I'd like to extend my skill set into GPU computing. I am familiar with raytracing and realtime graphics(OpenGL), but the next generation of graphics and high performance computing seems to be in GPU computing or something like it.
I currently use an AMD HD 7870 graphics card on my home computer. Could I write CUDA code for this? (my intuition is no, but since Nvidia released the compiler binaries I might be wrong).
A second more general question is, Where do I start with GPU computing? I'm certain this is an often asked question, but the best I saw was from 08' and I figure the field has changed quite a bit since then.
Yup. :) You can use Hipify to convert CUDA code very easily to HIP code which can be compiled run on both AMD and nVidia hardware pretty good. Here are some links
GPUOpen very cool site by AMD that has tons of tools and software libraries to help with different aspects of GPU computing many of which work on both platforms
HIP Github Repository that shows the process to hipify
HIP GPUOpen Blog
You can run NVIDIA® CUDA™ code on Mac, and indeed on OpenCL 1.2 GPUs in general, using Coriander . Disclosure: I'm the author. Example usage:
Result:
I think it is going to be possible soon in AMD FirePro GPU's, see press release here but support is coming 2016 Q1 for the developing tools:
Nope, you can't use CUDA for that. CUDA is limited to NVIDIA hardware. OpenCL would be the best alternative.
Khronos itself has a list of resources. As does the StreamComputing.eu website. For your AMD specific resources, you might want to have a look at AMD's APP SDK page.
Note that at this time there are several initiatives to translate/cross-compile CUDA to different languages and APIs. One such an example is HIP. Note however that this still does not mean that CUDA runs on AMD GPUs.
You can't use CUDA for GPU Programming as CUDA is supported by NVIDIA devices only. If you want to learn GPU Computing I would suggest you to start CUDA and OpenCL simultaneously. That would be very much beneficial for you.. Talking about CUDA, you can use mCUDA. It doesn't require NVIDIA's GPU..