- Darshan-users - mailman3.cels.anl.gov

Call for Contributions to the HPC I/O Archive Website
by Brinkmann, Prof. Dr. André 28 Aug '23

28 Aug '23

Dear Colleagues, We are pleased to announce the launch of the HPC I/O Archive website https://hpcioanalysis.zdv.uni-mainz.de/ and would like to invite you and your team to contribute traces and explore its online analysis capabilities. Core Purpose =========== At the intersection of AI/ML and HPC, the analysis of I/O patterns is critical for both application and storage optimization. Therefore, we are building a repository of Darshan-based I/O traces to foster interaction among system and storage researchers, developers, and application specialists from diverse scientific fields. Key Highlights ============ Analytics Hub: The website goes beyond storing traces and provides interactive graphs for comprehensive I/O analysis. Contextual Analysis: Our platform captures application I/O data and metadata, enabling comparisons of I/O traces across diverse HPC environments. Open Collaboration: Embracing the principles of open science, our framework simplifies trace submission and encourages cross-disciplinary interactions. Each trace gets its own DOI, so that traces can be individually referenced to recognize your efforts in collecting traces. Your active participation is critical to the success of the initiative. For details on how to contribute, please visit the “Getting Involved” section of our website. We would like to thank early contributors, such as those from the EuroHPC projects ADMIRE and IOSEA. We are also happy to thank the Darshan team for an exceptional collaboration, which is central to this project. We hope that you will benefit from using the HPC I/O Trace Archive and are looking forward to your feedback. Thank you and best regards, André Brinkmann (for the developer team)

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Darshan 3.4.4 now available
by Snyder, Shane 07 Aug '23

07 Aug '23

Darshan users, Darshan version 3.4.4 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: * Fixed bug leading to inconsistent heatmap record shapes when Darshan shared file reductions are disabled * Also added a darshan-util library fix to resolve this inconsistency on already impacted logs (any generated with 3.4.0+ versions of Darshan) * Added workaround for potential undefined symbol errors for 'H5FD_mpio_init' when LD_PRELOADing an HDF5-enabled runtime library * Bug triggered by 1.13+ versions of HDF5 We have also released PyDarshan 3.4.4.0 on PyPI, though this is just to track the 3.4.4 darshan-util library. There are no modifications to PyDarshan functionality. 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 this mailing list or by opening an issue on our GitHub: https://github.com/darshan-hpc/darshan. Thanks! --Darshan team

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Darshan 3.4.3 now available
by Snyder, Shane 13 Jun '23

13 Jun '23

Darshan users, 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 3.4.3.0 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 this mailing list, or by opening an issue on our GitHub: https://github.com/darshan-hpc/darshan. Thanks! --Darshan team

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Error: incompatible darshan file.
by Zoya Masih 09 Mar '23

09 Mar '23

Hello, I have installed Darshan version 3.4.1 on an HPC cluster and generated a log file without any problem. Then copied the log file to my own laptop, which has version 3.4.2 installed. When I do darshan-parser, I get the error message: Error: incompatible darshan file. Error: expected version 3.21, but got 3.41 Error: failed to read darshan log file header. (also the same problem with version 3.4.1 on my laptop). There is no error when I do a parser for log files of older version 3.3.1 Would you please guide me to understand the issue? Sincerely Zoya Masih

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no valid logfile in instrumenting io500
by Zoya Masih 31 Jan '23

31 Jan '23

Hi, I've configured darshan with * ./configure --with-log-path=/log/file/path --with-jobid-env=SLURM_JOB_ID --prefix=/bin/file/path --with-mod-mem=500 CC=mpicc* I get no error in installing the Darshan. Then In the app io500, I put *CC=/mpicc.darshan/file/path *in Makefile. In the file mpicc.darshan I wrote the output of the commands *mpicc --show and darshan-config --dyn-ld-flags (the content of the file is attached). * After a slurm job, an invalid log file is produced with the name *2023* which is empty. Please guide me in solving the problem, as it is so important to me and I do not have any other reference to refer to. Looking forward to hearing from you. Sincerely Zoya Masih

