current application software stack on an AMD devkit, I would buy one tomorrow.
Meanwhile Excel was gaining features and winning users with them even before Windows was in play.
By what measures hasn't that happened already? CUDA been around and constantly improving for more than 15 years, and there is no competitors in sight so far. It's basically the de facto standard in many ecosystems.
Rosetta 2 runs apps at 80-90% their native speed.
At which point why tie yourself to the competitor's language. Probably much more effective to just write a well optimized library that serves the MLIR/whatever is popular API in order to run big ML jobs.
CUDA currently has the better raw performance, better availability, and a long record indicating that the platform won't just disappear in a couple of years. You can use it on pretty much any NVIDIA GPU and it's properly supported. The same CUDA code that ran on a GTX680 can run on an RTX4090 with minimal changes if any (maybe even the same binary).
In comparison, AMD has a very spotty record with their compute technologies, stuff gets released and becomes effectively abandonware, or after just a few years support gets dropped regardless of the hardware's popularity. For several generations they basically led people on with promises of full support on consumer hardware that either never arrived or arrived when the next generation of cards were already available, and despite the general popularity of the rx580 and the popularity of the Radeon VII in compute applications, they dropped 'official' support. AMD treats its 'consumer' cards as third class citizens for compute support, but you aren't going to convince people to seriously look into your platform like that. Plus, it's a lot more appealing to have "GPU acceleration will allow us to take advantage of newer supercomputers, while also offering massive benefits to regular users" than just the former.
This was ultimately what removed AMD as a consideration for us when we were deciding on which to focus on for GPU acceleration in our application. Many of us already had access to an NVIDIA GPU of any sort, which would make development easier, while the entire facility had one ROCm capable AMD GPU at the time, specifically so they could occasionally check in on its status.
So while Intel had to bow to AMD's success and give up Itanium, they weren't then limited by that and could proceed to iterate on top of it.
Meanwhile it'll be a cold day in hell before Nvidia licenses anything about CUDA to AMD, much less allows AMD to iterate on top of it.
The right path for AMD has always been to make their own API that runs on all of their own hardware, just as CUDA does for Nvidia, and push support for that API into all the open source ML projects (but mostly PyTorch), while attacking Nvidia's price discrimination by providing features they use to segment the market (e.g. virtualization, high VRAM) at lower price points.
Perhaps one day AMD will realize this. It seems like they're slowly moving in the right direction now, and all it took for them to wake up was Nvidia's market cap skyrocketing to 4th in the world on the back of their AI efforts...
Well, then I guess CUDA is not really the problem, so being able to run CUDA on AMD hardware wouldn't solve anything.
> try for an Embrace Extend Extinguish play against CUDA
They wouldn't need to go that route. They just need a way to run existing CUDA code on AMD hardware. Once that happens, their customers have the option to save money by writing ROCm or whatever AMD is working on at that time.
Not at all, the performance hit was in the low 10s %, before natively supporting Apple Silicon most of the apps I use for music/video/photography didn't seem to have a performance impact at all, even more when the M1 machines were so much faster than the Intels.
Even if AMD lagged support on CUDA versioning, I think it would be widely accepted if the performance per dollar at certain price points was better.
Taking the whole market from NVIDIA is not really an option, it's better to attack certain price points and niches and then expand from there. The CUDA ship sailed a long time ago in my view.
So the contract is: as long as your future program does not touch any intrinsics etc that do not exist in CUDA 1.0, you can export the new program from CUDA 27.0 as PTX, and the GTX 6800 driver will read the PTX and let your gpu run it as CUDA 1.0 code… so it is quite literally just as they describe, unlimited forward and backward capability/support as long as you go through PTX in the middle.
https://docs.nvidia.com/cuda/archive/10.1/parallel-thread-ex...
A lot went wrong with os/2. For CUDA, I think a better analogy is vhs. The standard, in the effective not open sense, is what it is. AMD sucks at software and views it as an expense rather than an advantage.
