Taking on CUDA with ROCm: 'One Step After Another'

https://www.eetimes.com/taking-on-cuda-with-rocm-one-step-after-another/

by mindcrime • 3 months ago

264 198 3 months ago

Naive question, could agents help speed up building code for ROCm parity with CUDA? Outside of code, what are the bottlenecks for reaching parity?

jiggawatts• 3 months ago

Lack of focus from AMD management. See the sibling comment: https://news.ycombinator.com/item?id=47745611

They just don't care enough to compete.

WorldPeas2• 3 months ago

to be honest, outside of fullstack and basic MCU stuff, these agents aren't very good. Whenever a sufficiently interesting new model comes out I test it on a couple problems for android app development and OS porting for novel cpu targets and we still haven't gotten there yet. I'd be happy to see a day where it was possible however

catgary• 3 months ago

I’ve found they’re quite good when you’re higher in the compiler stack, where it’s essentially a game of translating MLIR dialects.

hypercube33• 3 months ago

Maybe this is dumb but at the moment through windows (and WSL?) you get: rocm DirectML Vulkan OpenML?

m-schuetz3• 3 months ago

Agents work great for tasks that thousands of developers have done before. This isn't one of those tasks.

WithinReason• 3 months ago

Unless you train them with RL in the right task specifically

superkuh• 3 months ago

AMD hasn't signaled in behavior or words that they're going to actually support ROCm on $specificdevice for more than 4-5 years after release. Sometimes it's as little as the high 3.x years for shrinks like the consumer AMD RX 580. And often the ROCm support for consumer devices isn't out until a year after release, further cutting into that window.

Meanwhile nvidia just dropped CUDA/driver support for 1xxx series cards from their most recent drivers this year.

For me ROCm's mayfly lifetime is a dealbreaker.

canpan2• 3 months ago

I was thinking to get 2x r9700 for a home workstation (mostly inference). It is much cheaper than a similar nvidia build. But still not sure if good value or more trouble.

chao-2• 3 months ago

Talking to friends who have fought more homelab battles than I ever will, my sense is that (1) AMD has done a better job with RDNA4 than the past generations, and (2) it seems very workload-dependent whether AMD consumer gear is "good value", "more trouble", or both at the same time.

Edit: I misread the "2x r9700" as "2 rx9700" which differs from the topic of this comment (about RNDA4 consumer SKUs). I'll keep my comment up, but anyone looking to get Radeon PRO cards can (should?) disregard.

cyberax2• 3 months ago

I have this setup, with 2x 32Gb cards. It's perfect for my needs, and cheaper than anything comparable from NV.

stephlow• 3 months ago

I own a single R9700 for the same reason you mentioned, looking into getting a second one. Was a lot of fiddling to get working on arch but RDNA4 and ROCm have come a long way. Every once in a while arch package updates break things but that’s not exclusive to ROCm.

LLM’s run great on it, it’s happily running gemma4 31b at the moment and I’m quite impressed. For the amount of VRAM you get it’s hard to beat, apart from the Intel cards maybe. But the driver support doesn’t seem to be that great there either.

Had some trouble with running comfyui, but it’s not my main use case, so I did not spent a lot of time figuring that out yet

djsjajah2• 3 months ago

I have 2 of them. I would advise against if you want to run things like vllm. I have had the cards for months and I still have not been able to create a uv env with trl and vllm. For vllm, it’s works fine in docker for some models. With one gpu, gpt-oss 20b decoding at a cumulative 600-800tps with 32 concurrent requests depending on context length but I was getting trash performance out of qwen3.5 and Gemma4

If I were to do it again, I’d probably just get a dgx spark. I don’t think it’s been worth the hassle.

hotstickyballs• 3 months ago

Driver support eats directly into driver development

lrvick9• 3 months ago

ROCm is open source and TheRock is community maintained, and in a minute the first Linux distro will have native in-tree builds. It will be supported for the foreseeable future due to AMDs open development approach.

It is Nvidia that has the track record of closed drivers and insisting on doing all software dev without community improvements to expected results.

KennyBlanken4• 3 months ago

expected results

The defacto GPU compute platform? With the best featureset?

mindcrime• 3 months ago

Last year, AMD ran a GitHub poll for ROCm complaints and received more than 1,000 responses. Many were around supporting older hardware, which is today supported either by AMD or by the community, and one year on, all 1,000 complaints have been addressed, Elangovan said. AMD has a team going through GitHub complaints, but Elangovan continues to encourage developers to reach out on X where he’s always happy to listen.

