TY - GEN
T1 - Towards addressing CPU-intensive seismological applications in Europe
AU - Carpené, Michele
AU - Klampanos, Iraklis A.
AU - Leong, Siew Hoon
AU - Casarotti, Emanuele
AU - Danecek, Peter
AU - Ferini, Graziella
AU - Gemünd, André
AU - Krause, Amrey
AU - Krischer, Lion
AU - Magnoni, Federica
AU - Simon, Marek
AU - Spinuso, Alessandro
AU - Trani, Luca
AU - Atkinson, Malcolm
AU - Erbacci, Giovanni
AU - Frank, Anton
AU - Igel, Heiner
AU - Rietbrock, Andreas
AU - Schwichtenberg, Horst
AU - Vilotte, Jean Pierre
PY - 2013
Y1 - 2013
N2 - Advanced application environments for seismic analysis help geoscientists to execute complex simulations to predict the behaviour of a geophysical system and potential surface observations. At the same time data collected from seismic stations must be processed comparing recorded signals with predictions. The EU-funded project VERCE ( http://verce.eu/ ) aims to enable specific seismological use-cases and, on the basis of requirements elicited from the seismology community, provide a service-oriented infrastructure to deal with such challenges. In this paper we present VERCE's architecture, in particular relating to forward and inverse modelling of Earth models and how the, largely file-based, HPC model can be combined with data streaming operations to enhance the scalability of experiments. We posit that the integration of services and HPC resources in an open, collaborative environment is an essential medium for the advancement of sciences of critical importance, such as seismology.
AB - Advanced application environments for seismic analysis help geoscientists to execute complex simulations to predict the behaviour of a geophysical system and potential surface observations. At the same time data collected from seismic stations must be processed comparing recorded signals with predictions. The EU-funded project VERCE ( http://verce.eu/ ) aims to enable specific seismological use-cases and, on the basis of requirements elicited from the seismology community, provide a service-oriented infrastructure to deal with such challenges. In this paper we present VERCE's architecture, in particular relating to forward and inverse modelling of Earth models and how the, largely file-based, HPC model can be combined with data streaming operations to enhance the scalability of experiments. We posit that the integration of services and HPC resources in an open, collaborative environment is an essential medium for the advancement of sciences of critical importance, such as seismology.
UR - http://www.scopus.com/inward/record.url?scp=84884490487&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-38750-0_5
DO - 10.1007/978-3-642-38750-0_5
M3 - Conference contribution
AN - SCOPUS:84884490487
SN - 9783642387494
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 55
EP - 66
BT - Supercomputing - 28th International Supercomputing Conference, ISC 2013, Proceedings
T2 - 28th International Supercomputing Conference on Supercomputing, ISC 2013
Y2 - 16 June 2013 through 20 June 2013
ER -