However, that same logic doesn't apply to consumers, and since they continued to fail to learn that lesson now IBM doesn't even target the consumer market given that they never learned how to be competitive and could only ever effectively function when they had a monopoly or at least a vendor lock-in.
https://en.wikipedia.org/wiki/Acquisition_of_the_IBM_PC_busi...
Ahhhh, your hindsight is well developed. I would be interested to know the background on the reasons why Lotus made that bet. We can't know the counterfactual, but Lotus delivering on a platform owned by their deadly competitor Microsoft would seem to me to be a clearly worrysome idea to Lotus at the time. Turned out it was an existentially bad idea. Did Lotus fear Microsoft? "DOS ain't done till Lotus won't run" is a myth[1] for a reason. Edit: DRDOS errors[2] were one reason Lotus might fear Microsoft. We can just imagine a narritive of a different timeline where Lotus delivered on Windows but did some things differently to beat Excel. I agree, Lotus made other mistakes and Microsoft made some great decisions, but the point remains.
We can also suspect that AMD have a similar choice now where they are forked. Depending on Nvidea/CUDA may be a similar choice for AMD - fail if they do and fail if they don't.
[1] http://www.proudlyserving.com/archives/2005/08/dos_aint_done...
[2] https://www.theregister.com/1999/11/05/how_ms_played_the_inc...
Proton, Wine, and all of the compatibility fixes and drive improvements that the community has made in the last 16 years has been amazing, and every day is another day where you can say that it has never been easier to switch away from Windows.
However, Microsoft has definitely been drinking the IBM koolaid a little to long and has lost the mandate of heaven. I think in the next 7-10 years we will reach a point where there is nothing Windows can do that linux cannot do better and easier without spying on you, and we may be 3-5 years from a "killer app" that is specifically built to be incompatible with Windows just as a big FU to them, possibly in the VR world, possibly in AR, and once that happens maybe, maybe, maybe it will finally actually be the year of the linux desktop.
As such Fermi seems to be the shortest supported architecture, and it was around for 7 years. GCN4 (Polaris) was introduced in 2016, and seems to have been officially dropped around 2021, just 5 years in. While you could still get it working with various workarounds, I don't see the evidence of Nvidia being even remotely as hasty as AMD with removing support, even for early architectures like Tesla and Fermi.
I tried to get it working this weekend but it was a huge PITA so I switched to putting everything into WSL2 then in arch on there pytorch etc in containers so I could flip versions easily now that I know how SPECIFIC the versions are to one another.
I'm still working on that part, halfway into it my WSL2 completely broke and I had to reinstall windows. I'm scared to mount the vhdx right now. I did ALL of my work and ALL of my documentation is inside of the WSL2 archlinux and NOT on my windows machine. I have EVERYTHING I need to quickly put another server up (dotfiles, configs) sitting in a chezmoi git repo ON THE VM. That I only git committed one init like 5 mins into everything. THAT was a learning experience, now I have no idea if I should follow the "best practice" of keeping projects in wsl or having wsl reach out to windows, there's a performance drop. The 9p networking stopped working and no matter what I reinstalled, reset, removed features, reset windows, etc, it wouldn't start. But at least I have that WSL2 .vhdx image that will hopefully mount and start. And probably break WSL2 again. I even SPECIFICALLY took backups of the image as tarballs every hour in case I broke LINUX, not WSL.
If anyone has done sd containers in wsl2 already let me know. I've tried to use WSL for dev work (i use osx) like this 2-3 times in the last 4-5 years and I always run into some catastrophically broken thing that makes my WSL stop working. I hadn't used it in years so hoped it was super reliable by now. This is on 3 different desktops with completely different hardware, etc. I was terrified it would break this weekend and IT DID. At least I can be up in windows in 20 minutes thanks to chocolately and chezmoi. Wiped out my entire gaming desktop.
