Exploiting the EGI Federated clouds - Paas & SaaS workshop
- Diego Scardaci (EGI.eu/INFN)
Andrei Tsaregorodtsev (CNRS)
Multiple scientific communities are using more and more intensive computations to reach their research goals. Various computing resources can be exploited by these communities making it difficult to adapt their applications for different computing infrastructures. Therefore, there is a need for tools for seamless aggregation of different computing and storage resources in a single coherent...
Dr Sandro Fiore (CMCC)
The Ophidia project is a research effort on big data analytics facing scientific data analysis challenges in multiple domains (e.g. climate change). It provides a framework responsible for atomically processing and manipulating datacubes, by providing a common way to run distributive tasks on large set of fragments (chunks). Even though the most relevant use cases for Ophidia have been...
Catalin Condurache (STFC)
The CernVM-FS is firmly established as a method of software and conditions data distribution for the LHC experiments and many other Virtual Organizations at Grid sites. Use of CernVM-FS is reaching now a new stage, its advantages starting to be acknowledged by communities activating within and making use of the EGI Federated Cloud. As the manipulation of research data within cloud...
Peter Kacsuk (MTA SZTAKI)
Compute-intensive applications such as simulations applied in various research areas and industry require computing infrastructures enabling highly parallel, distributed processing. Grids, clusters, supercomputers and clouds are often used for this purpose. There also exist tools that allow easier design and construction of such complex applications, typically in the form of workflows, which...
Tamas Kiss (University of Westminster, London, UK)
With the rapid increase of data volumes in scientific computations, the importance of utilising parallel and distributed computing paradigms in data processing is becoming more and more important. Hadoop is an open source implementation of the MapReduce framework supporting processing large datasets in parallel and on multiple nodes in a reliable and fault-tolerant manner. Scientific workflow...
Luis Cabellos (CSIC)
Many problems can be addressed in a realistic way with the help of Agent Based Model tools. However, these tools are sometimes not easy to use for a final user, or are not able to scale up to use the computing resources required by the problem. We propose to develop a general platform supporting different ABM solutions, and deployed as a service in HPC Cloud resources. We analyze a first...