As you noted, polyhedral compilers work on a pretty restricted subset of programs, but are fairly impressive in what they do. There has been research on distributed code generation [1] as well as GPUs [2]. While there has been work on generalizing the model [3], I think the amount of parallelization that a compiler can do is still very limited by its ability to analyze the code (which is to say, highly restricted).
Then you've got a large class of data-parallel-ish constructs like Rayon [4] as well as executors which may work their way into the C++ standard at some point [5]. How much safety these provide depends greatly on the underlying language. Generally speaking, the constructs here are usually pretty restricted (think parallel map), but often you can write more-or-less arbitrary code inside, which is often not the case in the polyhedral compilers.
If you don't care so much about safety and just want access to every parallel programming construct under the sun, Chapel [6] may be interesting to you. There is no attempt here, as best I can tell, to offer any sort of safety guarantees, but maybe that's fine.
On the other end of the spectrum you have languages like Pony [7] that do very much care about safety, but (I assume, haven't looked deeply) this comes with tradeoffs in expressiveness.
(I work in this area too [8].)
Overall, there are some very stringent tradeoffs involved in parallelizing code and while it certainly has been and continues to be a very active area of research, there's only so much you can do to tackle fundamentally intractable analysis problems that pop up in the area of program parallelization.
[1]: https://www.csa.iisc.ac.in/~udayb/publications/uday-sc13.pdf
[2]: https://arxiv.org/pdf/1804.10694.pdf
[3]: https://inria.hal.science/file/index/docid/551087/filename/B...
[4]: https://docs.rs/rayon/latest/rayon/
[5]: https://github.com/NVIDIA/stdexec (disclaimer: I did a quick Google search on this, not 100% sure this is the best link)
