[llvm-dev] Suggestions on register allocation by using reinforcement learning

[Matthias Braun via llvm-dev]

> On Jan 9, 2018, at 6:31 AM, Tsung-Yu Hsieh via llvm-dev <llvm-dev at lists.llvm.org> wrote:
> 
> Hi everyone,
> 
> I'm quite new to LLVM and doing a  Q-learning  (just a hobby) on register allocation for LLVM. RegAllocRL is based on
> RegAllocBase, RegAllocBasic and add some feature to implement Q-learning algorithm. 
> I’ve currently run as MachineFunctionPass and things seem to work in simple case. In order to make progress on training, 
> I have questions and want to get some help:
> Is there any file data format used in LLVM to store information in each compilation step ? As I know, the Pass can not run several time in one compilation step, which means that I have to export data to file before compilation step finished and load from it in the next iteration. 
>  For training q-learning parameters, it would be necessary to run reg allocation pass several iterations to converge. Now, I train by compiling the target program once in each iteration and it will cost time. I wonder if I can train by  running the specific reg pass several time to optimize my parameters ?
We have the .mir file format to save/restore machine functions. See also http://llvm.org/docs/MIRLangRef.html <http://llvm.org/docs/MIRLangRef.html> so something like
llc -stop-before=greedy something.ll -o something.mir
llc -run-pass=greedy something.mir

should allow you to run the greedy allocator separately. Note though that the MIR serialization is only a 95% solution today and doesn't handle all programs (though it should be easy to extend/improve it, patches welcome :)

- Matthias

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