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join us on Slack
by Snyder, Shane 12 Jan '23

12 Jan '23

Darshan users, Follow the below invitation to join Darshan's new Slack workspace: https://join.slack.com/t/darshan-io/shared_invite/zt-1n6rhkqu8-waSQCVWYDrUp… We hope this workspace will provide another opportunity for the Darshan team and users to engage, whether it be about bug reports, usage questions, feature requests, project roadmap, etc. The Darshan team will also use this workspace to get user feedback on upcoming Darshan enhancements and other changes, as well as to announce new software releases. Hope to see you there! Thanks, --Darshan team

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Darshan 3.4.2 release is now available
by Snyder, Shane 16 Dec '22

16 Dec '22

Darshan users, Darshan version 3.4.2 is now officially available for download here: https://www.mcs.anl.gov/research/projects/darshan/download/. This point release includes important bug fixes for Darshan's new PnetCDF module: * Fixed segfault when defining scalar variables in PnetCDF module * Fixed bug attributing all PnetCDF variable instrumentation to the first variable instrumented * Fixed memory corruption (and potential segfault) when reading/writing high-dimensional PnetCDF variables using vara/vars/varm interfaces * Fixed crashes related to using PnetCDF vard interfaces with input MPI_DATATYPE_NULL datatypes Note that these bugs can only be triggered by the PnetCDF module released in Darshan version 3.4.1, which is disabled by default. There should be no impact on Darshan 3.4.1 configurations that did not explicitly enable PnetCDF instrumentation. We have also released PyDarshan 3.4.2.0 on PyPI, though this is just to track the 3.4.2 darshan-util library. There are no new modifications to PyDarshan functionality. 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 this mailing list, or by opening an issue on our GitHub: https://github.com/darshan-hpc/darshan. Thanks! --Darshan team

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Darshan 3.4.1 release is now available
by Snyder, Shane 02 Dec '22

02 Dec '22

Darshan users, Darshan version 3.4.1 is now officially available for download here: https://www.mcs.anl.gov/research/projects/darshan/download/. This release includes the following new features, bug fixes, etc.: * Added comprehensive instrumentation of PnetCDF APIs via PNETCDF_FILE and PNETCDF_VAR modules (contributed by Wei-Keng Liao) * disabled by default, enabled by passing `--enable-pnetcdf-mod` to configure * Modified Darshan log format to support a max of 64 instrumentation modules, since the current version of Darshan reached the old max (16) * Modified Darshan to report job start/end times at nanosecond granularity (previously only second granularity was possible) * Added support for instrumenting H5Oopen family of calls * Modified HDF5 module extraction of dataspace selection details * Extraction of point selections now possible regardless of HDF5 version * H5S_ALL selections are no longer counted as regular hyperslab accesses * Fixed bug causing no instrumentation of child processes of fork() calls (reported by Rui Wang) * Deprecated --file-list and --file-list-detailed options in darshan-parser * Added "darshan_accumulator" API to the logutils library * _create(), _inject(), _emit(), and _destroy() * generalizes the mechanism for producing summation records and derived metrics for sets of records from a given module * refactored darshan-parser to use new API * implemented support for accumulators in POSIX, STDIO, and MPIIO modules * Fixed memory leak in darshan-util helper functions used by PyDarshan * darshan_log_get_name_records * darshan_log_get_filtered_name_records * Integrated the µnit Testing Framework in darshan-util * implemented unit tests for darshan_accumlator API We have also released PyDarshan 3.4.1.0 on PyPI, which includes a number of improvements: * Fixed memory leaks in the following backend CFFI bindings (reported by Jesse Hines): * log_get_modules * log_get_mounts * log_get_record * log_get_name_records * log_lookup_name_records * Added PnetCDF module information to job summary tool * Testing modifications: * Switched to use of context managers for log Report objects to avoid test hangs in certain environments * Marked tests requiring lxml package as xfail when not installed 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 this mailing list, or by opening an issue on our GitHub: https://github.com/darshan-hpc/darshan. Thanks! --Darshan team

