llvm dev - Jan 2018 - Suggestions on register allocation by using reinforcement learning

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:*


   1. *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. *
   2.  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 ?


Since I'm new and this project is just experimental , I would appreciate
any help and comments. Thanks in advance!


https://github.com/Knight-X/llvm/blob/reg_ml/lib/CodeGen/RegAllocRL.h


-- 

Sincerely,

Tsung-yu Hsieh (Kazami)
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> 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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