step...

doc.zih.tu-dresden.de/docs/archive/hardware_overview_2022.md

@@ -31,7 +31,7 @@ users and the ZIH.
     - 3.5 TB local memory on NVMe device at `/tmp`
 - Hostnames: `taurusi[8001-8034]`
 - Slurm partition: `alpha`
-- Further information on the usage is documented on the site [Alpha Centauri Nodes](alpha_centauri.md)
+- Further information on the usage is documented on the site [Alpha Centauri Nodes](../jobs_and_resources/alpha_centauri.md)
 
 ## Island 7 - AMD Rome CPUs
 
@@ -41,7 +41,7 @@ users and the ZIH.
     - 200 GB local memory on SSD at `/tmp`
 - Hostnames: `taurusi[7001-7192]`
 - Slurm partition: `romeo`
-- Further information on the usage is documented on the site [AMD Rome Nodes](rome_nodes.md)
+- Further information on the usage is documented on the site [AMD Rome Nodes](../jobs_and_resources/rome_nodes.md)
 
 ## Large SMP System HPE Superdome Flex
 
@@ -53,7 +53,7 @@ users and the ZIH.
 - 370 TB of fast NVME storage available at `/nvme/<projectname>`
 - Hostname: `taurussmp8`
 - Slurm partition: `julia`
-- Further information on the usage is documented on the site [HPE Superdome Flex](sd_flex.md)
+- Further information on the usage is documented on the site [HPE Superdome Flex](../jobs_and_resources/sd_flex.md)
 
 ## IBM Power9 Nodes for Machine Learning
 

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

@@ -70,7 +70,7 @@ More information about profiling with Slurm:
 ## Memory Consumption of a Job
 
 If you are only interested in the maximal memory consumption of your job, you don't need profiling
-at all. This information can be retrieved from within [job files](slurm.md#batch-jobs) as follows:
+at all. This information can be retrieved from within [job files](../jobs_and_resources/slurm.md#batch-jobs) as follows:
 
 ```bash
 #!/bin/bash

doc.zih.tu-dresden.de/docs/index.md

@@ -31,6 +31,8 @@ Please also find out the other ways you could contribute in our
 
 ## News
 
+* **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)
 * **2022-01-13** [Supercomputing extension for TU Dresden](https://tu-dresden.de/zih/die-einrichtung/news/supercomputing-cluster-2022)
 

doc.zih.tu-dresden.de/docs/jobs_and_resources/architecture_2023.md

+# Architectural Redesign 2023
+
+With the replacement of the Taurus system by the cluster `Barnard`
\ No newline at end of file

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

@@ -44,7 +44,6 @@ software performance engineering or application performance engineering within s
 | [Perf](#perf-tools)  | Produce and visualize [profile](#profile)    | easy        | medium   | low       | (no)[^2]       |
 | [PIKA](#pika)        | Show performance [profile](#profile) and [trace](#trace) | very easy | low | very low | no         |
 | [Score-P](#score-p)  | Create performance [trace](#trace)           | complex     | high     | variable  | yes            |
-| [Slurm](#slurm-profiler) | Produce and visualize simple [trace](#trace)| easy     | low      | low       | no             |
 | [Vampir](#vampir)    | Visualize performance [trace](#trace)        | complex     | high     | n.a.      | n.a.           |
 
 [^2]: Re-compilation is not required. Yet, to obtain more details it is recommended to re-compile with the `-g` compiler option, which adds debugging information to the executable of an application.
@@ -248,18 +247,6 @@ Many raw data sources are supported by Score-P.
 It requires some time, training, and practice to fully benefit from the tool's features.
 See [Score-P](scorep.md) for further details.
 
-### Slurm Profiler
-
-!!! hint "Easy to use performance visualization of entire batch jobs"
-
-The [Slurm Profiler](../jobs_and_resources/slurm_profiling.md) gathers performance data from every
-task/node of a given [batch job](../jobs_and_resources/slurm.md).
-It records a coarse-grained [trace](#trace) for subsequent analysis.
-[Instrumentation](#instrumentation) of the applications under test is not needed.
-The data analysis of the given set of system metrics needs to be initiated by the user with a
-command line interface.
-The resulting performance metrics are accessible in a simple graphical front-end that provides
-time/performance graphs.
 
 ### Vampir
 

doc.zih.tu-dresden.de/mkdocs.yml

@@ -91,7 +91,6 @@ nav:
       - Produce Performance Overview with Perf: software/perf_tools.md
       - Track Slurm Jobs with PIKA: software/pika.md
       - Record Course of Events with Score-P: software/scorep.md
-      - Profile Jobs with Slurm: jobs_and_resources/slurm_profiling.md
       - Study Course of Events with Vampir: software/vampir.md
       - Measure Energy Consumption: software/energy_measurement.md
       - Compare System Performance with SPEChpc: software/spec.md
@@ -99,6 +98,8 @@ nav:
   - HPC Resources and Jobs:
     - Overview: jobs_and_resources/overview.md
     - HPC Resources:
+      - Overview: jobs_and_resources/hardware_overview.md
+      - Architecture 2023: jobs_and_resources/architecture_2023.md
       - AMD Rome Nodes: jobs_and_resources/rome_nodes.md
       - NVMe Storage: jobs_and_resources/nvme_storage.md
       - Alpha Centauri: jobs_and_resources/alpha_centauri.md
@@ -122,7 +123,7 @@ nav:
     - Platform LSF: archive/platform_lsf.md
     - BeeGFS Filesystem on Demand: archive/beegfs_on_demand.md
     - Jupyter Installation: archive/install_jupyter.md
-    - Job Profiling: jobs_and_resources/slurm_profiling.md
+    - Job Profiling: archive/slurm_profiling.md
     - Switched-Off Systems:
       - Overview 2022: archive/hardware_overview_2022.md
       - Overview: archive/systems_switched_off.md