Seems like they're making some effort in that direction at least. If you have specific concerns, maybe try hitting up Anush Elangovan on Twitter?

djsjajah2• 3 months ago

or by the community

Hmmm

SwellJoe2• 3 months ago

Is it really that short? This support matrix shows ROCm 7.2.1 supporting quite old generations of GPUs, going back at least five or six years. I consider longevity important, too, but if they're actively supporting stuff released in 2020 (CDNA), I can't fault them too much. With open drivers on Linux, where all the real AI work is happening, I feel like this is a better longevity story than nvidia...where you're dependent on nvidia for kernel drivers in addition to CUDA.

https://rocm.docs.amd.com/en/latest/compatibility/compatibil...

Karliss• 3 months ago

You missed the note at the top "GPUs listed in the following table support compute workloads (no display information or graphics)". It doesn't mean that all CDNA or RDNA2 cards are supported. That table is very is very misleading it's for enterprise compute cards only - AMD Instinct and AMD Radeon Pro series. For actual consumer GPUs list is much worse https://rocm.docs.amd.com/projects/radeon-ryzen/en/latest/in... , more or less 9000 and select 7000 series. Not even all of the 7000 series.

Shitty-kitty3• 3 months ago

The splist CDNA/RDNA architecture is a problem for AMD. The upcoming unified UDMA will solve the issue.

shmerl6• 3 months ago

Side question, but why not advance something like Rust GPU instead as a general approach to GPU programming? https://github.com/Rust-GPU/rust-gpu/

From all the existing examples, it really looks the most interesting.

I.e. what I'm surprised about is lack of backing for it from someone like AMD. It doesn't have to immediately replace ROCm, but AMD would benefit from it advancing and replacing the likes of CUDA.

MobiusHorizons• 3 months ago

From the readme:

Note: This project is still heavily in development and is at an early stage.
Compiling and running simple shaders works, and a significant portion of the core library also compiles.
However, many things aren't implemented yet. That means that while being technically usable, this project is not yet production-ready.

Also projects like rust gpu are built on top of projects like cuda and ROCm they aren’t alternatives they are abstractions overtop

shmerl6• 3 months ago

I think Rust GPU is built on top of Vulkan + SPIR-V as their main foundation, not on top of CUDA or ROCm.

What I meant more is the language of writing GPU programs themselves, not necessarily the machinery right below it. Vulkan is good to advance for that.

I.e. CUDA and ROCm focus on C++ dialect as GPU language. Rust GPU does that with Rust and also relies on Vulkan without tying it to any specific GPU type.

HarHarVeryFunny2• 3 months ago

If you don't want/need to program at lowest level possible, then Pytorch seems the obvious option for AMD support, or maybe Mojo. The Triton compiler would be another option for kernel writing.

shmerl6• 3 months ago

I don't think that's something that can be pitched as a CUDA alternative. Just different level.

LegNeato• 3 months ago

One of the rust-gpu maintainers here. Haven't officially heard from anyone at AMD but we've had chats with many others. Happy to talk with whomever! I would imagine AMD is focusing on ROCm over Vulkan for compute right now as their pure datacenter play, which makes sense.

We've started a company around Rust on the GPU btw (https://www.vectorware.com/), both CUDA and Vulkan (and ROCm eventually I guess?).

Note that most platform developers in the GPU space are C++ folks (lots of LLVM!) and there isn't as much demand from customers for Rust on the GPU vs something like Python or Typescript. So Rust naturally gets less attention and is lower on the list...for now.

shmerl6• 3 months ago

I see, thanks. Would be good if Vulkan was pushed more as an approach for this since others are GPU specific.

pjmlp12• 3 months ago

Because the people that care want C++, Fortran, Python and Julia, which already enjoy a rich ecosystem.

lrvick9• 3 months ago

Just spent the last week or so porting TheRock to stagex in an effort to get ROCm built with a native musl/mimalloc toolchain and get it deterministic for high security/privacy workloads that cannot trust binaries only built with a single compiler.

It has been a bit of a nightmare and had to package like 30+ deps and their heavily customized LLVM, but got the runtime to build this morning finally.

Things are looking bright for high security workloads on AMD hardware due to them working fully in the open however much of a mess it may be.

jauntywundrkind2• 3 months ago

https://github.com/ROCm/TheRock/issues/3477 makes me quite sad for a variety of reasons. It shouldn't be like this. This work should be usable.

lrvick9• 3 months ago

Oh I fully abandoned TheRock in my stagex ROCm build stack. It is not worth salvaging, but it was an incredibly useful reference for me to rewrite it.

MrDrMcCoy2• 3 months ago

So much about this confuses me. What do Kitty and ncurses have to do with ROCm? Why is this being built with GCC instead of clang? Why even bother building it yourself when the tarballs are so good and easy to work with?

WhyNotHugo2• 3 months ago

I also attempted to package ROCM on musl. Specifically, packaging it for Alpine Linux.

It truly is a nightmare to build the whole thing. I got past the custom LLVM fork and a dozen other packages, but eventually decided it had been too much of a time sink.

