[Mpi3-tools] New MPIT draft available / Question regarding Verbosity
Hi all, I uploaded a new draft of the MPIT proposal to https://svn.mpi-forum.org/trac/mpi-forum-web/wiki/MPI3Tools/draft Changes since the last draft are marked with changebars and are colored in green. The latest draft contains changes based on comments from Kathryn Mohror and the MPI group at Sun/Oracle. There is one open question that I would like to bring up for a general discussion: as discussed in the WG earlier, we need some kind of verbosity parameter that allows the MPI implementation to classify each variable according to its importance and general usage scenario. Jeff and I have been going forth and back on this one for a while over email, but we can't come to a useful conclusion and hence would like wider feedback. In general, we both think that we want 5 classes of verbosity (odd number larger than 3, but not too large). The original proposal had the following classes VERY_HIGH HIGH MEDIUM LOW VERY_LOW which was rejected by the forum (I think rightfully so) since it doesn't really convey any useful application level information. The current proposal has: USER_BASIC USER_DETAILED TUNER_BASIC TUNER_DETAILED MPI_IMPLEMENTOR with the idea that the first two classes are intended for general MPI users, the third and fourth for performance experts and system administrators wishing to tune the performance of MPI itself, while the fifth is for MPI implementors and would include debugging information. Open MPI uses a similar idea of verbosity and defines the following five classes: INFORMATION TRIVIAL MINOR MAJOR CRITICAL However, both Jeff and I don't like these classes, since they don't convey any useful information either. Jeff proposes something like BASIC ? ADVANCED ? INTERNAL but this proposal misses good names for 2 and 4. Any comments or suggestions (either extending one of the above or completely new) would be very much appreciated. Thanks, Martin ________________________________________________________________________ Martin Schulz, [email protected], http://people.llnl.gov/schulzm CASC @ Lawrence Livermore National Laboratory, Livermore, USA
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Martin Schulz