GCC 13 compilation errors due to missing headers
Users may encounter the following errors when compiling a C++ program with GCC 13:
error: 'uint64_t' in namespace 'std' does not name a type
or
Software
HCOLL-related failures in OpenMPI applications
Several applications using OpenMPI, including HDF5, Boost, Rmpi, ORCA, and CP2K, may fail with errors such as
mca_coll_hcoll_module_enable() coll_hcol: mca_coll_hcoll_save_coll_handlers failed
or
Caught signal 11: segmentation fault
We have identified that the issue is related to HCOLL (Hierarchical Collectives) being enabled in OpenMPI.
STAR-CCM+ MPI job failure and workaround
STAR-CCM+ encounters errors when running MPI jobs with Intel MPI or OpenMPI, displaying the following message:
ib_iface.c:1139 UCX ERROR Invalid active_speed on mlx5_0:1: 128
This issue occurs because the UCX library (v1.8) bundled with STAR-CCM+ only supports Mellanox InfiniBand EDR, while Mellanox InfiniBand NDR is used on Cardinal. As a result, STAR-CCM+ fails to correctly communicate over the newer fabric.
Affected versions
18.18.06.006, 19.04.009 and possibly later versions
Unavailability of intel channel among the conda channel list:
If you are getting an error:
UnavailableInvalidChannel: HTTP 403 FORBIDDEN for channel intel <https://conda.anaconda.org/intel> while creating a python environment or installing python packages, you can solve it by running the command
conda config --remove channels intel.
If you would like to use intel hosted packages for python environment, you can access them by running the following command
Compatibility Issues with NumPy 2.0
The newly released version of NumPy 2.0 includes substantial internal changes, including migrating code from C to C++. These modifications have led to significant issues with backwards compatibility, resulting in numerous breaking changes to both the Python and C APIs. As a consequence, packages built against NumPy 1.xx may encounter ImportError messages. To ensure compatibility, these packages must be rebuilt against NumPy 2.0.
Recommendation for Addressing the Issue:
Multi-node job hang with ORCA 5
You may experience a multi-node job hang if the job runs into a module that requires heavy I/O, e.g., MP2 or CCSD. Additionally, it potentially leads to our GPFS performance issue. We have identified the issue as related to the MPI I/O issue of OpenMPI 4.1. To remedy this, we will take the following procedures:
Possible job failures due to MPI library change on Pitzer after May 20
There are changes on MPI libraries on Pitzer after May 20. We will upgrade MOFED from 4.9 to 5.6 and recompile all OpenMPI and Mvapich2 against the newer MOFED version. Users with their own MPI libraries may see job failures and will need to rebuild their applications linked against the MPI libraries.
ORCA Bind to CORE Failure
The default CPU binding for ORCA jobs can fail sporadically. The failure is almost immediate and produces a cryptic error message, e.g.:
MPI_THREAD_MULTIPLE is not supported with OpenMPI-HPCX 4.x
A threading code with MPI where MPI_Init_thread uses MPI_THREAD_MULTIPLE will fail because UCX from HPCX package is built without enabling multi-threading. UCX is the default framework for OMPI 4.0 and above.
Affects versions
Owens: openmpi/4.0.3-hpcx, openmpi/4.1.2-hpcx, penmpi/4.1.4-hpcx
Ascend: openmpi/4.1.3
