Latest News

News

 

Annual Report 2018/19

Take a look at our latest annual report. Find current highlights and projects of our department.

 

Press Release / 5.12.2018

Project EPEEC

Bringing European parallel programming technology to the exascale era.The European EPEEC project (European joint Effort toward a Highly Productive Programming Environment for Heterogeneous Exascale Computing) has received €3.9 M in funding to develop and deploy a production-ready parallel programming environment.

 

Article / 26.11.2018

Move Over Lustre & Spectrum Scale – Here Comes BeeGFS?

BeeGFS won the 'HPCwire Best HPC Storage Product or Technology Award' at SC18

Blog Post / 7.9.2018

Collaboration with SAP

»After almost 4 years of collaboration, we are convinced that partnering with the ITWM was the best thing SAP could do to streamline the development process of SAP S/4HANA for advanced variant configuration.«. We are very pleased with these words from the SAP blog.

Since 2015, we have been developing a new, state-of-the-art configuration engine for the SAP database S/4HANA together with experts from SAP. Our part in the project consisted primarily of developing algorithms for processing a wide variety of variant configurations.

Fairs & Events

Fair / Frankfurt a. M. / 06/16/2019 - 06/20/2019

ISC 2019

We present news around Machine Learning. Currently we focus on the distributed parallelization of optimization methods used to train large Machine Learning models.

Deep Learning Seminar

 

Machine Learning, Deep Learning and the analysis of huge amounts of data in general are becoming more and more important. Such methods are used in almost every area of research, development or industry. The Deep Learning Seminar of the Fraunhofer ITWM is intended to give interes persons an insight into this large field of research and a deeper understanding. Everyone who wants to learn more about Deep Learning, Machine Learning or AI in general is invited - no matter if students, PhD students, professors or software developers.

 

The seminar takes place regularly on Thursdays at 10 am.

Conference Room E4.09 (Riemann)
Fraunhofer-Zentrum 
Fraunhofer-Platz 1 
67663 Kaiserslautern

Vacancies

To work in industrial and research projects, the department High Performance Computing is permanently looking for Scientific Staff and Software Developers (m/f) for our various fields of activities, for example Green by IT, Deep Learning or Parallel Programming.

We expect that all applicants enjoy research and team communication, that they are confident handling of modern programming languages, preferably C++ and have an interest or experience in software development and object-oriented software design as well as having a good command of German or English.

Please look at the currently posted job vacancies or apply unsolicited.

 

BSc/MSc and Diploma Students

  • For a thesis project in the fields of our HPC tools and applications.
  • Your field of study is not restricted to mathematics or computer science, but students of physics, engineering or related areas are also invited to apply. We supervise your thesis in cooperation with your university or German "Fachhochschule"

 

PhD Students

We are permanently looking for PhD students. PhD students will gain scholarships according to the DFG guidance.

 

Postdocs

Our team of the field "Data Analysis and Machine Learning" searches for a postdoc with the following topics:

  • AutoML
  • Topologiesuche
  • In-Memory Processing
  • Partitioned Global Address Space (PGAS)
  • Optimierung 
  • Deep Learning
  • Python
  • Parallel Programming
  • Frameworks

The postdoc will extend our distributed analytics runtime (DART) framework by a partitioned global address space virtual memory layer and does research on workflow optimization for neuronal network topology search (AutoML).

Please apply unsolicited if you are interested: to the application

 

Graduate Assistants

The department HPC provides interesting tasks for scientific assistants from the main study course in mathematics, engineering sciences or physics. We expect basic knowledge and interest in computational simulation and/or programming competency.