Abstract
The analysis and visualization of the LHC data is a good example of human interaction with petabytes of inhomogeneous data. After outlining the computational requirements for an efficient analysis of such data sets, a proposal, RAVEN – a Random Access, Visualization and Exploration Network for petabyte sized data sets, for a scalable architecture meeting these demands is presented. The proposed hardware basis is a network of ”CSR”-units based on off-the-shelf components, which combine Computing, data Storage and Routing functionalities. At the software level efficient protocols for broadcasting information, data distribution and information collection are required, together with a middleware layer for data processing.
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Schmelling, M., Britsch, M., Gagunashvili, N., Gudmundsson, H.K., Neukirchen, H., Whitehead, N. (2012). RAVEN – Boosting Data Analysis for the LHC Experiments. In: Jónasson, K. (eds) Applied Parallel and Scientific Computing. PARA 2010. Lecture Notes in Computer Science, vol 7134. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28145-7_21
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