Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

PyTorch 1.8, with AMD ROCm support

github.com

Post reply on HN
Print view View original

41–50 of 147 posts

Re: PyTorch 1.8, with AMD ROCm support

#41

Post by dheera »

my123 wrote: post #31
NavinF wrote: post #14

Earlier quoted context omitted.

Are there any If it exists, I wanna buy it

Jetson Xavier NX, but that comes with a high price tag. It’s much more powerful however.

I'll also add a caveat that toolage for Jetson boards is extremely incomplete.

They supply you with a bunch of sorely outdated models for TensorRT like Inceptionv3 and SSD-MobileNetv2 and VGG-16. WTF, it's 2021. If you want to use anything remotely state-of-the-art like EfficientDet or HRNet or Deeplab or whatever you're left in the dark.

Yes you can run TensorFlow or PyTorch (thankfully they give you wheels for those now; before you had to google "How to install TensorFlow on Jetson" and wade through hundreds of forum pages) but they're not as fast at inference.

Re: PyTorch 1.8, with AMD ROCm support

#42

Post by etaioinshrdlu »

rfoo wrote: post #36
etaioinshrdlu wrote: post #15

Earlier quoted context omitted.

Tensorflow doesn't seem to officially support ROCm, only unofficial community projects do. This is official support from PyTorch.

Tensorflow does officially support ROCm. The project was started by AMD and later upstreamed. https://github.com/tensorflow/tensorflow/tree/master/tensorf... https://github.com/tensorflow/tensorflow/blob/master/tensorf... It is true that it is not Google who are distributing binaries compiled with ROCm support through PyPI (tensorflow and tensorflow-gpu is uploaded by Google, but tensorflow-rocm is uploaded by AMD).…

Oh, interesting. I do wonder if Google puts the same quality control and testing into the Rocm version, though. Otherwise it would really be a lower tier of official support.

Granted, I don't know anything about the quality of PyTorch's support either.

Re: PyTorch 1.8, with AMD ROCm support

#43

Post by mcdevilkiller »

slavik81 wrote: post #26
mastazi wrote: post #8

Now that major frameworks finally started supporting ROCm, AMD has half-abandoned it (IIRC the last consumer cards supported were the Vega ones, cards from 2 generations ago). I hope this will change.

I work for AMD, but this comment contains exclusively my personal opinions and information that is publicly available. ROCm has not been abandoned. PyTorch is built on top of rocBLAS, rocFFT, and Tensile (among other libraries) which are all under active development. You can watch the commits roll in day-by-day on their public GitHub repositories. I can't speak about hardware support beyond what's written in the docs…

Yes, you can ask bridgmanAMD on Reddit.

Re: PyTorch 1.8, with AMD ROCm support

#44

Post by std_badalloc »

PyTorch is the most impressive piece of software engineering that I know of. So yeah, it's a nice interface for writing fast numerical code. And for zero effort you can change between running on CPUs, GPUs and TPUs. There's some compiler functionality in there for kernel fusing and more. Oh, and you can autodiff everything. There's just an incredible amount of complexity being hidden behind behind a very simple interface there, and it just continues to impress me how they've been able to get this so right.

Re: PyTorch 1.8, with AMD ROCm support

#45

Post by slavik81 »

beagle3 wrote: post #27
slavik81 wrote: post #26

Earlier quoted context omitted.

I work for AMD, but this comment contains exclusively my personal opinions and information that is publicly available. ROCm has not been abandoned. PyTorch is built on top of rocBLAS, rocFFT, and Tensile (among other libraries) which are all under active development. You can watch the commits roll in day-by-day on their public GitHub repositories. I can't speak about hardware support beyond what's written in the docs…

Can you comment perhaps on what you guys have compared to nVidia’s DGX? I’d rather buy a workhorse with open drivers.

The MI100 is our server compute product. The marketing page is probably a better source of information than I am: https://www.amd.com/en/products/server-accelerators/instinct...

Re: PyTorch 1.8, with AMD ROCm support

#46

Post by my123 »

dheera wrote: post #41
my123 wrote: post #31

Earlier quoted context omitted.