I’m using llama.cpp with its vulkan support and it’s good enough for my uses. Vulkan so already there and just works. It’s probably on your host too, since so many other things rely on it anyway.

That said, I’d be curious to look at your build recipes. Maybe it can help power through the last bits of the Alpine port.

lrvick9• 3 months ago

Keep an eye out for a stable rocm PR to stagex in the next week or so if all goes well.

sigmoid10• 3 months ago

Interesting how Vulkan and ROCM are roughly the same age (~9 years), but one is incredibly more stable (and sometimes even more performant) for AI use cases as side-gig, while the other one is having AI as its primary raison d'être. Tells you a lot about the development teams behind them.

icedchai• 3 months ago

I've built llama.cpp against both Vulkan and ROCm on a Strix Halo dev box. I agree Vulkan is good enough, at least for my hobbyist purposes. ROCm has improved but I would say not worth the administrative overhead.

seemaze2• 3 months ago

I realize it does not address the OP security concerns, but I'm having success running rocm containers[0] on alpine linux specifically for llama.cpp. I also got vLLM to run in a rocm container, but I didn't have time to to diagnose perf problems, and llama.cpp is working well for my needs.

[0] https://github.com/kyuz0/amd-strix-halo-toolboxes

999900000999• 3 months ago

Wait ?

You don't trust Nvidia because the drivers are closed source ?

I think Nvidia's pledged to work on the open source drivers to bring them closer to the proprietary ones.

I'm hopping Intel can catch up , at 32GB of VRAM for around 1000$ it's very accessible

lrvick9• 3 months ago

Nvidia has been pledging that for years. If it ever actually happens, I am here for it.

cmxch2• 3 months ago

Intel

For some workloads, the Arc Pro B70 actually does reasonably well when cached.

With some reasonable bring-up, it also seems to be more usable versus the 32gb R9700.

jeroenhd2• 3 months ago

Nvidia is opening their source code because they moved most of their source code to the binary blob they're loading. That's why they never made an open source Nvidia driver for Pascal or earlier, where the hardware wasn't set up to use their giant binary blobs.

It's like running Windows in a VM and calling it an open source Windows system. The bootstrapping code is all open, but the code that's actually being executed is hidden away.

Intel has the same problem AMD has: everything is written for CUDA or other brand-specific APIs. Everything needs wrappers and workarounds to run before you can even start to compare performance.

salawat2• 3 months ago

Just spent the last week or so porting TheRock to stagex in an effort to get ROCm built with a native musl/mimalloc toolchain and get it deterministic for high security/privacy workloads that cannot trust binaries only built with a single compiler.

...I have a feeling you might not be at liberty to answer, but... Wat? The hell kind of "I must apparently resist Reflections on Trusting Trust" kind of workloads are you working on?

And what do you mean "binaries only built using a single compiler"? Like, how would that even work? Compile the .o's with compiler specific suffixes then do a tortured linker invo to mix different .o's into a combined library/ELF? Are we talking like mixing two different C compilers? Same compiler, two different bootstraps? Regular/cross-mix?

I'm sorry if I'm pushing for too much detail, but as someone whose actually bootstrapped compilers/user spaces from source, your usecase intrigues me just by the phrasing.

lrvick9• 3 months ago

You can get a sense of what my team and I do from https://distrust.co/threatmodel.html

For information on stagex and how we do signed deterministic compiles across independently operated hardware see https://stagex.tools

Stagex is used by governments, fintech, blockchains, AI companies, and critical infrastructure all over the internet, so our threat model must assume at least one computer or maintainer is compromised at all times and not trust any third party compiled code in the entire supply chain.

zby• 3 months ago

It is sad to observe this time and time again. Last year I had the idea to run a shareholder campaign to change this, I suspended it after last years AMD promises - but maybe this really needs to be done: https://unlockgpu.com/action-plan/

alecco• 3 months ago

Apple got it right with unified memory with wide bus. That's why Mac Minis are flying for local models. But they are 10x less powerful in AI TOPS. And you can't upgrade the memory.

I really wish AMD and Intel boards get replaced by competent people. They could do it in very short time. Both have integrated GPUs with main memory. AMD and Intel have (or at least used to have) serious know-how in data buses and interconnects, respectively. But I don't see any of that happening.

ROCm? It can't even support decent Attention. It lacks a lot of features and NVIDIA is adding more each year. Soon they will reach escape velocity and nobody will catch them for a decade. smh

caycep• 3 months ago

Granted, I feel like NVIDIA GPU pricing is such that Mac minis will be way less than 10x cheaper if not already, so one might still get ahead purchasing a bulk order of Mac minis....

KennyBlanken4• 3 months ago

A 5090 will cost you about the same amount of money as a Mac Studio M3 Ultra with eight times the RAM.