Sorry I'm venting now this was my entire weekend.
This repo is from a deepspeed contrib (iirc) and lists the reqs for deepspeed + windows that mention the version matches
https://github.com/S95Sedan/Deepspeed-Windows
> conda install pytorch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 pytorch-cuda=12.1 -c pytorch -c nvidia
It may sound weird to do any of this in Windows, or maybe not, but if it does just remember that it's a lot of gamers like me with 4090s who just want to learn ML stuff as a hobby. I have absolutely no idea what I'm doing but thank god I know containers and linux like the back of my hand.
Again, you are missing the point. Java is both a language (java source) and a machine (the JVM). The latter is a hardware ISA - there are processors that implement Java bytecode as their ISA format. Yet most people who are running Java are not doing so on java-machine hardware, yet they are using the java ISA in the process.
https://en.wikipedia.org/wiki/Java_processor
https://en.wikipedia.org/wiki/Bytecode#Execution
any bytecode is an ISA, the bytecode spec defines the machine and you can physically build such a machine that executes bytecode directly. Or you can translate via an intermediate layer, like how Transmeta Crusoe processors executed x86 as bytecode on a VLIW processor (and how most modern x86 processors actually use RISC micro-ops inside).
these are completely fungible concepts. They are not quite the same thing but bytecode is clearly an ISA in itself. Any given processor can choose to use a particular bytecode as either an ISA or translate it to its native representation, and this includes both PTX, Java, and x86 (among all other bytecodes). And you can do the same for any other ISA (x86 as bytecode representation, etc).
furthermore, what most people think of as "ISAs" aren't necessarily so. For example RDNA2 is an ISA family - different processors have different capabilities (for example 5500XT has mesh shader support while 5700XT does not) and the APUs use a still different ISA internally etc. GFX1101 is not the same ISA as GFX1103 and so on. These are properly implementations not ISAs, or if you consider it to be an ISA then there is also a meta-ISA encompassing larger groups (which also applies to x86's numerous variations). But people casually throw it all into the "ISA" bucket and it leads to this imprecision.
like many things in computing, it's all a matter of perspective/position. where is the boundary between "CMT core within a 2-thread module that shares a front-end" and "SMT thread within a core with an ALU pinned to one particular thread"? It's a matter of perspective. Where is the boundary of "software" vs "hardware" when virtually every "software" implementation uses fixed-function accelerator units and every fixed-function accelerator unit is running a control program that defines a flow of execution and has schedulers/scoreboards multiplexing the execution unit across arbitrary data flows? It's a matter of perspective.
They have a hard time to understand the pain points of their consumers, as they don't feel that pain, look trough their own organisation-coloured glases, and can't see the real pain points from the whiney-customer ones.
AMD probably thinks software ecosystems are the easy part, ready to take it on whenever they feel like it and throw a token amount at it. They've built a great engine, see the carossery as beneath them, and don't understand why the lazy customer wants them to build the rest of the car too.
And that someone usually isn't a manufacturer, lest the committee be accused of bias.
Consequently, you get (a) outdated features that SotA has already moved beyond, (b) designed in a way that doesn't correspond to actual practice, and (c) that are overly generalized.
There are some notable exceptions (e.g. IETF), but the general rule has been that open specs please no one, slowly.
IMHO, FRAND and liberal cross-licensing produce better results.
As much as I love Microsoft/Windows for the work they have put into WSL, I ended up just putting Kubuntu on my devices and use QEMU with GPU passthrough whenever I need Windows. Gaming perf is good. You need an iGPU or a cheap second GPU for Linux in order to hand off a 4090 etc. to Windows (unless maybe your motherboard happens to support headless boot but if it's a consumer board it doesn't). Dual boot with Windows always gave me trouble.
Same reason it wasn't when it was obvious Nvidia was taking over this space maybe 8 years ago now when they let OpenCL die then proceeded to do nothing till it's too late.
