JARA-HPC Symposium 2016

Start
4th October 2016 07:00 AM
End
5th October 2016 04:00 PM
Location
IT Center, RWTH Aachen University, Kopernikusstraße 6, 52074 Aachen, Germany

JHPCS'16

Current HPC systems consist of complex configurations with a huge number of components, very likely heterogeneous, and typically with not enough memory. The hard- and software configuration can change dynamically due to fault recovery or power saving procedures. Deep software hierarchies of large, complex software components are needed to make efficient use of such systems. On the applications side, HPC systems are increasingly used for data analytics and complex workflows. Successful application development requires collaboration between the domain scientists on one side, and computer science / HPC experts on the other.

JARA-HPC is the High Performance Computing section of JARA, the Jülich Aachen Research Alliance. JARA represents a cooperation between RWTH Aachen University and Forschungszentrum Jülich and is a model that is unique in Germany, overcoming the mere juxtaposition of university and non-university research and teaching. Scientists of JARA-HPC combine the knowledge of massively parallel computing on supercomputers with the respective expert competences from different research fields.

JARA-HPC organizes this symposium to motivate lively discussions on the various aspects of the development of HPC applications among experts. Participants will have the opportunity for an in-depth exchange with colleagues from different research fields who also make use of HPC systems in their scientific work.

Specifically, visualization methods, performance optimization and data management topics will be discussed in connection with application development in Engineering-, Materials- and Neuroscience.

Topics

Topics of interest include, but are not limited to, the following:

  • Efficient multi-physics coupling strategies in CFD
  • Large materials simulation for energy applications
  • Integration of HPC numerical libraries in ab-initio codes
  • Provenance tracking for reproducibility of workflows and data in science
  • Scalable I/O for massively parallel applications
  • Scalable parallel visualization methods
  • In-situ visualization solutions
  • Scalable algorithms in Simulation Science
  • Performance portability / porting applications
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Last Modified: 16.11.2022