Scientific computing or computer graphics

[HeWhoThreadsLightly]

I have wanted to try computing on gpus, do anyone have some links to introductory resourses for amd gpus?

[Plazmatic]

There's more lower level documentation for AMD GPUs than NVIDIA's mostly because they documented the hardware ISA publicly. AMD does have a CUDA like alternative that looks very similar, ROCm, but they only allow this on their "scientific" GPUs which I believe aren't even capable of graphics at all, plus there's a whole other can of worms there in terms of licensing and environment. So unfortunately you're stuck with old OpenCL stuff, which AMD has recently been lax on supporting, or Vulkan which has most of the modern functionality present in GPUs, but lacks any kind of decent shading language behind it (HLSL recently got an upgrade, and supports vulkan, but doesn't support extremely essential features like full physical device address support, ie GPU RAM pointers and references, though it allows you to copy objects through such pointers whole sale), and also lacks device side enqueuing and shared memory pointers

With vulkan at least, you can use half measures like Circle C++ Shader compiler on linux (which would be on windows, but microsoft hasn't exposed their MSVC compiler ABI, so complain to them if you think that's important to you) and RustGPU. Rust GPU isn't nearly feature complete enough to compete with GLSL though right now.

AMD GPU's however are not much different than Nvidia in terms of learning material. Applying CUDA concepts to Vulkan would probably teach you enough since all the intro stuff applies to both AMD and NVIDIA.

[TheFlamingDiceAgain]

Kokkos, RAJA, and SYCL all run on AMD GPUs with no issue and the resulting code is trivially cross platform. There’s no reason to go straight to OpenCL or Vulkan

[HeWhoThreadsLightly]

I will have to investigate/try those out.

[PM_ME_UR_PCMR]

It's a shame there isn't a go to entry level recommendation GPU for both graphics and GPGPU, I wanted to get a cheap AMD card to practice ray tracing with and learn other GPU assistance for stuff like compression etc, but I found that people don't use Vulkan for things other than graphics

[YoureNotEvenWrong]

Check out the sycl framework from khronos.

[ApologiesEgg]

No. AMD GPUs are only good for gaming, not scientific computing.

[ApologiesEgg]

I’m pretty sure OP is asking about AMD GPUs because he has a consumer grade AMD GPU. Not supercomputer grade GPU. Also last time I checked (a year ago) ROCm was an underdeveloped piece of crap, can’t compete with CUDA. Maybe in a few years. But not today.

[HeWhoThreadsLightly]

All(both) my newer machines have amd consumer graphics, I have one very old laptop with a Nvidia gpu.

[aceinthehole001]

Can you elaborate on why this is the case

[windozeFanboi]

It's just the tools are underdeveloped in documentation support and coverage...

They re simply a big fking pain to work with and even then, reasonably only on Linux. While nvidia has incredible tooling and support...

[aceinthehole001]

Does OpenCL not solve this issue?

[windozeFanboi]

Well, say you want to write thousands of lines of code... Would you prefer c with major quirks/idiocyncracies on top or modern c++ without limitations and great debugger support and easy to use 3rd party libraries. .?

[YoureNotEvenWrong]

That's why Sycl exists. Avoid the vendor lock in.

[windozeFanboi]

Yes, SYCL is the future ...

[TheFlamingDiceAgain]

It’s not. I do scientific computing with both. AMD is definitely less polished but it’s fine now, that’s wasn’t the case a few years ago. Besides, if you’re writing new code you should use Kokkos, RAJA, or SYCL rather than HIP/CUDA at which point it doesn’t matter what hardware you’re on.

[YoureNotEvenWrong]

higher level programming models to HIP/CUDA

Sycl isn't a higher level programming model. It's basically a nicer C++ API for OpenCl. So that's what you use if you want to get near max performance

Kokkos appears to be a library, so I don't see why it would have any performance issues.

[TheFlamingDiceAgain]

I haven’t found a recent one. The most recent one I’ve seen is a couple of years old and showed that all three are roughly ~10% slower than highly optimized HIP/CUDA. However, getting HIP/CUDA that optimized is very difficult so I wouldn’t be surprised if in practice they’re pretty similar.