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

doc.zih.tu-dresden.de/docs/archive/system_taurus.md

@@ -37,7 +37,7 @@ users and the ZIH.
 ## Island 2 Phase 2 - Intel Haswell CPUs + NVIDIA K80 GPUs
 
 - 64 nodes, each with
-    - 2 x Intel(R) Xeon(R) CPU E5-E5-2680 v3 (12 cores) @ 2.50 GHz, Multithreading disabled
+    - 2 x Intel(R) Xeon(R) CPU E5-2680 v3 (12 cores) @ 2.50 GHz, Multithreading disabled
     - 64 GB RAM (2.67 GB per core)
     - 128 GB local memory on SSD
     - 4 x NVIDIA Tesla K80 (12 GB GDDR RAM) GPUs

doc.zih.tu-dresden.de/docs/software/gpu_programming.md

@@ -4,7 +4,25 @@
 
 The full hardware specifications of the GPU-compute nodes may be found in the
 [HPC Resources](../jobs_and_resources/hardware_overview.md#hpc-resources) page.
-Each node uses a different modules(modules.md#module-environments):
+Note that the clusters may have different [modules](modules.md#module-environments) available:
+
+E.g. the available CUDA versions can be listed with
+
+```bash
+marie@compute$ module spider CUDA
+```
+
+Note that some modules use a specific CUDA version which is visible in the module name,
+e.g. `GDRCopy/2.1-CUDA-11.1.1` or `Horovod/0.28.1-CUDA-11.7.0-TensorFlow-2.11.0`.
+
+This especially applies to the optimized CUDA libraries like `cuDNN`, `NCCL` and `magma`.
+
+!!! important "CUDA-aware MPI"
+
+    When running CUDA applications using MPI for interprocess communication you need to additionally load the modules
+    that enable CUDA-aware MPI which may provide improved performance.
+    Those are `UCX-CUDA` and `UCC-CUDA` which supplement the `UCX` and `UCC` modules respectively.
+    Some modules, like `NCCL`, load those automatically.
 
 ## Using GPUs with Slurm