D. D'Agostino, A. Clematis, A. Galizia, A. Quarati, E. Danovaro, Luca Roverelli, Gabriele Zereik, D. Kranzlmüller, Michael Schiffers, N. Felde, Christian Straube, Olivier Caumontz, E. Richard, L. Garrote, Quillon Harphamk, H.R.A. Jagers, V. Dimitrijevic, L. Dekic, Elisabetta Fiorizz, F. Delogu, A. Parodi
{"title":"The DRIHM Project: A Flexible Approach to Integrate HPC, Grid and Cloud Resources for Hydro-Meteorological Research","authors":"D. D'Agostino, A. Clematis, A. Galizia, A. Quarati, E. Danovaro, Luca Roverelli, Gabriele Zereik, D. Kranzlmüller, Michael Schiffers, N. Felde, Christian Straube, Olivier Caumontz, E. Richard, L. Garrote, Quillon Harphamk, H.R.A. Jagers, V. Dimitrijevic, L. Dekic, Elisabetta Fiorizz, F. Delogu, A. Parodi","doi":"10.1109/SC.2014.49","DOIUrl":null,"url":null,"abstract":"The distributed research infrastructure for hydrometeorology (DRIHM) project focuses on the development of an e-Science infrastructure to provide end-to-end hydro meteorological research (HMR) services (models, data, and post processing tools) by exploiting HPC, Grid and Cloud facilities. In particular, the DRIHM infrastructure supports the execution and analysis of high-resolution simulations through the definition of workflows composed by heterogeneous HMR models in a scalable and interoperable way, while hiding all the low level complexities. This contribution gives insights into best practices adopted to satisfy the requirements of an emerging multidisciplinary scientific community composed of earth and atmospheric scientists. To this end, DRIHM supplies innovative services leveraging high performance and distributed computing resources. Hydro meteorological requirements shape this IT infrastructure through an iterative \"learning-by-doing\" approach that permits tight interactions between the application community and computer scientists, leading to the development of a flexible, extensible, and interoperable framework.","PeriodicalId":275261,"journal":{"name":"SC14: International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"172 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SC14: International Conference for High Performance Computing, Networking, Storage and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SC.2014.49","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23
Abstract
The distributed research infrastructure for hydrometeorology (DRIHM) project focuses on the development of an e-Science infrastructure to provide end-to-end hydro meteorological research (HMR) services (models, data, and post processing tools) by exploiting HPC, Grid and Cloud facilities. In particular, the DRIHM infrastructure supports the execution and analysis of high-resolution simulations through the definition of workflows composed by heterogeneous HMR models in a scalable and interoperable way, while hiding all the low level complexities. This contribution gives insights into best practices adopted to satisfy the requirements of an emerging multidisciplinary scientific community composed of earth and atmospheric scientists. To this end, DRIHM supplies innovative services leveraging high performance and distributed computing resources. Hydro meteorological requirements shape this IT infrastructure through an iterative "learning-by-doing" approach that permits tight interactions between the application community and computer scientists, leading to the development of a flexible, extensible, and interoperable framework.