[ET Trac] [Einstein Toolkit] #764: cached output in CarpetIOSCalar

Einstein Toolkit trac-noreply at einsteintoolkit.org
Sat Mar 3 12:23:02 CST 2012


#764: cached output in CarpetIOSCalar
--------------------------+-------------------------------------------------
  Reporter:  rhaas        |       Owner:  eschnett
      Type:  enhancement  |      Status:  review  
  Priority:  minor        |   Milestone:          
 Component:  Carpet       |     Version:          
Resolution:               |    Keywords:          
--------------------------+-------------------------------------------------

Comment (by rhaas):

 I really really detest this Spam filter. This is the second time I had to
 type my comments since the spam filter happily removed my posting and my
 browser (Opera) did not restore the text in the box.

 Using pointers instead of copying the cached_stream objects seems like a
 good idea.

 The number of file limit can be reached if we request scalar output for
 the majority of our grid functions. I have seen limits as low as 1024
 files per process (reachable with hdf5_slicer and HDF5 3D output from 576
 MPI processes).

 I order to avoid loss of data when the simulation fails any caching should
 flush its caches during checkpointing (I believe ther eis a bin for it).
 This way all currently cached data will be reproduced when the user
 recovers from the last checkpoint.

 I can easily change CarpetIOScalar's code (trunk version) to have
 different columns for the individual reductions. This is very
 straigthforward with the exception of the case where the requested
 reductions change during the run (where I would opt to output a second
 header with the column numbers). Note that this logic will fail if the
 user changes the requested reductions when recovering from a checkpoint
 (unless I track the parameter value out of the checkpoint and what is seen
 the next time the code is called, not sure though if the flesh lets me see
 the parameter values from the checkpoint).

-- 
Ticket URL: <https://trac.einsteintoolkit.org/ticket/764#comment:3>
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