Kognitive Systeme

The TCML cluster

The Training Center for Machine Learning (TCML) is a BMBF funded project which consists of a large GPU cluster. The GPU cluster is administered by the Cognitive Systems group in the Department of Computer Science (Wilhelm-Schickard-Institute). The following research groups are project partners in the TCML project and their members and students have the right to use the cluster for their research:

  1. Prof. Dr. Martin Butz (Cognitive modelling)
  2. Prof. Dr.-Ing Andreas Geiger (Autonomous Vision)
  3. Prof. Dr. Matthias Hein (Machine Learning)
  4. Prof. Dr. Philipp Hennig (Machine learning methods)
  5. Prof. Dr. Hendrik Lensch (Computergraphik)
  6. Prof. Dr. Ulrike von Luxburg (Machine Learning)
  7. Prof. Dr. Georg Martius (Distributed Intelligence)
  8. Prof. Dr. Gerard Pons-Moll (Real Virtual Humans)
  9. Prof. Dr. Kay Nieselt (Integrative Transcriptomics)
  10. Prof. Dr. Nico Pfeifer (Medical Informatics)
  11. Prof. Dr. Felix Wichmann (Neural Inform. Processing)
  12. Prof. Dr. Andreas Zell (Cognitive Systems) (administrators)

This cluster is intended to be used by various groups of people. The master and bachelor students working in the field of machine learning can benefit from the powerful computation capabilities in their practical assignments in courses and their thesis/projects research. It is also intended to be used for training courses on machine learning for participants from industry.

Overview of the cluster

The overview of the cluster can be seen in the figure. To separate and control computations and data storage/transfer, the cluster is divided into compute, data and head nodes.

The compute nodes: There are 40 compute nodes on which all the computations are performed. Each compute node has the following hardware specifications:

  • 2 TB SSD disk space
  • 256 GB memory
  • Intel XEON CPU E5-2650 v4
  • 4x GeForce GTX 1080 Ti

The data nodes: In addition there are two data nodes which hold all data on the cluster. The hardware specifications of each data node is as follows:

  • 73 TB disk space
  • 135 GB memory
  • Intel XEON CPU E5-2620 v4

The head node: The head (master) node controls all the functionalities of the cluster in a centralized manner. This makes sure that the jobs (tasks) on the cluster are scheduled and monitored properly. The users are only allowed to access this node and submit their jobs here.

A workload manager (Slurm) schedules the jobs based on the requested resources, availability of resources and priority of tasks in an optimal way. Slurm allocates different compute nodes to different jobs in an intelligent manner.

Documentation Link

The detailed documentation can be found on this link. It contains detailed information about the hardware and software of the cluster. There is also an example on how to run your code on the cluster using the workload manager (Slurm) and the container virtualization software (Singularity).

TCML-Upgrade 2024

In 2024-07 four of the nodes of the TCML were exchanged with different hardware. All 4 new nodes have 8 x 2080Ti  GPUs - instead of 4 x 1080Ti. Both GPU types have 11 GB RAM. Also newer CPU processors and better SSD. Thanks to the ML-Cloud for giving us this servers.

TCML-Upgrade 2025

In 2025-04 four of the nodes of the TCML were exchanged with new hardware. All 4 new nodes have 8 x L40S GPUs with 48 GB of GPU-RAM. This upgrade was founded by 8 Professors and in the beginning only members of those groups are allowed to use the L40S hardware. In the beginning, L40S usage is additional limited to jobs with max 1 day calculating time.

If you are in the group of  …  and want to use L40S please contact  …
and tell him/her your TCML user name and maybe the reason

Professor Andreas Zelltcml-contactspam prevention@listserv.uni-tuebingen.de
Professor Georg MartiusFelix Kloss
Professor Martin Butznn
Professor Matthias Heinnn
Professor Gerard Pons-Mollnn
Professor Philipp HennigAndres Fernandez
Professor Andreas GeigerBernhard Jaeger, Bozidar Antic
Professor Nico PfeiferJules Kreuer

TCML Maintenance

The next maintenance is scheduled

from Monday, 2025-10-06 until Friday, 2025-10-10

Account applications between Monday, 2025-09-29 until end of maintenance will be rejected.

TCML Account Application

Logging in to the TCML

To use the cluster, the users must login to one of 3 available login node and execute their tasks from there. The login nodes have the following IP addresses or aliases:
IP address: 134.2.17.166
Alias: login1.tcml.uni-tuebingen.de

IP address: 134.2.17.248
Alias: login2.tcml.uni-tuebingen.de

IP address: 134.2.17.202
Alias: login3.tcml.uni-tuebingen.de

use ssh in the following way:

$ ssh username@login3.tcml.uni-tuebingen.de

ssh is only available from inside of the university network (134.2.x.y)

remote development only allowed on login3

Privacy policy

We use the data provided to us only to create a user account on the cluster and to contact you with issues concerning the cluster. We wont share given data with anyone. Administrators are allowed to delete your data after warning you beforehand. As long as it does not contradict to the former three sentences, the privacy policy of the Eberhard Karls Universitaet Tuebingen holds.

Contact

If you have any question, complaint, suggestion of improvement or anything else feel free to contact us via tcml-contactspam prevention@listserv.uni-tuebingen.de.

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