Milepost GCC - Plugins

5:26 AM Nik 0 Comments

Here are some of the plugins that I have installed and a summary of what they do:
  • save_executed_passes.legacy
    This plugin saves the executed passes per function in external files
    "ici_passes_function.txt"
  • save_executed_passes_with_time.legacy
    This plugin times the execution of the passes split-compilation.
  • substitute-passes.legacy
    This plugin substitutes original GCC pass order with the one read from either external files "ici_passes_function.txt", 1 global file "ici_passes_all.txt" or environment variable ICI_PASSES_ALL (passes are separated by comma) thus allowing external manipulation with passes (adding, removing or reordering).
  • extract_program_static_features
    This plugin extracts program static features per function as vectors and saves them into "ici_features_function.txt"
The installation of these plugins was not very intuitive but I managed by tweaking the code here and there. The plugins are working fine now with GCC. The only problem I now face with Milepost is how to predict the optimization flags using the static program features which are extracted by the last plugin mentioned above. I believe (I may be wrong here) that we need to access the cDatabase and push our features in there, which then returns a set of optimization flags which can be used to compile with GCC. There are two ways to do this: using Web Services or using the CCC Framework (http://ctuning.org/wiki/index.php/CDatabase:Documentation:API). I have currently tried both but there are issues.

I cannot find a php script using which I can send a request to the "predict_opt" Web Service. Without this, its not possible to use the Web Service. The script for adding the optimization cases is available though.
With the CCC framework, I am unable to access the Web Service using sockets. This is the part where I am currently working. I have posted a request on the Discussions of the Community for making available the php script. Meanwhile, I'll try to get the CCC framework to work and return the predicted flags.

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