It's pretty insane how overpriced NVIDIA hardware is.

bsder• 3 months ago

I really wish AMD and Intel boards get replaced by competent people.

Intel? Agreed. But AMD is making money hand over fist with enterprise AI stuff.

Right now, any effort that AMD or NVIDIA expend on the consumer sector is a waste of money that they could be spending making 10x more at the enterprise level on AI.

KeplerBoy3• 3 months ago

Aren't mac minis flying for "local models" because people have no clue what they are doing?

All those people who bought them for openclaw just bought them because it was the trendy thing to do. No one of those people is running local models on there.

pjmlp12• 3 months ago

They aren't flying outside US, or countries with similar salary levels.

p1esk• 3 months ago

Someone from AMD posted this a few minutes ago, then deleted it:

"Anush's success is due to opting out of internal bureaucracy than anything else. most Claude use at AMD goes through internal infrastructure that can take hundreds of seconds per response due to throttling. Anush got us an exemption to use Anthropic directly. he is also exempt from normal policies on open source and so I can directly contribute to projects to add AMD support. He's an effective leader and has turned ROCm into a internal startup based in California. Definitely worth joining the team even if you've heard bad things about AMD as a whole."

This kind of bullshit is why I don't want to join AMD, even if this particular team is temporarily exempt from it.

brcmthrowaway• 3 months ago

So join NVIDIA instead

nl2• 3 months ago

he is also exempt from normal policies on open source and so I can directly contribute to projects to add AMD support.

It's crazy that this is a big deal.

I understand the need for some kind of governance around this but for it to require a special exemption just shows how far the AMD culture needs to shift.

0xbadcafebee4• 3 months ago

Liability is always a big deal.

noident• 3 months ago

Policies like these are widespread in most companies with >1000 employees

wongarsu2• 3 months ago

And are a part of the reason people always ask "how is it that this company has >1000 employees and gets nothing done"

fg137• 3 months ago

How does that work?

To be able to use Claude directly, you need to handle separate accounts, billing, security etc.

At the very least you'll need to set up SSO separately or asking people to login with one-time password?

That's a lot to ask in a giant corporation. I mean, there are (good) reasons to use an internal gateway in the first place.

hurricanepootis3• 3 months ago

I've been using ROCm on my Radeon RX 6800 and my Ryzen AI 7 350 systems. I've only used it for GPU-accelerated rendering in Cycles, but I am glad that AMD has an option that isn't OpenCL now.

roenxi• 3 months ago

Challenger AMD’s ability to take data center GPU share from market leader Nvidia will certainly depend on the success or failure of its AI software stack, ROCm.

I don't think this is true. ROCm is a huge advantage for Nvidia but as far as I can tell it is more a set of R&D libraries than anything else, so all the Hot New Stuff keeps being Nvidia first and only (to start with) as the library ecosystem for the hotness doesn't exist yet. Then eventually new libraries are created that are CUDA independent and AMD turns out to make pretty good graphics cards.

I wouldn't be surprised of ROCm withered on the vine and AMD still does fine.

ycui1986• 3 months ago

For many LLM load, it seems ROCm is slower than vulkan. What’s the point?

mmis10002• 3 months ago

Compatibility so foundation packages like torch onnx-runtime can run on AMD GPU without massive change in architecture. It's the biggest reason for those stuff that "only works on nvidia gpu". It's not faster if vulkan alternative exists, but at least it runs.

rdevilla2• 3 months ago

ROCm is not supported on some very common consumer GPUs, e.g. the RX 580. Vulkan backends work just fine.

hurricanepootis3• 3 months ago

RX 580 is a GCN 4 GPU. I'm pretty sure the bare minimum for ROCm is GCN 5 (Vega) and up.

daemonologist2• 3 months ago

Among consumer cards, latest ROCm supports only RDNA 3 and RDNA 4 (RX 7000 and RX 9000 series). Most stuff will run on a slightly older version for now, so you can get away with RDNA 2 (6000 series).

BobbyTables2• 3 months ago

Did it used to be different?

A few years ago I thought I had used the ROCm drivers/libraries with hashcat on a RX580

Now it’s obsolete ?

maxloh• 3 months ago

I have the same experience with my RX 5700. The supported ROCm version is too old to get Ollama running.

Vulkan backend of Ollama works fine for me, but it took one year or two for them to officially support it.

chao-2• 3 months ago

I purchased my RX 580 in early 2018 and used it through late 2024.

I am critical of AMD for not fully supporting all GPUs based on RNDA1 and RDNA2. While backwards compatibility is always better than less for the consumer, the RX 580 was a lightly-updated RX 480, which came out in 2016. Yes, ROCm technically came out in 2016 as well, but I don't mind acknowledging that it is a different beast to support the GCN architecture than the RDNA/CDNA generations that followed (Vega feels like it is off on an island of its own, and I don't even know what to say about it).