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missing "prepare" scripts in darshan-3.4.0
by Karrels, Edward 06 Sep '22

06 Sep '22

The 3.4.0 release build instructions say that before running configure it is necessary to run "./prepare" but the prepare scripts in darshan-runtime and darshan-util are missing. I saw the contents of the prepare script from 3.3.1 were pretty simple ("aclocal -I ../maint/config && autoheader && autoconf") so I tried running that in darshan-3.4.0/darshan-util, but then the configure command failed, complaining about missing install-sh. This is on Ubuntu 22.04, automake version 1.16.5. Here's the output from the aclocal, autoheader, and autoconf: $ aclocal -I ../maint/config && autoheader && autoconf configure.ac:40: warning: The macro `AC_LANG_C' is obsolete. configure.ac:40: You should run autoupdate. ./lib/autoconf/c.m4:72: AC_LANG_C is expanded from... ../maint/config/check_bzlib.m4:26: CHECK_BZLIB is expanded from... configure.ac:40: the top level configure.ac:97: warning: Checking for headers with the preprocessor is configure.ac:97: deprecated. Specify prerequisite code to AC_CHECK_HEADER configure.ac:97: instead of using fourth argument `-'. (Many headers need configure.ac:97: no prerequisites. If you truly need to test whether configure.ac:97: something passes the preprocessor but not the compiler, configure.ac:97: use AC_PREPROC_IFELSE.) ./lib/autoconf/headers.m4:115: _AC_CHECK_HEADER_PREPROC is expanded from... ./lib/autoconf/headers.m4:56: AC_CHECK_HEADER is expanded from... configure.ac:97: the top level configure.ac:108: warning: Checking for headers with the preprocessor is configure.ac:108: deprecated. Specify prerequisite code to AC_CHECK_HEADER configure.ac:108: instead of using fourth argument `-'. (Many headers need configure.ac:108: no prerequisites. If you truly need to test whether configure.ac:108: something passes the preprocessor but not the compiler, configure.ac:108: use AC_PREPROC_IFELSE.) ./lib/autoconf/headers.m4:115: _AC_CHECK_HEADER_PREPROC is expanded from... ./lib/autoconf/headers.m4:56: AC_CHECK_HEADER is expanded from... configure.ac:108: the top level Here's the output from configure: $ ./configure --prefix=$HOME/sw/darshan configure: error: cannot find required auxiliary files: compile missing install-sh

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Darshan 3.4.0 release is now available
by Snyder, Shane 21 Jul '22

21 Jul '22

Darshan users, Darshan version 3.4.0 is now officially available for download here: https://www.mcs.anl.gov/research/projects/darshan/download/. This release is a follow-up to our recent 3.4.0-pre1 pre-release, and we believe it is stable and ready for production use. In addition to features and bug fixes introduced in 3.4.0-pre1, this full release includes the following bug fixes to Darshan libraries/tools: * Fix segfault affecting new DARSHAN_MOD_DISABLE/ENABLE environment variables * Fix divide-by-zero condition that can potentially be triggered by new heatmap module * Fix potential MPI errors related to calling MPI_Type_size() on a user-supplied MPI_DATATYPE_NULL type (reported by Jim Edwards) * cuserid() is no longer the default method for determining username, and must be manually enabled at configure time * Fix backwards compatibility bug affecting darshan-3.0.0 logs in darshan-util C library functions used by PyDarshan * Suppress noisy output warnings when using darshan-job-summary.pl * Clarify units displayed by darshan-job-summary.pl (reported by Jeff Layton) We have also released PyDarshan 3.4.0.1 on PyPI, which includes a number of improvements: * New Darshan job summary report styling * HTML job summary reports can be generated using: python -m darshan summary <logfile_path> * Bug fix to heatmap module plotting code caused by logs with inactive ranks * Fix warnings related to Pandas deprecation of df.append 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 this mailing list, or by opening an issue on our GitHub: https://github.com/darshan-hpc/darshan Thanks! --Darshan team

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