Speaking to anyone working in general purpose GPU coding back then they all just said the same thing, OpenCL was a nightmare to work with and CUDA was easy and mature compared to it. Writing was on the wall where things were heading the second you saw a photon based renderer running on GPU vs CPU all the way back then, AMD has only themselves to blame because Nvidia basically showed them the potential with CUDA.
These were precisely the arguments for 'x86 will entrench Intel for all time', and we've seen AMD succeed at that game just fine.
First I thought it was hardware related in a Remote Desktop session leading me to think some weird audio driver thing
have you encountered anything like this at all?
(To be clear, HIP is about converting CUDA source code not running CUDA-compiled binaries but the Zluda project discussed in OP heavily relies on it.)
I bet there are at least two markets (or niches):
1. People who want the absolute best performance and the latest possible version and are willing to pay the premium for it;
2. People who want to trade performance by cost and accept working with not-the-latest versions.
In fact, I bet the market for (2) is much larger than (1).
I think the case of cuda vs an open standard is different from os2 vs Windows because the customers of cuda are programmers with access to source code while the customers of os2 were end users trying to run apps written by others.
If your shrink-wrapped software didn't run on os2, you'd have no choice but to go buy Windows. Otoh if your ai model doesn't run on an AMD device and the issue is something minor, you can edit the shader code.
If AMD invented the analogous to x86_64 for CUDA, this would increase competition and progress in AI by some huge fraction.
The big issue for Intel is pretty similar to that of AMD; everything is made for CUDA, and Intel has to either build their own solutions or convince people to build support for Intel. While I'm working on learning AI and plan to use an Nvidia card, its pretty the progress Intel has made in the last couple of years since introducing their first GPU to market has been pretty wild, and I think it really give AMD pause.
... after a couple decades of legal proceedings and a looming FTC monopoly case convinced Intel to throw in the towel, cross-license, and compete more fairly with AMD.
https://jolt.law.harvard.edu/digest/intel-and-amd-settlement
AMD didn't just magically do it on its own.
that's a fascinating statement with the clear ascendancy of neural-assisted algorithms etc. Things like DLSS are the future - small models that just quietly optimize some part of a workload that was commonly considered impossible to the extent nobody even thinks about it anymore.
my prediction is that in 10 years we are looking at the rise of tag+collection based filesystems and operating system paradigms. all of us generate a huge amount of "digital garbage" constantly, and you either sort it out into the important stuff, keep temporarily, and toss, or you accumulate a giant digital garbage pile. AI systems are gonna automate that process, it's gonna start on traditional tree-based systems but eventually you don't need the tree at all, AI is what's going to make that pivot to true tag/collection systems possible.
Tags mostly haven't worked because of a bunch of individual issues which are pretty much solved by AI. Tags aren't specific enough: well, AI can give you good guesses at relevance. Tagging files and maintaining collections is a pain: well, the AI can generate tags and assign collections for you. Tags really require an ontology for "fuzzy" matching (search for "food" should return the tag "hot dog") - well, LLMs understand ontologies fine. Etc etc. And if you do it right, you can basically have the AI generate "inbox/outbox" for you, deduplicate files and handle versioning, etc, all relatively seamlessly.
microsoft and macos are both clearly racing for this with the "AI os" concept. It's not just better relevance searches etc. And the "generate me a whole paragraph before you even know what I'm trying to type" stuff is not how it's going to work either. That stuff is like specular highlights in video games around 2007 or whatever - once you had the tool, for a few years everything was w e t until developers learned some restraint with it. But there are very very good applications that are going to come out in the 10 year window that are going to reduce operator cognitive load by a lot - that is the "AI OS" concept. What would the OS look like if you truly had the "computer is my secretary" idea? Not just dictating memorandums, but assistance in keeping your life in order and keeping you on-task.
