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Merge branch 'preview' into merge-preview-in-main

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......@@ -31,6 +31,7 @@ Please also find out the other ways you could contribute in our
## News
* **2023-11-16** [OpenMPI 4.1.x - Workaround for MPI-IO Performance Loss](jobs_and_resources/mpi_issues/#openmpi-v41x-performance-loss-with-mpi-io-module-ompio)
* **2023-10-04** [User tests on Barnard](jobs_and_resources/barnard_test.md)
* **2023-06-01** [New hardware and complete re-design](jobs_and_resources/architecture_2023.md)
* **2023-01-04** [New hardware: NVIDIA Arm HPC Developer Kit](jobs_and_resources/arm_hpc_devkit.md)
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......@@ -21,7 +21,7 @@ computations, please use interactive jobs.
## Storage Systems
### Permananent Filesystems
### Permanent Filesystems
We now have `/home`, `/projects` and `/software` in a Lustre filesystem. Snapshots
and tape backup are configured. For convenience, we will make the old home available
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This pages holds known issues observed with MPI and concrete MPI implementations.
## OpenMPI v4.1.x - Performance Loss with MPI-IO-Module OMPIO
OpenMPI v4.1.x introduced a couple of major enhancements, e.g., the `OMPIO` module is now the
default module for MPI-IO on **all** filesystems incl. Lustre (cf.
[NEWS file in OpenMPI source code](https://raw.githubusercontent.com/open-mpi/ompi/v4.1.x/NEWS)).
Prior to this, `ROMIO` was the default MPI-IO module for Lustre.
Colleagues of ZIH have found that some MPI-IO access patterns suffer a significant performance loss
using `OMPIO` as MPI-IO module with OpenMPI/4.1.x modules on ZIH systems. At the moment, the root
cause is unclear and needs further investigation.
**A workaround** for this performance loss is to use "old", i.e., `ROMIO` MPI-IO-module. This
is achieved by setting the environment variable `OMPI_MCA_io` before executing the application as
follows
```console
export OMPI_MCA_io=^ompio
srun ...
```
or setting the option as argument, in case you invoke `mpirun` directly
```console
mpirun --mca io ^ompio ...
```
## Mpirun on partition `alpha`and `ml`
Using `mpirun` on partitions `alpha` and `ml` leads to wrong resource distribution when more than
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