collaborative tuning of GCC optimization heuristic

[Grigori Fursin <grigori at dividiti dot com>]

Dear colleagues,

If it's of interest, we have released a new version of our open-source 
framework to share compiler optimization knowledge across diverse 
workloads and hardware. We would like to thank all the volunteers who 
ran this framework and shared some results for GCC 4.9 .. 6.0 in the 
public repository here: http://cTuning.org/crowdtuning-results-gcc

Here is a brief note how this framework for crowdtuning compiler 
optimization heuristics works (for more details, please see 
https://github.com/ctuning/ck/wiki/Crowdsource_Experiments): you just 
install a small Android app 
(https://play.google.com/store/apps/details?id=openscience.crowdsource.experiments) 
or python-based Collective Knowledge framework 
(http://github.com/ctuning/ck). This program sends system properties to 
a public server. The server compiles a random shared workload using some 
flag combinations that have been found to work well on similar machines, 
as well as some new random ones. The client executes the compiled 
workload several times to account for variability etc, and sends the 
results back to the server.

If a combination of compiler flags is found that improves performance 
over the combinations found so far, it gets reduced (by removing flags 
that do now affect the performance) and uploaded to a public repository. 
Importantly, if a combination significantly degrades performance for a 
particular workload, it gets recorded as well. This potentially points 
to a problem with optimization heuristics for a particular target, which 
may be worth investigating and improving.

At the moment, only global GCC compiler flags are exposed for 
collaborative optimization. Longer term, it can be useful to cover 
finer-grain transformation decisions (vectorization, unrolling, etc) via 
plugin interface. Please, note that this is a prototype framework and 
much more can be done! Please get in touch if you are interested to know 
more or contribute!

Take care,
Grigori

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Grigori Fursin, CTO, dividiti, UK