Topic 15: High Performance and Scientific Applications


As demand in high-resolution and high-fidelity modeling and simulation increases, desktop computers or small clusters of processors have proven to be insufficient to carry out the calculations in many scientific, engineering, and industrial applications. Indeed, many such applications typically require a significant amount of computing time or need to process a large amount of data. This topic will highlight recent progress in the use of high-performance parallel and scientific computing, with an emphasis on successes, advances, and lessons learned in the development and implementation of novel scientific, engineering, and industrial applications. Today's large computational solutions are often required to operate in complex information and computation environments, where data access can be as important as computational methods and performance, hence the technical approaches in this topic span a wide range of areas, which include, but are not limited to, high performance parallel computing, data access, and the associated problem-solving environments that compose and manage advanced solutions. We welcome papers that describe new applications, as well as existing applications ported to new environments, e.g., from workstations to modern parallel computers.


  • Advances in science and engineering modeling and simulation in fluid dynamics, structural mechanics/dynamics, physics, chemistry, earth sciences, pharmaceutical design, etc.
  • Applications in bioinformatics and systems biology (e.g. genomics and proteomics, gene identification and annotation, phylogeny reconstruction, structural biology).
  • New applications in non-traditional areas such as health care, social sciences, financial modeling, transportation, and economics.
  • Large-scale data analysis in high-performance applications.
  • Success and lesson learned in petascale computing and beyond.

Topic Committee

Global chair

Esmond G. Ng, Lawrence Berkeley National Laboratory, USA

Local chair

Olivier Coulaud, INRIA, France


Kengo NAKAJIMA, University of Tokyo, Japan
Mariano Vazquez, Barcelona Supercomputing Center, Spain