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services:cluster:start [2024/07/01 11:39] – [Table] zedvservices:cluster:start [2025/07/21 10:50] (current) hoffmac00
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 ====== Information about the HPC-Cluster ====== ====== Information about the HPC-Cluster ======
  
-<note tip>If you have questions, you can find us on [[https://meet.physik.fu-berlin.de/#/room/!lwzXdWYwaTwKKSKfAb:physik.fu-berlin.de?via=physik.fu-berlin.de|Matrix in #hpc:physik.fu-berlin.de]]</note>+<note tip>If you have questions, you can find us on [[https://meet.physik.fu-berlin.de/#/room/#hpc:physik.fu-berlin.de|Matrix in #hpc:physik.fu-berlin.de]]</note>
  
 ===== Access to the Cluster ===== ===== Access to the Cluster =====
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   - Your ZEDAT account username   - Your ZEDAT account username
-  - The group you are using the system for (e.g. ag-netz,ag-imhof,...+  - The group you are using the system for (e.g. AG NetzAG EisertAG Franke…
-  - The software you are using for your simulations (e.g. gromacs, gaussian, self-written code in language XYZ, ...) and whether you use MPI or OpenCL/CUDA.+  - The software you are using for your numerics (e.g. externally developed software like GROMACS or Gaussianor self-written code in language PythonFortran, Julia or C)Also let us know if you have any special needs, e.gif you use any MPI, GPU offloading (OpenCL/CUDA/Vulkan Compute), or need special compiler toolchains.
   - Software that you happen to know so well that other HPC users within the department may ask you for help.   - Software that you happen to know so well that other HPC users within the department may ask you for help.
-  - A self-contained example job that is typical for the workload you will be using the HPC systems for, ideally **with a small README** describing how to run it **and a job script**. If possible scale it so it runs between a few minutes and an hour at maximum+  - A self-contained example job that is typical for the workload you will be using the HPC systems for. 
-  - If you are no longer a member of the physics department, we would like to get an estimate on how much longer you will need access to the systems (e.g. to finish some paper)+  - If you are no longer a member of the physics department, we would like to get an estimate on how much longer you will need access to the systems (e.g. to finish some paper).
  
 +The example must contain:
 +
 +  - A small README  describing how to run (and if necessary build) the example,
 +  - a Slurm job script, and
 +  - the program that is run in the example and/or all input files needed to run it, this includes data files and definitions for the environment the job is to run in (e.g. a ''requirements.txt'' for a Python virtual environment) or that is needed to build the software (e.g. a ''cargo.lock''). 
 +
 +If possible:
 +
 +  - The example should have an option to scale it so it runs between a few minutes and an hour at maximum, so that it can be used for benchmarking.
 +
 +If you can't answer the questions for your example, these steps can help you answer them
 +
 +  - If you have written the code yourself, what dependecies does it have (e.g. Python libraries you import)?
 +  - How long does your example run?
 +  - How many CPUs and how much memory does the example need?
 +  - Can the  example's runtime be made to scale, preferably by changing a single parameter?
 ===== Slurm documentation ===== ===== Slurm documentation =====
  
-  * [[important|Important notes]] on cluster usage+Read this for an introduction to Slurm queuing system, if you haven't used an HPC cluster before and want to learn the workflow:  
   * Start with the [[slurm|Introduction to the Slurm HPC cluster]].   * Start with the [[slurm|Introduction to the Slurm HPC cluster]].
 +
 +Read this for some important notes on the specifics of our clusters.
 +
 +  * [[important|Important notes]] on cluster usage
 +
 +These are more specialised topics:
 +
   * Using [[interactivesessions|interactive sessions]] with the queuing system.   * Using [[interactivesessions|interactive sessions]] with the queuing system.
-  * How to make use of the [[gpunodes|GPU-nodes]]. 
   * Here is a [[nodes|list of special nodes]] that are currently not part of slurm.   * Here is a [[nodes|list of special nodes]] that are currently not part of slurm.
   * Here is a [[userlist|list of HPC users]] and the software they use   * Here is a [[userlist|list of HPC users]] and the software they use
- 
-===== General documentation ===== 
- 
-  * Robert Hübener from AG-Eisert has written a HOWTO for using [[mmacluster|Mathematica on a HPC-Cluster]]. 
-  * A more current Python version has been built for cluster usage. The [[pythoncluster|Python on the HPC-Cluster]] tutorial describes how to set it up. 
  
 ===== Overview of available resources ===== ===== Overview of available resources =====
  
-The following table lists some HPC resources available at the physics department. The tron cluster at Takustrasse 9 is currently restructured. We also have some [[nodes|special purpose nodes]] that are currently not managed by Slurm.+The following table lists some HPC resources available at the physics department. The tron cluster at Takustraße 9 is currently being restructured. We also have some [[nodes|special purpose nodes]] that are not managed by Slurm.
  
-The name of the login node for each of our clusters has the same name as the cluster, e.g. the tron login node is reachable via ssh under the hostname ''tron''.+The name of the login node for each of our clusters has the same name as the cluster, e.g. the sheldon login node is reachable via ssh under the hostname ''sheldon.physik.fu-berlin.de'' (or just ''sheldon'' inside the department).
  
