V Breton1, R Medina, J Montagnat. 1. Laboratoire de Physique Corpusculaire, CNRS-IN2P3, Campus des Cézeaux, Aubière, France. breton@clermont.in2p3.fr
Abstract
BACKGROUND: The availability of large amounts of data in heterogeneous formats and the rapid progress in fields such as computer based drug design, medical imaging and medical simulations have lead to a growing demand for large computational power and easy accessibility to heterogeneous data sources. OBJECTIVES: The goal is to address these needs by deploying computing grids. Grids provide both large scale and distributed storage facilities and an increased computing power. Moreover, Grids are a promising tool to foster the synergy between bioinformatics and computerised medical imaging. METHODS: A first biomedical grid is being deployed within the framework of the DataGrid IST project (http://www.edg.org). The goal of the project is to provide a novel environment to support globally distributed scientific exploration involving up to multi-Perabyte datasets. RESULTS AND CONCLUSIONS: The first biomedical applications deployed inside the project demonstrate the relevance of the grid paradigm for genomics and medical image processing. They also highlight the specific requirements of the biomedical community.
BACKGROUND: The availability of large amounts of data in heterogeneous formats and the rapid progress in fields such as computer based drug design, medical imaging and medical simulations have lead to a growing demand for large computational power and easy accessibility to heterogeneous data sources. OBJECTIVES: The goal is to address these needs by deploying computing grids. Grids provide both large scale and distributed storage facilities and an increased computing power. Moreover, Grids are a promising tool to foster the synergy between bioinformatics and computerised medical imaging. METHODS: A first biomedical grid is being deployed within the framework of the DataGrid IST project (http://www.edg.org). The goal of the project is to provide a novel environment to support globally distributed scientific exploration involving up to multi-Perabyte datasets. RESULTS AND CONCLUSIONS: The first biomedical applications deployed inside the project demonstrate the relevance of the grid paradigm for genomics and medical image processing. They also highlight the specific requirements of the biomedical community.