[ggreg84]

Chips and Cheese GPU analysis are pretty detailed, but they need to be taken with a huge grain of salt because the results only really apply to OpenCL and nobody buying NVIDIA or AMD GPUs for Compute runs OpenCL on them; its either CUDA or HIP, which differ widely in parts of their compilation stack.

After reading the entire analysis, I'm left wondering, what observations in this analysis - if any - actually apply to CUDA?

[nromiun]

For benchmarking code like this CUDA, HIP and OpenCL are almost the same. You will only see the difference in big codebases, where you launch multiple kernels and move data between them.

Otherwise OpenCL is very good as well, with the added benefit of running on all GPUs.

[almostgotcaught]

> its either CUDA or HIP, which differ widely in parts of their compilation stack.

This is an ironic comment - OpenCL uses the same compiler as CUDA on NVIDIA and HIP on AMD.

[JonChesterfield]

Sort of. Same compiler backend, mostly, but the set of intrinsics and semantic rules are different.

[almostgotcaught]

i have no idea what your point is - same compiler, different frontend, yes that's literally what i said.