-^ Hosts                                                                              ^ Manager  ^ Nodes                                       Form                                 ^ Hardware                ^ CPU                ^ Speed   ^ Core/Node   RAM/Core ^ RAM/Node   #RAM                                         #Cores                                      +^ Hosts ^ Nodes ^ Cores/Node ^ RAM/Core ^ RAM/Node ^ CPU features ^ GPU ^ on-GPU RAM ^ #Cores ^ #RAM ^ #GPU 
-| @#cfc:**tron cluster** - FB Physik - Location: Takustrasse 9 - OS: Debian/Stretch                                                                                                                                                                                                                                                                                   |||||||||||| +| @#cfc:** sheldon-ng cluster** - FB Physik - Location: Takustraße 7 - OS: Debian/Bookworm ||||||||||| 
-| @#cfc:z001-z020                                                                    SLURM                                             20 1U                                   IBM iDataPlex dx360 M4  2x Xeon E5-2680v2  2.8GHz  |  20         25G       512G                                           10024G |  400                                         +| @#cfc:x[001-016,049-160] 128 24 5.2GB 125GB x86-64-v2 |  |  | 3072 16000GB 
-| @#cfc:z021-z040                                                                    SLURM                                             20 | 1U                                   IBM iDataPlex dx360 M4  2x Xeon E5-2680v2  2.8GHz   20        |  12G      |  256G                                            5120G  400                                         +| @#cfc:x[017-048] 32 | 24 | 20.9GB 502GB | x86-64-v2 |  |  | 768 | 16064GB | 0 | 
-| @#cfc:z041-z113                                                                    SLURM                                             72 2U GPU Nodes (2x Nvidia Tesla K20x)  IBM iDataPlex dx360 M4  2x Xeon E5-2680v2  | 2.8GHz   20         6G        128G                                            9216G  1440                                        +| @#cfc:x[161-176] | 16 | 24 | 5.2GB 125GB | x86-64-v3 |  |  | 384 2000GB | 0 
-| @#cfc:z163-z166                                                                    SLURM                                              4 | 2U                                   HP DL560 G8             | 4x Xeon E5-4650L   | 2.6GHz   32         24G       768G                                            3072G  128                                         +| @#cfc:sheldon,x[177-178,180-222] 45 24 | 42.0GB | 1007GB | x86-64-v3 |  |  | 1080 | 45315GB | 0 | 
-| @#cfc:**#Taku9**                                                                             **~~=sum(range(col(),1,col(),row()-1))~~**                                                                                                                         **~~=sum(range(col(),1,col(),row()-1))~~G** |  **~~=sum(range(col(),1,col(),row()-1))~~**  | +| @#cfc:xq[01-10] | 10 | 128 | 2.0GB | 250GB | x86-64-v3 | 2x A5000 | 24GB | 1280 | 2500GB | 20 | 
-                                                                                                                                                                                                                                                                                                            |                                              |+@#cfc:xgpu[01-05,07-13] 12 16 | 11.7GB | 187GB | x86-64-v4 | 4x nVidia RTX 2080 TI | 11GB | 192 | 2244GB | 48 
 +| @#cfc:xgpu06 | 1 | 16 | 11.2GB | 179GB | x86-64-v4 4x nVidia RTX 2080 TI | 11GB | 16 | 179GB | 4 | 
 +@#cfc:xgpu[14-23] | 10 | 16 | 11.7GB | 187GB | x86-64-v4 | 4x A5000 | 24GB | 160 | 1870GB | 40 | 
 +| @#cfc:xgpu[24-25] | 2 | 16 | 11.7GB | 187GB | x86-64-v3 | 4x nVidia RTX 3090 | 24GB | 32 | 374GB | 
 +@#cfc:xgpu26 | 1 | 64 | 2.0GB | 125GB | x86-64-v3 | 10x A5000 | 24GB | 64 | 125GB | 10 
 +| @#cfc:xgpu28 | 1 | 24 | 10.4GB | 250GB | x86-64-v3 | 4x nVidia RTX A600 Ada | 48GB | 24 | 250GB | 4 | 
 +| @#cfc:xgpu[29-33] 24 | 5.2GB | 125GB | x86-64-v3 | 4x nVidia Titan V | 12GB | 120 | 625GB | 20 | 
 +| @#cfc:xgpu[27,34-52,54-56,58,62] | 25 | 24 | 5.2GB | 125GB | x86-64-v3 4x A5000 24GB 600 3125GB 100 | 
 +@#cfc:xgpu57 | 1 | 24 | 5.2GB | 125GB | x86-64-v3 | 4x nVidia RTX A600 | 48GB | 24 | 125GB | 4 | 
 +| @#cfc:xgpu[59-61] | 3 | 36 | 41.9GB | 1509GB | x86-64-v4 | 8x nVidia Tesla P100 | 16GB | 108 | 4527GB | 24 | 
 +| @#cfc:xgpu63 | | 24 | 5.2GB | 125GB | x86-64-v3 | 4x nVidia RTX A4500 Ada | 24GB | 24 | 125GB | 4 | 
 +| @#cfc:**#Taku 7** | **293** | | | | | | | **7948** **95448GB** **286** |
  
-(06.11.2018)+(21.07.2025)
  
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services/cluster/start.1719833989.txt.gz · Last modified: 2024/07/01 11:39 by zedv

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