Aktualisieren doc.zih.tu-dresden.de/docs/jobs_and_resources/hardware_overview_2023.md

doc.zih.tu-dresden.de/docs/jobs_and_resources/hardware_overview_2023.md

@@ -27,3 +27,67 @@ All clusters have access to these shared parallel file systems:
 | `Weka` | `/weka` | 232 TB | 
 | `Home` | `/home` | 40 TB |
 
+## Barnard - Intel Sapphire Rapids CPUs
+
+- 630 nodes, each with
+    - 2 x Intel(R) Xeon(R) CPU E5-2680 v3 (12 cores) @ 2.50 GHz, Multithreading disabled
+    - 128 GB local memory on SSD
+- Varying amounts of main memory (selected automatically by the batch system for you according to
+  your job requirements)
+  * 594 nodes with 2.67 GB RAM per core (64 GB in total): `taurusi[6001-6540,6559-6612]`
+    - 18 nodes with 10.67 GB RAM per core (256 GB in total): `taurusi[6541-6558]`
+- Hostnames: `taurusi[6001-6612]`
+- Slurm Partition: `haswell`
+
+??? hint "Node topology"
+
+    ![Node topology](misc/i4000.png)
+    {: align=center}
+
+
+## AMD Rome CPUs + NVIDIA A100
+
+- 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: `taurusi[8001-8034]`
+- Slurm partition: `alpha`
+- Further information on the usage is documented on the site [Alpha Centauri Nodes](alpha_centauri.md)
+
+## Island 7 - 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: `taurusi[7001-7192]`
+- Slurm partition: `romeo`
+- Further information on the usage is documented on the site [AMD Rome Nodes](rome_nodes.md)
+
+## Large SMP System HPE Superdome Flex
+
+- 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: `taurussmp8`
+- Slurm partition: `julia`
+- Further information on the usage is documented on the site [HPE Superdome Flex](sd_flex.md)
+
+## IBM Power9 Nodes for Machine Learning
+
+For machine learning, we have IBM AC922 nodes installed with this configuration:
+
+- 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: `taurusml[1-32]`
+- Slurm partition: `ml`
+
+