This session aims to highlight Earth Science research concerned with state of the art computational and data infrastructures such as HPC (Supercomputers), Grids, Clouds and accelerator-based systems (GPGPU, FPGA). This year the focus is also on data intensive workflows (scientific workflows), that are nowadays playing a significant role where services for data flow, classical simulation and analytics have to be orchestrated.

The session presents an opportunity for everyone to present and learn from results achieved, success stories and experience gathered during the process of study, adaptation and exploitation of these systems.
Further 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 include:
- Data intensive Earth Science applications and how they have been adapted to different HPC infrastructures
- Data mining software stacks to deal with large environmental data
- HPC simulation and High Performance Data Analytics
- Experience with Earth Science data and applications in Cloud environments e.g. solutions on Amazon EC2, Microsoft Azure, and Earth Science simulation codes running on Cloud infrastructures or platforms.
- Earth Science applications executed on "traditional" Grid infrastructures, HPC and/or data-oriented architecture in e-Science
- Tools and services for Earth Science data management, workflow execution, web services and portals to ease access to compute resources.
- Tools and middleware for Earth Science applications on Grid, Cloud and on High Performance Computing infrastructures.
- How the current development of the platforms and middleware fit to the requirements of researchers from the Earth Science sector and their applications?

This session offers an unique opportunity to bridge the Cloud, Grid, HPC, Data-mining and Geoscience communities.

Invited Speakers: will be announced soon