Pytorch VS ROCm

Hi everyone! I’m devloker, and today I’m excited to share a project I’ve been working on: a digit recognition system implemented using pure math functions in Python. This project aims to help beginners grasp the mathematics behind AI and digit recognition without relying on high-level libraries like TensorFlow or PyTorch. You can find the complete code on my GitHub repository.

PyTorch

> their own custom stack to interact with GPUs

lol completely made up.

are you conflating CUDA the platform with the C/C++ like language that people write into files that end with .cu? because while some people are indeed not writing .cu files, absolutely no one is skipping the rest of the "stack".

source: i work at one of these "mega corps". hell if you don't believe me go look at how many CUDA kernels pytorch has https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/n....

> Everybody thinks it’s CUDA that makes Nvidia the dominant player.

it 100% does

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Tinygrad targets consumer hardware (to be precise, only Radeon 7900XTX and nothing else[1]), while ROCm does not actually provide good support for such hardware. For example, last release of hipBLASLt-6.1.1 library has deep integration with PyTorch[1], while working only on AMD Instinct hardware. And even for the professional hardware out there, the support period is ridiculous: AMD Instinct MI100 (2020) is not supported. Only 4 years and tens of thousands of dollars worth of hardware is going to the trash, yay!

And to be more precise, they still use some core libraries from ROCm stack[3], they just don't use all these fancy multi-gigabyte[4] hardware-limited rocBLAS/hipBLASlt/rocWMMA/rocRAND/etc. libraries.

[1] https://tinygrad.org/#tinybox

[2] https://github.com/pytorch/pytorch/issues/119081

[3] https://github.com/tinygrad/tinygrad/blob/v0.9.0/tinygrad/ru...

[4] https://repo.radeon.com/rocm/yum/6.1.1/main/

PyTorch (https://pytorch.org/)

Yep, did exactly that. IMO he threw a fit, even though AMD was working with him squashing bugs. https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...

Ok, I wonder what's wrong. maybe it's this? https://stackoverflow.com/questions/4959621/error-1001-in-cl...

Nope. Anything about this on the arch wiki? Nope

This bug report[2] from 2021? Maybe I need to update my groups.

[2]: https://github.com/RadeonOpenCompute/ROCm/issues/1411

    $ ls -la /dev/kfd

HMM is, I believe, a Linux feature.

AMD added HMM support in ROCm 5.0 according to this: https://github.com/RadeonOpenCompute/ROCm/blob/develop/CHANG...

Woot AMD now supports APU? I sold my notebook as i hit a wall when trying rocm [1] Is there a list oft Wirkung apu's ?

[1] https://github.com/RadeonOpenCompute/ROCm/issues/1587

Last I heard he's abandoned working with AMD products.

https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...

They're talking about the meltdown he had on stream [1] (in front of the mentioned pirate flag), that ended with him saying he'd stop using AMD hardware [2]. He recanted this two weeks after talking with AMD [3].

Maybe he'll succeed, but this definitely doesn't scream stability to me. I'd be wary of investing money into his ventures (but then I'm not a VC, so what do I know).

[1] https://www.youtube.com/watch?v=Mr0rWJhv9jU

[2] https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...

[3] https://twitter.com/realGeorgeHotz/status/166980346408248934...

As for rocm support on consumer devices, AMD wont even clarify what devices are supported. https://github.com/RadeonOpenCompute/ROCm/pull/1738

He flamed out, then is back after Lisa Su called him (lmao)

https://geohot.github.io/blog/jekyll/update/2023/05/24/the-t...

https://www.youtube.com/watch?v=Mr0rWJhv9jU

https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...

https://geohot.github.io/blog/jekyll/update/2023/06/07/a-div...

On a personal level that youtube doesn't make him come off looking that good... like people are trying to get patches to him and generally soothe him/damage control and he's just being a bit of a manchild. And it sounds like that's the general course of events around a lot of his "efforts".

On the other hand he's not wrong either, having this private build inside AMD and not even validating official, supported configurations for the officially supported non-private builds they show to the world isn't a good look, and that's just the very start of the problems around ROCm. AMD's OpenCL runtime was never stable or good either and every experience I've heard with it was "we spent so much time fighting AMD-specific runtime bugs and specs jank that what we ended up with was essentially vendor-proprietary anyway".

On the other other hand, it sounds like AMD know this is a mess and has some big stability/maturity improvements in the pipeline. It seems clear from some of the smoke coming out of the building that they're cooking on more general ROCm support for RDNA cards, and generally working to patch the maturity and stability issues he's talking about. I hate the "wait for drivers/new software release bro it's gonna fix everything" that surrounds AMD products but in this case I'm at least hopeful they seem to understand the problem, even if it's completely absurdly late.

Some of what he was viewing as "the process happening in secret" was likely people doing rush patches on the latest build to accommodate him, and he comes off as berating them over it. Again, like, that stream just comes off as "mercurial manchild" not coding genius. And everyone knew the driver situation is bad, that's why there's notionally alpha for him to realize here in the first place. He's bumping into moneymakers, and getting mad about it.

I tried to train another model using InceptionResNetV2 and the same issues happens. Also, this happens even using the model.predict() method if using the GPU. Probably this is an issue related to the AMD Radeon RX 6700 XT or some mine misconfiguration. System Inormation: ArchLinux 6.1.32-1-lts - AMD Radeon RX 6700 XT - gfx1031 Opened issues: - https://github.com/RadeonOpenCompute/ROCm/issues/2250 - https://github.com/ROCmSoftwarePlatform/tensorflow-upstream/issues/2125