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• Write intermediate results and checkpoints as seldom as possible.
• Try to write/read larger data volumes (>1 MiB) and reduce the number of files concurrently managed in WORK.
• For inter-process communication use proper protocols (e.g. MPI) instead of files in WORK.
• If you want to control your jobs externally, consider to use POSIX signals, instead of using files frequently opened/read/closed by your program. You can send signals e.g. to batch jobs via "scancel --signal..."
• Use MPI-IO to coordinate your I/O instead of each MPI task doing individual POSIX I/O (HDF5 and netCDF may help you with this).
• Instead of using resursive chmod/chown/chgrp, please use as combination of lfs find and xargs, e.g. lfs find /path/to/folder|xargs chgrp $project, as this creates less stress on the metadataservers and is much faster

Analysis of meta data

An existing application can be investigated with respect to meta data usage. Let us assume an example job script for the parallel application myexample.bin with 16 MPI tasks.

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Once you add the linux command strace to the job you create two files per linux process (MPI task). For this example 32 trace files are created. Large MPI jobs can create a huge number of trace files, e.g. a 128 node job with 128 x 96 MPI tasks created 24576 files. For this investigation That is why we strongly recommend to reduce the MPI task number as far as possible. 

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For the interpretation of the trace file you need to expect a number of open entries originating from the linux system independent of independently from your code. The example code  myexample.bin creates only one file with the name mpiio_zxyblock.dat.  258 open statements in the trace file include only one open from the application which indicates a very desirable meta data activity.

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