As cool as it would be to repurpose my RX 580, I am not at all surprised that GCN GPUs are not supported for new library versions in 2026.

I would be MUCH more annoyed if I had any RDNA1 GPU, or one of the poorly-supported RDNA2 GPUs.

daemonologist2• 3 months ago

ROCm usually only supports two generations of consumer GPUs, and sometimes the latest generation is slow to gain support. Currently only RDNA 3 and RDNA 4 (RX 7000 and 9000) are supported: https://rocm.docs.amd.com/projects/install-on-linux/en/lates...

It's not ideal. CUDA for comparison still supports Turing (two years older than RDNA 2) and if you drop down one version to CUDA 12 it has some support for Maxwell (~2014).

terribleperson• 3 months ago

It's pretty crazy that a 6900XT/6950XT aren't supported.

0xbadcafebee4• 3 months ago

Worse, RDNA3 and RDNA4 aren't fully supported, and probably won't be, as they only focus on chips that make them more money. If we didn't have Vulkan, every nerd in the world would demand either a Mac or an Intel with Nvidia chip. AMD keeps leaving money on the table.

kombine• 3 months ago

I have RX 6700XT, damn. AMD is shooting themselves in the foot

imtringued2• 3 months ago

If you are on an unsupported AMD GPU, why would you ever consider switching to a newer AMD GPU, considering you know that it will reach the same sorry state as your current GPU?

Especially when as you say, the latest generation is slow to gain support, while they are simultaneously dropping old generations, leaving you with a 1-2 year window of support.

pjmlp12• 3 months ago

Vulkan backends work just fine, provided one wants to be constrained by Vulkan developer experience without first class support for C++, Fortran and Python JIT kernels, IDE integration, graphical debugging, libraries.

bruce343434• 3 months ago

In my experience fiddling with compute shaders a long time ago, cuda and rocm and opencv are way too much hassle to set up. Usually it takes a few hours to get the toolkits and SDK up and running that is, if you CAN get it up and running. The dependencies are way too big as well, cuda is 11gb??? Either way, just use Vulkan. Vulkan "just works" and doesn't lock you into Nvidia/amd.

cmovq• 3 months ago

Vulkan is a pain for different reasons. Easier to install sure, but you need a few hundred lines of code to set up shader compilation and resources, and you’ll need extensions to deal with GPU addresses like you can with CUDA.

rdevilla2• 3 months ago

Ah yes, but those hundred lines of code are basically free to produce now with LLMs...

Arech• 3 months ago

Haha. People have already said what is Vulkan in practice - it's very convoluted low-level API, in which you have to write pretty complicated 200+LoC just to have simplest stuff running. Also doing compute on NVIDIA in Vulkan is fun if you believe the specs word for word. If you don't, you switch a purely compute pipeline into a graphical mode with a window and a swapchain, and instantly get roughly +20% of performance out of that. I don't know if this was a bug or an intended behavior (to protect CUDA), but this how it was a couple years ago.

Almondsetat• 3 months ago

On Windows: download a 3GB exe and install

On Linux: add repository and install cuda-toolkit

Does that take a few hours?

0xbadcafebee4• 3 months ago

AMD has years of catching up to do with ROCm just to get their devices to work well. They don't support all their own graphics cards that can do AI, and when it is supported, it's buggy. The AMDGPU graphics driver for Linux has had continued instability since 6.6. I don't understand why they can't hire better software engineers.

onlyrealcuzzo• 3 months ago

Because they aren't willing to pay for them?

oofbey2• 3 months ago

Years. They neglected ROCm for soooo long. I have friends who worked there 5+ years ago who tried desperately to convince execs to invest more in ROCm and failed. You had to have your head stuck pretty deep in the sand back then to not see that AI was becoming an important workload.

I would love AMD to be competitive. The entire industry would be better off if NVIDIA was less dominant. But AMD did this to themselves. One hundred percent.

tux1968• 3 months ago

It would be very helpful to deeply understand the truth behind this management failing. The actual players involved, and their thinking. Was it truly a blind spot? Or was it mistaken priorities? I mean, this situation has been so obvious and tragic, that I can't help feeling like there is some unknown story-behind-the-story. We'll probably never really know, but if we could, I wouldn't spend quite as much time wearing a tinfoil hat.

jijijijij• 3 months ago

Not even AI. My 5 years old APU is completely neglected by AMD ROCm efforts. So I also can't use it in Blender! I feel quite betrayed to be honest. How is such a basic thing not possible, not to mention years later?

Look where Apple Silicon managed going in the same time frame...

Because of this, I would never consider another AMD GPU for a long time. Gaming isn't everything I want my GPU doing. How do they keep screwing this up? Why isn't it their top priority?

xethos• 3 months ago

I don't understand why they can't hire better software engineers.

