Darshan 3.4.3 now available

Darshan version 3.4.3 is now officially available for download here: https://www.mcs.anl.gov/research/projects/darshan/download/. This point release includes a few minor bug fixes for darshan-runtime libraries:

  • Added new configure option ‘–with-username-env’ to allow specification of an env variable to use to find the username associated with a job (e.g., SLURM_JOB_USER)
  • Fixed bug causing crashes for applications that call fork() and use Darshan app exclusions settings
  • Fixed bug related to not closing open HDF5 file ID when instrumenting H5Fflush() calls

More notably, we have also released PyDarshan on PyPI, with this release including a number of improvements/changes to the log analysis package and corresponding tools:

  • PyDarshan job summary tool improvements:
    • Added new module overview table
    • Added new file count summary table
    • Added new plot of POSIX module sequential/consecutive accesses
    • Included PnetCDF `wait` time in I/O cost figures
    • Dropped default generation of DXT-based heatmaps and added a new cmdline option to force generate them (–enable_dxt_heatmap)
    • Dropped usage of scientific notation in “Data access by category” plot
    • Made captions, axis labels, and annotations clearer and easier to read
  • Integrated Python support for darshan-util accumulator API for aggregating file records and calculating derived metrics
    • Added backend routine `accumulate_records`, which returns a derived metric structure and a summary record for an input set of records
    • Added backend routine `_df_to_rec` to allow conversion of a DataFrame of records into raw byte arrays to pass into the darshan-util C library (e.g., for using accumulator API)
  • Fixed bug allowing binary wheel installs to prefer darshan-util libraries found in LD_LIBRARY_PATH
  • Fixed bug in DXT heatmap plotting code related to determining the job’s runtime
  • Updated docs for installation/usage of PyDarshan
  • Dropped support for Python 3.6

For reference, an example report generated by the updated PyDarshan job summary tool can be found here: https://www.mcs.anl.gov/research/projects/darshan/docs/e3sm_io_report.html.

Documentation for Darshan and PyDarshan is available here: https://www.mcs.anl.gov/research/projects/darshan/documentation/.

Please report any questions, issues, or concerns with this release using our mailing list, or by opening an issue on our GitHub: https://github.com/darshan-hpc/darshan.