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PyCOMPSs implementation of Probabilistic Tsunami Forecast (PTF). PTF explicitly treats data- and forecast-uncertainties, enabling alert level definitions according to any predefined level of conservatism, which is connected to the average balance of missed-vs-false-alarms. Run of the Boumerdes-2003 event test-case with 1000 scenarios, 8h tsunami simulation for each and forecast calculations for partial and full ensembles with focal mechanism and tsunami data updates.
Type: COMPSs
Creators: Louise Cordrie, Jorge Ejarque, Carlos Sánchez Linares, Jacopo Selva, Jorge Macías, Steven J. Gibbons, Fabrizio Bernardi, Roberto Tonini, Rosa M. Badia, Sonia Scardigno, Stefano Lorito, Finn Løvholt, Fabrizio Romano, Manuela Volpe, Alessandro D'Anca, Marc de la Asunción, Manuel J. Castro
Submitter: Jorge Ejarque
Name: Random Forest Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum4 This is an example of Random Forest algorithm from dislib. To show the usage, the code generates a synthetical input matrix. The results are printed by screen. This application used dislib-0.9.0
Lysozyme in water sample COMPSs application
Cluster Comparison COMPSs application
Cholesky factorisation COMPSs application
K-means COMPSs application
Wordcount reduce version COMPSs application
Wordcount merge version COMPSs application
Lysozyme in water full COMPSs application, using dataset_small
Name: Lanczos SVD Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum4
Lanczos SVD for computing singular values needed to reach an epsilon of 1e-3 on a matrix of (150000, 150). The input matrix is generated synthetically. This application used dislib-0.9.0
Type: COMPSs
Creators: Fernando Vázquez-Novoa, Workflows and Distributed Computing
Submitter: Fernando Vázquez-Novoa
