Feral VS Thrust

I have been working on my own VM (and language) as well and I decided to have only a small set of instructions that I wanted. I finalized on ~25 instructions. You can check them out here - https://github.com/Feral-Lang/Feral/blob/master/include/VM/OpCodes.hpp

this is frankly starting to sound a lot like the ridiculous "blue bubbles" discourse.

AMD's products have generally failed to catch traction because their implementations are halfassed and buggy and incomplete (despite promising more features, these are often paper features or career-oriented development from now-departed developers). all of the same "developer B" stuff from openGL really applies to openCL as well.

http://richg42.blogspot.com/2014/05/the-truth-on-opengl-driv...

AMD has left a trail of abandoned code and disappointed developers in their wake. These two repos are the same thing for AMD's ecosystem and NVIDIA's ecosystem, how do you think the support story compares?

https://github.com/HSA-Libraries/Bolt

https://github.com/NVIDIA/thrust

in the last few years they have (once again) dumped everything and started over, ROCm supported essentially no consumer cards and rotated support rapidly even in the CDNA world. It offers no binary compatibility support story, it has to be compiled for specific chips within a generation, not even just "RDNA3" but "Navi 31 specifically". Etc etc. And nobody with consumer cards could access it until like, six months ago, and that still is only on windows, consumer cards are not even supported on linux (!).

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

This is on top of the actual problems that still remain, as geohot found out. Installing ROCm is a several-hour process that will involve debugging the platform just to get it to install, and then you will probably find that the actual code demos segfault when you run them.

AMD's development processes are not really open, and actual development is silo'd inside the company with quarterly code dumps outside. The current code is not guaranteed to run on the actual driver itself, they do not test it even in the supported configurations.

it hasn't got traction because it's a low-quality product and nobody can even access it and run it anyway.

For a higher level GPU interface, Thrust provides "standard library"-like functions that run in parallel on the GPU (Nvidia only)

For GPGPU, I like thrust. C++-idiomatic way of writing CUDA code, passing between host and device, etc.

Users should work with higher level primitives like tasks, parallel loops, asynchronous functions etc. Think TBB, Thrust, Taskflow, lparallel for CL, etc.