Moses is a statistical machine translation system that allows you to automatically train translation models for any language pair. Intention of the project is to tune up existing software, where a glimpse shows that majority of time is consumed by memory allocation, dynamic casting and other calculation non-related stuff. I would like to inspect many techniques (like perf profiling, GCC LTO, GCC profile-guided optimization, code refactoring, OpenTuner, etc.) which may bring really significant performance gain. Moreover, it would be really beneficial to come up with a cookbook that can be used by folk in general. If possible, I would like to create a step-by-step performance improvement graphs.
Following Tizen and other internal initiatives, to have Factory complete or partially compiled with Address Sanitizer and give it openQA a try to "fuzz" it, looking for memory management issues:
about 3 years
3 hacker ♥️.
Has no hacker:
The goal is to use the work from the debug-early GCC branch to generate better debug information for LTO compiled objects,
especially with regarding to language specifics like classes and templates. This has now been achieved and openSUSE Factory
RPMlint upstream milestone 2.0 is shaping up but there are still ticket that needs to be tackled to finalize the release and enjoy the freshness of awesome QA on Tumbleweed/SLE16.
In this hackweek we plan to look on various problems as described at:
In previous hack weeks, the first few days ended up being wasted on just getting it working. I'm pleased to share that the code quality has improved dramatically since the last hack week and there are now extensive test cases for both unit testing and testing against real vmcores, and we'll use both mypy and pylint (if installed) to perform static analysis. Packages for those are available in openSUSE or as part of the crash-python OBS repo for SLE15. It has been tested with kernels from 3.0 to 5.1.