Section: Overall Objectives

Context: the need for scalable data management

We are witnessing a rapidly increasing number of application areas generating and processing very large volumes of data on a regular basis. Such applications are called data-intensive. Governmental and commercial statistics, climate modeling, cosmology, genetics, bio-informatics, high-energy physics are just a few examples. In these fields, it becomes crucial to efficiently store and manipulate massive data, which are typically shared at a large scale and concurrently accessed. In all these examples, the overall application performance is highly dependent on the properties of the underlying data management service. With the emergence of recent infrastructures such as cloud computing platforms and post-Petascale architectures, achieving highly scalable data management has become a critical challenge.

The KerData project-team is namely focusing on scalable data storage and processing on clouds and post-Petascale platforms, according to the current needs and requirements of data-intensive applications. We are especially concerned by the applications of major international and industrial players in Cloud Computing and post-Petascale High-Performance Computing (HPC), which shape the long-term agenda of the Cloud Computing and Exascale HPC research communities.