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
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
