HiPerCH 11

HiPerCH 11

High Performance Computing in Hessen (HiPerCH)

The 11th installment of the HiPerCH workshop series takes place at Technical University Darmstadt. It focuses on Deep Learning on high performance computing clusters, and related tools and languages. In addition, we hold a course on Fortran modernization in cooperation with NAG.

The HiPerCH workshops are conducted by the Competence Center for High Performance Computing in Hessen (HKHLR). They are targeted at students and scientists from Hessen, Mainz, and Kaiserslautern with interest in programming modern HPC hardware.

The modules can be booked separately. Please note that there is a limited number of participants for each module.

All talks and lectures will be held in English.

The registration is now open!

Update August 8: Module 1 is fully booked! New registrations will be placed on the waiting list.

Update August 23: Module 4 is fully booked! New registrations will be placed on the waiting list.

Update September 16: Module 5 is fully booked! New registrations will be placed on the waiting list.


Public talks

See: Public talks detailed information

Prof. Dr. Kristian Kersting (TU Darmstadt, Machine Learning Lab)
"Deep Machines That Know When They Do Not Know"

PD Dr. Olena Linnyk (Frankfurt Institute for Advanced Studies, milch&zucker Gießen)
"What Can Machine Learning Do For My Project"

Christian Griebel (TU Darmstadt, Lichtenberg High Performance Computer)
"New computational resources with Lichtenberg II and the coming DL/ML software environment"

Prof. Dr. Christian Bischof et al. (TU Darmstadt)
"Research in Software-Factory 4.0"

Date: Monday, September 23, and Tuesday, September 24

Module 1: Deep Learning

See: Module 1 detailed information

Date: Monday, September 23, and Tuesday, September 24

Module 2: Fortran Modernization

See: Module 2 detailed information

Date: Wednesday, September 25, and Thursday, September 26

Module 3: R on HPC Systems

See: Module 3 detailed information

Date: Wednesday, September 25

Module 4: Scientific Data Processing with Python

See: Module 4 detailed information

Date: Thursday, September 26

Module 5: Parallel Computing, Deep Learning and Reinforcement Learning Workflows in MATLAB

See: Module 5 detailed information

Date: Friday, September 27

Evening Event

The evening event will be a dinner in Darmstadt on September 24, 19:00.

The attendance fee is included in booking one of the modules.


The workshop will take place on several locations of the TU Darmstadt Stadtmitte campus. Please see the module descriptions for respective information.


Attention: We have reserved a limited amount single rooms at InterCity Hotel, located near the train station, with special pricing for HiPerCH visitors. The price for a single room will be €85,- per night. This includes breakfast and a public transport ticket for Darmstadt during your stay. This offer will be available until Friday, September 6. Please refer to the keyword sent to you in your HiPerCH registration confirmation.

Other hotel options in Darmstadt include:



Event Registration Remark

Before registering: Please read the detailed information about the modules you like to book!

The registration is binding.

All feed include coffee breaks and lunch (exception no lunch for modules 1 and 5). Please note that the reduced fee is only available for Bachelor and Master students. A certificate of study is necessary.

With your registration, HKHLR will use your contact information for organizational reasons:

  • to inform you about workshop details,  
  • about agenda changes, and
  • to contact you, in order to give us feedback about the workshop (evaluation).

The data will not be transferred to third parties (exception module 2, see below).

The personal data will be deleted two months after the closing of the invoice. We evaluate the data statistically to improve our service for your research. For further questions, please contact: office@hpc-hessen.de.

For module 2 (Fortran Modernization): Part of the registration data will be shared with NAG and NAG may use the data of participants after the workshop to get feedback and to communicate relative information.