I simply cannot see linux being able to keep up with this change, in the same way the kernel can't just switch to rust - at some point you are too calcified to ever do the big-bang rewrite if there is not a BDFL telling you that it's got to happen.
the downside of being "the bazaar" is that you are standards-driven and have to deal with corralling a million whiny nerds constantly complaining about "spying on me just like microsoft" and continuing to push in their own other directions (sysvinit/upstart/systemd factions, etc) and whatever else, on top of all the other technical issues of doing a big-bang rewrite. linux is too calcified to ever pivot away from being a tree-based OS and it's going to be another 2-3 decades before they catch up with "proper support for new file-organization paradigms" etc even in the smaller sense.
that's really just the tip of the iceberg on the things AI is going to change, and linux is probably going to be left out of most of those commercial applications despite being where the research is done. It's just too much of a mess and too many nerdlingers pushing back to ever get anything done. Unix will be represented in this new paradigm but not Linux - the commercial operators who have the centralization and fortitude to build a cathedral will get there much quicker, and that looks like MacOS or Solaris not linux.
Or at least, unless I see some big announcement from KDE or Gnome or Canonical/Red Hat about a big AI-OS rewrite... I assume that's pretty much where the center of gravity is going to stay for linux.
It's a classic "between a rock and a hard place" scenario. Quite a conundrum.
If the players in the space have naturally coalesced around one over the last decade, can we skip the thrashing and just go with it this time?
I've done this on both a hackintosh and void linux. I was so excited to get the hackintosh working because I honestly hate day desktop linux, it's my day job to work on and I just don't want to deal with it after work.
Unfortunately both would break in significant ways and I'd have to trudge through and fix things. I had that void desktop backed up with Duplicacy (duplicati front end) and IIRC I tried to roll back after breaking qemu, it just dumps all your backup files into their dirs, and I think I broke it more.
I think at that point I was back up in Windows in 30 mins.. and all of its intricacies like bsoding 30% of the time that I either restart it or unplug a usb hub. But my Macbooks have a 30% chance of not waking up on Monday morning when I haven't used them all weekend without me having to grab them and open the screen.
WebGPU might be the thing that unifies the frontend API for folks writing cross-platform renderers, seeing as browsers will have to implement it on top of the platform APIs anyway.
https://linuxmusicians.com/viewtopic.php?t=25556
Could be completely unrelated though, RDP sessions can definitely act up, get audio out of sync etc. I try to never do pass through rdp audio, it's not even enabled by default in the mstsc client IIRC but that may just be a "probably server" thing.
I was actually advising an HN user against using Jetson just the other day because it's such an extreme outlier when it comes to Nvidia and software support. Frankly Jetson makes no sense unless you really need the power efficiency and form-factor.
Meanwhile, any seven year old >= Pascal card is fully supported in CUDA 12 and the most recent driver releases. That combined with my initial data points and others people have chimed in with on this thread is far from "utter crap".
Use the right tool for the job.
But yes, AMD was playing the "follow x86" game for a long time until they came up with x86-64, which evened the playing field in terms of architecture.
I would guess there are lots of people still running CUDA 11. Older clusters, etc. A lot of that software doesn't get updated very often.
DirectX was targetted at gaming and was a much more limited simpler API which made programming games in it easier. It couldn't do everything that OpenGL can which is why CAD programs didn't use it even on Windows. DirectX worked because it chose its market correctly and delivered what the customers want. Window's exceptional backwards compatibility helped greatly as well. Many simple game engines still use DX9 API to this day.
It is not so much about having an open standard, but being able to provide extra functionality and performance. Unlike the CPU-dominated areas where executing the common baseline ISA is very competitive, in accelerated computing using every single bit of performance and having new and niche features matter. So providing exceptional hardware with good software is critical for the competition. Closed APIs have much more quick delivery time and they don't have to deal with multiple vendors.
Nobody except Nvidia delivers good enough low level software and their hardware is exceptionally good. AMD's combination is neither. The hardware is slower and it is hard to program so they continuously lose the race.