Beyond the fact they're competing with the most valuable companies in the world for talent while being less than a decade past "Bet the company"-level financial distress?

shakow• 3 months ago

I don't think that you need top-of-the-line, $1M/yr TC people to revamp a build system.

prewett• 3 months ago

I figure it must be a cultural problem. ATI was known for buggy graphics drivers back in The Day, if I remember correctly. I certainly remember not buying their cards for that reason. Apparently after AMD bought them, they have been unable to change the culture (or didn't care). The state of ATI drivers has always been about the same.

philipallstar• 3 months ago

I don't think they invest nearly as large a percentage of their profits in software compared to Nvidia.

jrm4• 3 months ago

[flagged]

nnevatie• 3 months ago

Why is it called "ROCm” (with the strange capitalization) in the first place? This may sound silly, but in order to compete, every detail matters, including the name.

WanderPanda• 3 months ago

This is so true! Shows a lack of care that usually doesn’t stop at just the naming

slongfield• 3 months ago

It used to stand for "[R]adeon [O]pen [C]o[m]pute", but since it's not affiliated with the Open Compute Project, they dropped the meaning of it a little while ago, and now it doesn't stand for anything.

dnautics• 3 months ago

presumably a reference to rocm/socm robots?

jmward01• 3 months ago

I really want to get to the point that I am looking online for a GPU and Nvidia isn't the requirement. I think we are really close to there. Maybe we are there and my level of trust just needs to bump up.

m-schuetz3• 3 months ago

Problem is, NVIDIA has so many quality of life features for developers. It's not easy getting especially smaller scale developers and academia to use other vendors that are 1) much more difficult to use while 2) also being slower and not as rich in features.

Personally I opted in to being NVIDIA-vendor-locked a couple of years ago because I just couldn't stand the insanely bonkers and pointless complexity of APIs like Vulkan. I used OpenGL before which supported all vendors, but because newer features weren't added to OpenGL I eventually had to make the switch.

I tried both Vulkan and CUDA, and after not getting shit done in Vulkan for a week I tried CUDA, and got the same stuff done in less than a day that I could not do in a whole week in Vulkan. At that moment I thought, screw it, I'm going to go NV-only now.

pjmlp12• 3 months ago

I did my thesis porting my supervisor's project from NeXTSTEP into Windows, was an OpenGL fanboy up to the whole Long Peaks disaster.

Additionally Vulkan has proven to be yet another extension mess (to the point now are actions try to steer it back on track), Khronos is like the C++ of API design, while expecting vendors to come up with the tools.

However, as great as CUDA, Metal and DirectX are to play around with, we might be stuck with Khronos APIs, if geopolitcs keep going as bad or worse, as they have been thus far.

suprjami• 3 months ago

Just in time for Vulkan tg to be faster in almost all situations, and Vulkan pp to be faster in many situations with constant improvements on the way, making ROCm obsolete for inference.

kimixa2• 3 months ago

ROCm vs Vulkan has never been about performance - you should be able to represent the "same" shader code in either, and often they back onto the same compilers and optimizers anyway. If one is faster, that often means something has gone /wrong/.

The advantages for ROCm would be integration into existing codebases/engineer skillsets (e.g. porting an existing C++ implementation of something to the GPU with a few attributes and API calls rather than rewriting the core kernel in something like GLSL and all the management vulkan implies).

m-schuetz3• 3 months ago

Vulkan has abysmal UX though. At one point I had to chose between Vulkan and Cuda for future projects, and I ended up with Cuda because a feasibilty study I couldn't get to work in Vulkan for an entire week, easily worked in Cuda in less than a day.

pjmlp12• 3 months ago

They need lots of steps, hardware support, IDE and graphical debugging integrations , the polyglot ecosystem, having a common bytecode used by several compiler backends (CUDA is not only C++), the libraries portfolio.

taherchhabra• 3 months ago

Genuine question. After claude code, codex etc, can't this be speedup ?

Gasp0de• 3 months ago

I believe this is what that teamlead in the article comments on as next steps?

mstaoru• 3 months ago

I'm team "taking on CUDA with OpenVINO" (and SYCL*), Intel seems really upped their game on iGPU and dGPU lately, with sane prices and fairly good software support and APIs.

I'm not talking gaming CUDA, but CV and data science workloads seem to scale well on Arc and work well on Edge on Core Ultra 2/3.

formerly_proven• 3 months ago

We’ve been talking about this for a good ten years at least and AMD is still essentially in the “concepts of a plan” phase. The AMD GPGPU software org has to be one of the most inconsequential ones at this rate.

mmis10002• 3 months ago

At least they finally do something this time. Now torch and whatever transformer stuff runs normally on windows/linux as long as you installed correct wheel from amd's own repository.

It's a huge step though.

