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

[Tsung-Yu Hsieh via llvm-dev]

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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