Seminari del Centre de Recerca INSPIRES. Earthquake and failure forecasting in real-time
Informació de l'esdeveniment
- Inici:
El proper dijous 9 de maig, a les 11:30h, tindrà lloc el següent seminari del Centre de Recerca INSPIRES:
Earthquake and failure forecasting in real-time: A Forecasting Model Testing Centre Affiliation
Dr. Rosa Filgueira. University of Edinburgh
El seminari es realitzarà en acabar el Plenari de Centre de Recerca INSPIRES que tindrà lloc a la Sala de Videoconferències de l'edifici CCCT del Campus de Cappont
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Rosa Filgueira is Research Associate in Data Intensive Research group from October 2011. Previously, she was research visitor in the same group with the grant HPC-Europa 2. She studied the Master of Computer Science in the University of Deusto (Spain) and made the PhD in Computer Sciences in the University of Carlos III of Madrid (Spain). There she worked as Teaching Assistant and participated in several projects co-funded by the University Carlos III of Madrid and the Spanish Government Grant. Currently, she is working in EFFORT project (Earthquake and Failure Forecasting in Real Time from controlled laboratory test to volcanoes and earthquakes). EFFORT is UK NERC funded research project running from January 2011 to January 2014. The aim of the project is to provide a facility for developing and testing models to forecast brittle failure in experimental and natural data. Rosa, as part of Data intensive Research Group it is in charge of Data transfer, Data formats, Data storage and Data access of the project. She is interested in improve the scalability and performance of parallel applications executed in multi-core clusters. This includes topics such as performance evaluation and modeling of HPC applications; techniques for increasing the performance of network communication, and parallel I/O for High Performance Computing Systems.Her specialties are: 1. Optimization and parallelization of irregular codes for multicore architectures 2. Optimization techniques to enchance scalability and performanced of MPI-based applications 3. Collective I/O techniques for multicore cluster 4. HPC applications and parallel benchmark