DeathArrow• 3 months ago

Do we get better perf or tokens per second with AMD and its software stack than with Nvidia?

wongarsu2• 3 months ago

The metric where AMD usually comes out on top is perf/$. Or with their instinct cards VRAM/$

amelius• 3 months ago

How long until we can use AI to simply translate all the CUDA stuff to another (more open) platform? I'm getting the feeling we're getting close.

AI won't be working in nVidia's advantage this time.

neuroelectron• 3 months ago

Now that the AI bubble is starting to burst, it's a great time for AMD to reveal their AI ambitions. They've set the tone by hiring low cost, outsourced labor.

Of course everybody knows what's really going on here. It's not an open discussion, however.

adev_2• 3 months ago

A little feedback to AMD executives about the current status of ROCm here:

(1) - Supporting only Server grade hardware and ignoring laptop/consumer grade GPU/APU for ROCm was a terrible strategical mistake.

A lot of developers experiments first and foremost on their personal laptop first and scale on expensive, professional grade hardware later. In addition: some developers simply do not have the money to buy server grade hardware.

By locking ROCm only to server grade GPUs, you restrict the potential list of contributors to your OSS ROCm ecosystem to few large AI users and few HPC centers... Meaning virtually nobody.

A much more sensible strategy would be to provide degraded performance for ROCm on top of consummer GPUs, and this is exactly what Nvidia with CUDA is doing.

This is changing but you need to send a clear message there. EVERY new released device should be properly supported by ROCm.

- (2) Supporting only the two last generations of architecture is not what customers want to see.

https://rocm.docs.amd.com/projects/install-on-linux/en/docs-...

People with existing GPU codebase invests significant amount of effort to support ROCm.

Saying them two years later: "Sorry you are out of update now!" when the ecosystem is still unstable is unacceptable.

CUDA excels to backward compatibility. The fact you ignore it entirely plays against you.

(3) - Focusing exclusively on Triton and making HIP a second class citizen is non-sensical.

AI might get all the buzz and the money right now, we go it.

It might look sensible on the surface to focus on Python-base, AI focused, tools like Triton and supporting them is definitively necessary.

But there is a tremendous amount of code that is relying on C++ and C to run over GPU (HPC, simulation, scientific, imaging, ....) and that will remain there for the multiple decades to come.

Ignoring that is loosing, again, custumers to CUDA.

It is currently pretty ironic to see such a move like that considering that AMD GPUs currently tend to be highly competitive over FP64, meaning good for these kind of applications. You are throwing away one of your own competitive advantage...

(4) - Last but not least: Please focus a bit on the packaging of your software solution.

There has been complained on this for the last 5 years and not much changed.

Working with distributions packagers and integrating with them does not cost much... This would currently give you a competitive advantage over Nvidia..

pjmlp12• 3 months ago

Additional points, CUDA is polyglot, and some people do care about writing their kernels in something else other than C++, C or Fortran, without going through code generation.

NVidia is acknowledging Python adoption, with cuTile and MLIR support for Python, allowing the same flexibility as C++, using Python directly even for kernels.

They seem to be supportive of having similar capabilities for Julia as well.

The IDE and graphical debuggers integration, the libraries ecosystem, which now are also having Python variants.

As someone that only follows GPGPU on the side, due to my interests in graphics programming, it is hard to understand how AMD and Intel keep failing to understand what CUDA, the whole ecosystem, is actually about.

Like, just take the schedule of a random GTC conference, how much of it can I reproduce on oneAPI or ROCm as of today.

Symmetry• 3 months ago

There actually isn't any locking involved. I can take a new, officially unsupported version of ROCm and just use it with my 7900 XT despite my card not being officially supported and it works. It's just that AMD doesn't feel that they need to invest the resources to run their test suite against my card and bless it as officially supported. And maybe if I was doing something other than running PyTorch I'd run into bugs. But it's just laziness, not malice.

machomaster• 3 months ago

This is a very unprofessional attitude. There is no space for laziness in business.

hmry• 3 months ago

I used to be able to run ROCm on my officially unsupported 7840U. Bought the laptop assuming it would continue to work.

Then in a random Linux kernel update they changed the GPU driver. Trying to run ROCm now hard-crashed the GPU requiring a restart. People in the community figured out which patch introduced the problem, but years later... Still no fix or revert. You know, because it's officially unsupported.

So "Just use HSA_OVERRIDE_GFX_VERSION" is not a solution. You may buy hardware based on that today, and be left holding the bag tomorrow.

shawnz• 3 months ago

Supporting only Server grade hardware and ignoring laptop/consumer grade GPU/APU for ROCm was a terrible strategical mistake. A lot of developers experiments first and foremost on their personal laptop first and scale on expensive, professional grade hardware later.

NVIDIA is making the same mistake today by deprioritizing the release of consumer-grade GPUs with high VRAM in favour of focusing on server markets.