The only thing it has going for it is being a free beer UNIX clone for headless environments, and even then, isn't that relevant on cloud environments where containers and managed languages abstract everything they run on.
Then there is the whole issue of extension spaghetti, and incompatibilities across OpenGL, OpenGL ES and WebGL, hardly possible to have portable code 1:1 everywhere, beyond toy examples.
Their leadership seems quite a bit more competent than random forum commenters give them credit for. I guess what they need, marketing wise, is a few successful halo GPU launches. They haven't done that in a while. Lisa acknowledged this years ago. It's marketing 101. I guess these things are easier said than done.
H100's are hard to get. Nearly impossible. CoreWeave and others have scooped them all up for the foreseeable future. So, if you are looking at only price as the factor, then it becomes somewhat irrelevant, if you can't even buy them [0]. I don't really understand the focus on price because of this fact.
Even if you do manage to score yourself some H100's. You also need to factor in the networking between nodes. IB (Infiniband) made by Mellanox, is owned by NVIDIA. Lead times on that equipment are 50+ weeks. Again, price becomes irrelevant if you can't even network your boxes together.
As someone building a business around MI300x (and future products), I don't care that much about price [!]. We know going in that this is a super capital intensive business and have secured the backing to support that. It is one of those things where "if you have to ask, you can't afford it."
We buy cards by the chassis, it is one price. I actually don't know the exact prices of the cards (but I can infer it). It is a lot about who you know and what you're doing. You buy more chassis, you get better pricing. Azure is probably paying half of what I'm paying [1]. But I'd also say that from what I've seen so far, their chassis aren't nearly as nice as mine. I have dual 9754's, 2x bonded 400G, 3TB ram, and 122TB nvme... plus the 8x MI300x. These are top of the top. They have Intel and I don't know what else inside.
[!] Before you harp on me, of course I care about price... but at the end of the day, it isn't what I'm focused on today as much as just being focused on investing all of the capex/opex that I can get my hands on, into building a sustainable business that provides as much value as possible to our customers.
[0] https://www.tomshardware.com/news/tsmc-shortage-of-nvidias-a...
[1] https://www.techradar.com/pro/instincts-are-massively-cheape...
Chasing CUDA compatibility is a fool's errand when the most important users of CUDA are open source. Just add explicit AMD support upstream and skip the never ending compatibility treadmill, and get better performance too. And once support is established and well used the community will pitch in to maintain it.
Maybe some Microsoft owned games makers will never make the shift, but if the majority of others do then that's the death knell.
For the non-vendor lock in AI's (copilot), casting as wide of a net as possible to catch customers as easily as possible should by default mean that they would invest the small amount of money to build linux integrations into their AI platforms.
Plus, the googs has a pretty deep investment into the linux ecosystem and should have little issue pushing bard or gemini or whatever they'll call it next week before they kill it out into a linux compatible interface, and if they do that then the other big players will follow.
And, don't overlook the next generation of VR headsets. People have gotten silly over the Apple headset, but Valve should be rolling out the Deckhard soon and others will start to compete in that space since Apple raised the price bar and should soon start rolling out hardware with more features and software to take advantage of it.
It is. All the things are the problem. AMD is behind on both hardware and software, for both gaming and compute workloads, and has been for many years. Their competitor has them beat in pretty much every vertical, and the lock-in from CUDA helps ensure that even if AMD can get their act together on the hardware side, existing compute workloads (there are oceans of existing workloads) won’t run on their hardware, so it won’t matter for professional or datacenter usage.
To compete with Nvidia in those verticals, AMD has to fix all of it. Ideally they’d come out with something better than CUDA, but they have not shown an aptitude for being able to do something like that. That’s why people keep telling them to just make a compatibility layer. It’s a sad place to be, but that’s the sad place where AMD is, and they have to play the hand they’ve been dealt.
