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COMPETENCE CENTER
FOR SCALABLE DATA SERVICES
AND SOLUTIONS

TEC-1: HPC cluster usage/processing capabilities

 

Contact

Jan Frenzel

Target

Developers who want to control communication patterns and data distribution for maximum of throughput or minimum of latency.

Dependencies

None.

Description

The ScaDS service center team together with the ZIH provide the possibility to use the ZIH high-performance computer for analyzing data and algorithms. Typically, serial programs reach speed limitations when they are applied to large datasets. To avoid long run times, an easy solution is to write a parallel version of the program. However, with small workstations, one can only expect small performance improvements. So, for Big Data applications, it might be necessary to run a parallel program on many processing elements. The registered user can log in and start jobs on the HPC system.

Offerings

• Possibility to start programs and/or save data on a high-performance computer: We provide example scripts and gateways to start HPC jobs. When needed, software tools are provided to analyze and optimize programs.

Consumption

  • Collect information about your use case. Prepare for the following questions:

  • What focus has your research?

  • Do you already have a (serial/parallel) program?

  • How many resources do you need? (type of computing resources and amount of required computing time)

  • Who is responsible for your project?

  • Contact us (via e-mail or phone)

  • We send you an application form. With this form, we want to have a look at your use case and see the specific requirements. This helps us to provide any additional software you might need. Additionally, we need this form to request computing resources.

  • Fill out the form and send it back to us.

  • We contact you, when your login is granted and you can access our cluster. This might require some time.

  • We send you information about how to use our cluster. This includes material on how to log on or submit jobs to the cluster, write programs or avoid potential bottlenecks.