Neural network as a machine code performance optimizer in a compiler, is it possible and are there any examples?

Question

Neural networks

I am not deeply familiar with neural networks, search engines give me not what I am looking for. I am also not familiar with assembler and writing compilers, so I am interested in those who are advanced in this area and in the field of neural networks, of course. I will try to describe my question as clearly as possible.
Here's how I understand it in the classical sense:
there is some code in a high-level compiled language, which is translated into machine code by means of a compiler (translator), taking into account different optimizations for certain platforms. The compiler itself contains complex algorithms for optimizing the performance of the program and they are written by people. Is it possible to write such optimizations using trained n.nets?
That is, we have some code in a compiled language, which is optimized for performance using the N.net. Perhaps such a network will somehow operate with processor instructions for each platform and optimize them specifically.
Is such a program even possible? I'm sure I'm not the only one asking this question. Perhaps I do not have enough knowledge to understand that this is impossible (or possible but does not make sense). Please help me with this issue.
Thanks in advance for the answer to everyone and everyone in particular.

Answer 1

I would not use neural networks directly for code optimization, because the most important property of any compiler is that it should not change the behavior of the program.
In principle, neural networks can be used to predict which parts of the program are most loaded, as well as to analyze statistical data after profiling or benchmarks.
It is still far from being completely replaced by a programmer with a program, because you need to analyze a lot of different information