Remove systems overview (is in hardware overview page) and fix links

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

@@ -199,7 +199,7 @@ Pre-installed software on our HPC systems is managed via [modules](../software/m
 You can see the
 [list of software that's already installed and accessible via modules](https://gauss-allianz.de/de/application?organizations%5B0%5D=1200).
 However, there are many different variants of these modules available. Each cluster has its own set
-of installed modules, [depending on their purpose](doc.zih.tu-dresden.de/docs/software/.md)
+of installed modules, [depending on their purpose](../software/software.md).
 
 Specific modules can be found with:
 
@@ -207,80 +207,6 @@ Specific modules can be found with:
 marie@compute$ module spider <software_name>
 ```
 
-### Available Hardware
-
-ZIH provides a broad variety of compute resources ranging from normal server CPUs of different
-manufactures, large shared memory nodes, GPU-assisted nodes up to highly specialized resources for
-[Machine Learning](../software/machine_learning.md) and AI.
-
-## Barnard
-
-The cluster **Barnard** is a general purpose cluster by Bull. It is based on Intel Sapphire Rapids
-CPUs.
-
-- 630 diskless nodes, each with
-    - 2 x Intel Xeon Platinum 8470 (52 cores) @ 2.00 GHz, Multithreading enabled
-    - 512 GB RAM
-- Hostnames: `n[1001-1630].barnard.hpc.tu-dresden.de`
-- Login nodes: `login[1-4].barnard.hpc.tu-dresden.de`
-
-## Alpha Centauri
-
-The cluster **Alpha Centauri** (short: **Alpha**) by NEC provides AMD Rome CPUs and NVIDIA A100 GPUs
-and designed for AI and ML tasks.
-
-- 34 nodes, each with
-    - 8 x NVIDIA A100-SXM4 Tensor Core-GPUs
-    - 2 x AMD EPYC CPU 7352 (24 cores) @ 2.3 GHz, Multithreading available
-    - 1 TB RAM
-    - 3.5 TB local memory on NVMe device at `/tmp`
-- Hostnames: `i[8001-8037].alpha.hpc.tu-dresden.de`
-- Login nodes: `login[1-2].alpha.hpc.tu-dresden.de`
-- Further information on the usage is documented on the site [GPU Cluster Alpha Centauri](alpha_centauri.md)
-
-## Romeo
-
-The cluster **Romeo** is a general purpose cluster by NEC based on AMD Rome CPUs.
-
-- 192 nodes, each with
-    - 2 x AMD EPYC CPU 7702 (64 cores) @ 2.0 GHz, Multithreading available
-    - 512 GB RAM
-    - 200 GB local memory on SSD at `/tmp`
-- Hostnames: `i[7001-7190].romeo.hpc.tu-dresden.de` (after
-  [recabling phase](architecture_2023.md#migration-phase)])
-- Login nodes: `login[1-2].romeo.hpc.tu-dresden.de`
-- Further information on the usage is documented on the site [CPU Cluster Romeo](romeo.md)
-
-## Julia
-
-The cluster **Julia** is a large SMP (shared memory parallel) system by HPE based on Superdome Flex
-architecture.
-
-- 1 node, with
-    - 32 x Intel(R) Xeon(R) Platinum 8276M CPU @ 2.20 GHz (28 cores)
-    - 47 TB RAM
-- Configured as one single node
-- 48 TB RAM (usable: 47 TB - one TB is used for cache coherence protocols)
-- 370 TB of fast NVME storage available at `/nvme/<projectname>`
-- Hostname: `smp8.julia.hpc.tu-dresden.de` (after
-  [recabling phase](architecture_2023.md#migration-phase)])
-- Further information on the usage is documented on the site [SMP System Julia](julia.md)
-
-## Power
-
-The cluster **power** by IBM is based on Power9 CPUs and provides NVIDIA V100 GPUs.
-**power** is specifically designed for machine learning tasks.
-
-- 32 nodes, each with
-    - 2 x IBM Power9 CPU (2.80 GHz, 3.10 GHz boost, 22 cores)
-    - 256 GB RAM DDR4 2666 MHz
-    - 6 x NVIDIA VOLTA V100 with 32 GB HBM2
-    - NVLINK bandwidth 150 GB/s between GPUs and host
-- Hostnames: `ml[1-29].power9.hpc.tu-dresden.de` (after
-  [recabling phase](architecture_2023.md#migration-phase)])
-- Login nodes: `login[1-2].power9.hpc.tu-dresden.de`
-- Further information on the usage is documented on the site [GPU Cluster Power9](power9.md)
-
 ## Processing of Data for Input and Output
 
 Pre-processing and post-processing of the data is a crucial part for the majority of data-dependent