They already have a huge moat, so it's not as crippling for them to do so, but I think it presents an interesting opportunity for AMD to pick up the slack.

0xbadcafebee4• 3 months ago

Working with distributions packagers and integrating with them does not cost much... This would currently give you a competitive advantage over Nvidia..

Packaging is actually a huge amount of effort if you try to package for all distros.

So the common long-standing convention is to use a "vendored software" approach. You design everything to install into /opt/foo/, and you provide a simple install script to install everything, from one (or several) giant zips/tarballs. It's very old and dumb but it works quite well. Easy to support from company perspective, just run your dumb installer on a couple distros once in a while. Don't depend on distro-specific paths, use basic autodetection to locate and load libraries/dependencies.

Once you do that, it is actually easier for distros to package your software for you. They make one basic package that runs the installer, then they carve up the resulting files into sub-packages based on path. Then they just iterate on that over time as bugs come in (as users try to install just package X.a, which really needs files from X.b).

But you need to hire people with expertise in the open source world to know all this, and most companies don't. Maybe there's just not a lot of us left out there. Or, more likely, they just don't understand that wider support + easier use = more adoption.

adev_2• 3 months ago

Packaging is actually a huge amount of effort if you try to package for all distros.

That's the neat part: You do not have too package for all the distro.

Just make your components easy to decouple with provided pkg-config (ideally) and a proper configuration mechanism.

No bundle, no hidden download or tangled vendored messy script.

Then it is easy to do: you can just provide the packages for your main targets (e.g Ubuntu, Redhat typically) and the community of other distros will take care of the rest.

grokcodec• 3 months ago

The day ROCm supports EVERY AMD card on release, just like CUDA does, is the day I will actually believe this marketing hype.They really dropped the ball here, also when they abandoned recently released cards (at the time) like the 400 series. Hopefully management gets their heads out of their butts and invests more in the software stack.

greenail• 3 months ago

I think GB10 is a bit of a counter point. There are tons of features that are not implemented for GB10 which was released 8/2025 It isn't all roses on the cuda side.

AshamedCaptain• 3 months ago

Last year, AMD ran a GitHub poll for ROCm complaints and received more than 1,000 responses. Many were around supporting older hardware, which is today supported either by AMD or by the community, and one year on, all 1,000 complaints have been addressed, Elangovan said.

Must have been by waiting for each of the 1000 complainers to die of old age, because I do not know what old hardware they have added support for.

throwaway1737382• 3 months ago

I guess it counts if you can find the information from one of the many conflicting wikis out there and then figure out how to hack support for your card into the specific version of ROCm.

androiddrew2• 3 months ago

I have been trying since February to get someone at AMD to shipped tuned Tensile kernels in the rcom-libs for the gfx1201. They are used by Ollama but no one on the Developer Discord knows who is responsible for that. It has been pretty frustrating and it shows that AMD has an organizational problem to overcome in addition to all the things technically that they want rocm to do.

FuriouslyAdrift• 3 months ago

Have you filed anything at github? https://github.com/zichguan-amd seems to be one of the main people for that...

or https://github.com/harkgill-amd

androiddrew2• 3 months ago

I’ll try and get in touch with them. Thank you.

naasking• 3 months ago

ROCm is so annoying (buggy, fiddly dependencies, limited hardware support) that TinyGrad built its own compiler and toolchain that targets the hardware directly. And it has broader device support than ROCm, which primarily seems focused on their datacenter GPUs.

ethan_smith• 3 months ago

The TinyGrad approach of going straight to the hardware is telling. Between that, Vulkan compute getting faster for inference (llama.cpp Vulkan backend is competitive now), and SYCL/oneAPI, it feels like the real threat to CUDA might not be ROCm at all but a fragmented set of alternatives that each bypass AMD's broken software stack entirely.

xyzsparetimexyz• 3 months ago

Better title: One Dispatch After Another

nullpoint420• 3 months ago

I just don’t understand how they haven’t figured this out yet. I genuinely want to know the corporate structure and politics that have lead to their inability to execute.

Is it leadership? Something else?

StillBored2• 3 months ago

I just wish they would make another pass at cleaning up the stack. It should be easy to `git clone --recurse-submodules rocm` followed by a configure/make that both prints out missing dependencies and configures without them, along with choices for 'build the world' vs just build some lower level opencl/HIP/SPIRV tooling without all the libraries/etc on top in a clear way.

Right now the entire source base is literally throw a bunch of crap into the rocm brand and hope it builds together vs some overarching architecture. Presumably the entire spend it also tied to "whatever big Co's evaluation needs this week" when it comes to developing with it.

mellosouls• 3 months ago

Related from Jan 2025:

ROCm Device Support Wishlist (205 points, 107 comments)

https://news.ycombinator.com/item?id=42772170

Taking on CUDA with ROCm: 'One Step After Another'

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