You don't win an overall market by focusing on several hundred million dollar bespoke HPC builds where the platform (frankly) doesn't matter at all. I'm working on a project on an AMD platform on the list (won't say - for now) and needless to say you build whatever you have to what's there, regardless of what it takes and the operators/owners and vendor support teams pour in whatever resources are necessary to make it work.
You win a market a generation at a time - supporting low end cards for tinkerers, the educational market, etc. AMD should focus on the low-end because that's where the next generation of AI devs, startups, innovation, etc is coming from and for now that's going to continue to be CUDA/Nvidia.
if that's the case you have billion-dollar opportunities waiting for you to prove it!
If their primary objective is to break the CUDA monopoly, they should up their game in software, which means going as far as implementing support for their hardware in the most popular user apps themselves, if necessary. But since they don't seem to want to do that, they should really go for option one, especially if a single engineer already got so far.
Let's say AMD sold a lot of cards with CUDA support. Now nvidia tries to cut them off. What will happen next? A lot of people will replace their cards with nvidia ones. But a lot of the rest will try to make their expensive AMD cards work regardless. And if AMD provides a platform for that, they will get that work for free.
Unity, Unreal and Godot all support compiling for Linux either by default or with inexpensive or possibly free add-ons. I'm sure many other game engines do as well, and when you're taking a few hours of work at most to add everyone who owns a steam deck or a steam deck clone as a potential customer to your customer base then that is not a tall order.
We already see things like Google abandoning tensorflow support for Windows, because they don't have enough devs using Windows to easily maintain it.
And of course, we have a changing of the guard in terms of a generation of software developers who primarily worked on Windows, because that was the way to do it, starting to retire. Younger devs came up in the Google era where Linux is a first class citizen alongside MacOS.
I think these factors are going to change the face of technology in the coming 15 years, and that's likely to affect how businesses and consumers consume technology, even if they don't understand what's actually running under the hood.
MS has put a collosal amount money into catching up to at least be able to take advantage of the AI wave, that much is clear. Maybe for consumers this will be enough, but R&D wise I don't see them ever being the default choice.
And this is potentially a huge problem for them in the long run, because OS choice by industry is driven by the available tooling. If they lose ML, they could potentially lose traditional engineering if fields like robotics start relying on Linux more heavily.
FOSS folks make this a bigger issue than it really is, game studios make a pluggable API on their engine and call it a day, move on into everything else that matters in actually delivering a game.
nVidia is dominant now. The question is, what's your wedge.
This doesn't make the "play" button any different. People only care if the Proton version is buggy or noticeably less performant, and native ports have no trouble being both of those (see: Rust (game) before the devs dropped Linux support)
It limits Nvidia's profit margin - if Nvidia cards run twice as fast but cost more than twice as much, then people will just buy two AMD cards. Meanwhile, it gives AMD some revenue with which to fund an improved CUDA stack.
>their customers have the option to save money by writing ROCm
CUDA saves money by having a fuckton of pre-written CUDA code and being supported as default basically everywhere.
Crackle would happen so rarely that I KNOW it definitely happened but it wasn't like a 2 day thing it was probably like, once in a year or 6 months, etc.
If you slap a CUDA compatibility layer on top of AMD, then CUDA code optimized for NVIDIA chips would run, but would suffer a performance penalty compared to code that was customized/tuned for AMD, so unless AMD GPUs were sold cheap enough (i.e. with low profit margin) to mitigate this loss of performance you might as well buy NVIDIA in the first place.
You probably already know but just in case you don't: you can set up a Linux VM with VirtualBox on your Windows and then mount the vhdx (read-only) as an additional disk to extract the stuff you need via shared folders.
I'm curios, so WSL2 broke that you cannot even add new distros, remove broken distros? or Windows host itself became unstable?
We can see that it’s not magic, the neuron either activates or it doesn’t, so why should I pay attention to some probabilistic steam of gibberish it spewed out? There is nothing meaningful that can be inferred from such systems, right?