Jetson Xavier NX, but that comes with a high price tag. It’s much more powerful however.

I'll also add a caveat that toolage for Jetson boards is extremely incomplete. They supply you with a bunch of sorely outdated models for TensorRT like Inceptionv3 and SSD-MobileNetv2 and VGG-16. WTF, it's 2021. If you want to use anything remotely state-of-the-art like EfficientDet or HRNet or Deeplab or whatever you're left in the dark. Yes you can run TensorFlow or PyTorch (thankfully they give you wheels for thos…

You have https://github.com/NVIDIA-AI-IOT/torch2trt as an option for example to use your own models on TensorRT just fine.

And https://github.com/tensorflow/tensorrt for TF-TRT integration.

Re: PyTorch 1.8, with AMD ROCm support

#47

Post by sjwright »

ipsum2 wrote: post #33
upbeat_general wrote: post #30

Earlier quoted context omitted.

I don’t understand this logic. If someone has $1000 for an entry level m1 machine then they also have enough money for a separate rig with a GPU that’s probably another $600-1000 for something decent? Cloud GPUs are also pretty expensive. I don’t think anyone is seriously training their ML models on their ultra thin laptop but I think the ability to do so would make it easier for lots of people to get started with wh…

If someone is shelling out for a brand new, early adopter product, then they probably have a decent amount of money. Even when TensorFlow and PyTorch implement training support on the M1, it will be useless for practically anything except training 2-3 layer models on MNIST. So why should valuable engineering time be spent on this?

I think you underestimate just how many MacBooks Apple sells. There’s only so many affluent early adopters out there. And the M1 MacBooks are especially ideal for mainstream customers.

Re: PyTorch 1.8, with AMD ROCm support

#48

Post by jiehong »

Dylan16807 wrote: post #11
porphyra wrote: post #4

Earlier quoted context omitted.

Lack of ROCm support in consumer RDNA 2 GPUs really makes it impossible for regular people to use ROCm. As an owner of an AMD Radeon RX 6800 I'm pretty salty about it.

At least they promised support. They're actively refusing to comment on 5000-series.

Indeed. Yet, the amdgpu-pro driver supports the 5000 series.

I managed to get it to work for my 5500 XT, but only in Ubuntu and for the 5.4 kernel and it wasn’t straightforward.

It would be nice if a project like Mesa would exist for OpenCL.

In the future, I suppose Vulkan will be used instead for compute though.

Re: PyTorch 1.8, with AMD ROCm support

#49

Post by the8472 »

dogma1138 wrote: post #29
mastazi wrote: post #8

Now that major frameworks finally started supporting ROCm, AMD has half-abandoned it (IIRC the last consumer cards supported were the Vega ones, cards from 2 generations ago). I hope this will change.

It’s worse.... It’s Linux only so no Mac, Windows or WSL. No support what so ever for APUs which means if you have a laptop without a dedicated GPU you’re out of luck (tho discrete mobile GPUs aren’t officially supported either and often do not work). They’ve not only haven’t been supporting any of their consumer based R“we promise it’s not GCN this time”DNA GPUs, but since December last year (2020) they’ve dropped s…

> or WSL

Does WSL not support PCIe passthrough?

Re: PyTorch 1.8, with AMD ROCm support

#50

Post by geek_at »

NavinF wrote: post #14
rfoo wrote: post #9

Earlier quoted context omitted.

I believe TensorFlow is a top-tier deep learning framework, and it had ROCm support since 2018. > edge TPU's are absolutely top-notch for performance per $ and Watt right now Do you mean "aren't"? The performance per $ and Watt is not awesome even when it was released, I was hoping for great toolchain support but that also didn't happen.

Are there any If it exists, I wanna buy it

I used the Intel neural compute sticks [1] for my porn detection service [2] and they worked great. Could import and run models on a Pi with ease

[1] https://blog.haschek.at/2018/fight-child-pornography-with-ra... [2] https://nsfw-categorize.it/

Post reply on HN