This ´traditional´ session aims at highlighting Earth Science research targeting or concerned with state of the art computational and data infrastructures such as HPC (Supercomputers), Grids, Clouds and accelerator-based systems (GPGPU, FPGA).
This year we will focus on data intensive applications and how Big Data methods – analytics and algorithms – used on HPC, Grids and Clouds.
The session presents an opportunity for everyone to present and learn from results achieved, success stories and experience gathered during the process of study, adaption and exploitation of these systems.

In addition, contributions are welcome that showcase middleware and tools developed to support Earth science applications on HPC systems, Grid and Cloud infrastructures, e.g. to increase effectivity, robustness, or ease of use.
Topics of interest thus include:
- Data intensive Earth Science applications
- Big Data methods, unstructured and structures Data bases in ES
- Experience with Earth Science data and applications in Cloud environments e.g. solutions on Amazon EC2, Microsoft Azure, and Earth Science simulation codes runing on Cloud Infrastructures or Platforms.
- Earth Science applications executed on "traditional" Grid Infrastructures.
- Tools and Middleware for Earth Science applications on Grid, Cloud and on High Performance Computing infrastructures.
- Tools and services for Earth Science data management, workflow execution, web services and portals to ease access to compute resources.
- How the current development of the platforms and middleware relate to the requirements of Earth Science researchers and applications?

This session offers a unique opportunity to bridge the Cloud, Grid, HPC and Geoscience communities

Invited Speakers: Prof. Cecile Germain