[Mpi3-tools] New MPIT draft available / Question regarding Verbosity

[Martin Schulz]

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, schulzm at llnl.gov, http://people.llnl.gov/schulzm
CASC @ Lawrence Livermore National Laboratory, Livermore, USA