I think you are pretty precise and your comment is appreciated, so I think I need to clarify my wording as well. I think a lot of CUDA C/C++'s difficulties are self-inflicted because they conflate two things into what they call "kernels": runtime and shaders. Fundamentally, GPU programming for compute is easier than either graphics programming as well as CPU programming because you are limited on what you can do on the GPU, memory allocation is static because the matrix size doesn't really change dynamically during runtime and branching behaviors are generally to be avoided for GPU compute.

It's pretty heretical for me to say this, but a lot of GPU compute complexity that Nvidia is doing in CUDA is unnecessary and is by the simple fact that to do anything meaningful you have to either use their library or handle allocation/scheduling yourself. Imagine if JavaScript required you to handroll part of the V8/Node's JIT compiler, allocator and scheduler yourself every time you just want to make a webpage, that is essentially what CUDA is doing.

The actual "program" that runs on the GPU, the compute shaders in PTX/SPIR-V, are very low level but pretty straight forward once you get down to it.