So it's important that vendors don't feel let off the hook to provide sane packaging just because there's an option to use a kitchen-sink container image they rebuild every day from source.
https://github.com/RadeonOpenCompute/ROCm-docker/blob/master...
They also have some for Fedora. Looks like for this you need to install their repo:
curl -sL https://repo.radeon.com/rocm/rocm.gpg.key | apt-key add - \
&& printf "deb [arch=amd64] https://repo.radeon.com/rocm/apt/$ROCM_VERSION/ jammy main" | tee /etc/apt/sources.list.d/rocm.list \
&& printf "deb [arch=amd64] https://repo.radeon.com/amdgpu/$AMDGPU_VERSION/ubuntu jammy main" | tee /etc/apt/sources.list.d/amdgpu.list \
So they are doing the packaging. There might even be documentation elsewhere for that type of setup.
I think my issue is more just with the mindset that it's okay to have one narrow slice of supported versions of everything that are "known to work together" and those are what's in the container and anything outside of those and you're immediately pooched.
This is not hypothetical btw, I've run into real problems around it with libraries like gproto, where tensorflow's bazel build pulls in an exact version that's different from the default one in nixpkgs, and now you get symbol conflicts when something tries to link to the tensorflow c++ API while linking to another component already using the default gproto. I know these problems are solveable with symbol visibility control and whatever, but that stuff is far from universal and hard to get right, especially if the person setting up the build rules for the library doesn't themselves use it in that type of heterogeneous environment (like, everyone at Google just links the same global proto version from the monorepo so it doesn't matter).
You need to ensure that there is only one version of any library used globally throughout the code and that the set of versions is compatible with each other, and preferably you also want everything to be built against the same toolchain with the same flags.
That usually means onboarding third-party libraries into your own build system.
Also, just to name it, it’s ridiculous that a specific graphics card manages to restrict the version of gproto that you’re using. You don’t have this problem with nvidia drivers, since cuda stuff is much less fiddly. AMD needs to pull a finger out and fix the bugs in their stack that make it so fragile like this.
Wanting to hold Python+C ecosystem more accountable is fair I think, at least from my own experience around half a year ago, Anaconda doesn't work and you need a Dockerfile for any sort of reproducibility, which can have issues since GPU with docker isn't that easy. And this means developers from the vendors working with Anaconda, for example, on solving the issue rather than just hoping for contributors to do it. If AMD were to make easy, reproducible builds without root or VM a reality, that would be reason enough to try their hardware. If not, hopefully Nvidia does and then there really would be no way across the moat for me at least.
A docker container is not really any different from any other process; the main difference is that it runs in a chroot pretty much.
But that has nothing to do with semver.
Semver gives you information about when when you can replace one version with another version. It doesn't promise that you can mix multiple versions together.
And you are mixing multiple versions if you are building against version x.y and linking against version x.(y+z).
If linking against a different version of the code breaks like that, that sounds like someone did semver wrong. If that happens a lot to you, then oh, I'm sorry about that happening.
Or rather, I install no versions of libraries because NixOS will put them all in the store in different folders, and will compile the executable to use the correct path (or patch the elf when needed)
it has an issue with pip because it's allergic to just randomly executing things as part of package management, but pip in general is wtf
Well, except for cuda. Which is a massive pile of proprietary software that people are using in production anyway.
I hear you. I think docker has been a plague on the quality of software. It's allowed "works for me" to become the norm, except it's now pronounced "works on the official docker image". It seems to be especially true in the ML sphere where compiling things is so temperamental that there's a lot of binaries being distributed.
Docker was meant to be a deployment platform, not a distribution medium.
Heh, if only. When working with F100's I've seen many terrible, terrible things.
Sadly if e.g. 95% of their users can use the container, then it could make economical sense to do it that way.
is this a real problem? exactly which embedded platform has a device that ROCm supports?
that's not embedded dev. if you
1. use underpowered devices to perform sophisticated tasks
2. using code/tools that operate at extremely high levels of "abstraction"
don't be surprised when all the inherent complexity is tamed using just more layers of "abstraction". if that becomes a problem for your cost/power/space budget then reconsider choice 1 or choice 2.
yes and in those instances you do not reach for pytorch/tensorflow on top of ubuntu on top of x86 with a discrete gpu and 32gb of ram. instead you reach for C and micro or some arm soc that supports baremetal or at most rtos. that's embedded dev.
so i'll repeat myself: if you want to run extremely high-level code then don't be "surprised pikachu" when your underpowered platform, that you chose due to concrete, tight budgets doesn't work out.
However, containers or Ubuntu Linux don’t perform great in that environment. Ubuntu is for desktops, containers are for cloud data centers. An offline stand-alone device is different. BTW, end users don’t typically aware that thing is a computer at all.
Personally, I usually pick Alpine or Debian Linux for similar use cases, bare metal i.e. without any containers.
Or at least you have some case as heaven never come. Or come just we do not aware now like internet. Can you need to use ibm to rub sna to provide a token ring based network. In 1980 …
Imagine and let us or they competite …
Tell that to their (much larger, more profitable, and better-funded) server org. This is far from true.
On Desktop you have to worry about things like... UIs, sound, Wine, etc.
X86 cannot do 64 bit let us do this and that so the market can use only our cpu. Repeat with me x86-64 is impossible.
Not sure Apple is in this otherwise the real great competition come.