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Gridification and virtualization: enabling e-Science in the life sciences

Published: 29 January 2008 Publication History

Abstract

The MediGRID [1] project, which is part of the German e-Science initiative D-Grid, aims to provide a community Grid for researchers in the fields of bioinformatics, medical image processing, biomedical ontology, and clinical research applications. Users in the life science domain usually do not have a strong computer science background. Therefore, it is crucial to make the Grid solution as user friendly as possible. To achieve this goal, MediGRID is building up an infrastructure that follows two principles: gridification and virtualization.
The basic Grid middleware used in MediGRID is the Globus Toolkit 4, which provides services for security, execution and data management, and resource discovery. On top of Globus, MediGRID employs further specialized middlewares. The first is the Grid Workflow Execution Service (GWES) [2] that orchestrates the distributed execution of workflows on Grid resources. Application workflows consist of several successive program executions and intermediate data transfers. Second, the Storage Resource Broker (SRB) [3] Data Grid middleware is utilized to handle large amounts of distributed data and corresponding metadata. We use SRB to create a global logical namespace in which file replica can be accessed by unique file names, independent of the physical locations. At the top level, a portal framework is employed to provide a convenient graphical user interface.
The middleware layers allow to virtualize the MediGRID resources. This means, end users do not interact with specific clusters and storage elements but deal with a high-level abstraction of the Grid. For this, extensive gridification work is necessary to set up the Grid infrastructure and adapt the applications to Grid computing. We will demonstrate the whole process with the gene-finding application AUGUSTUS [4].

References

[1]
S. Kottha, et al., Medical image processing in MediGRID. In Proceedings of the German e-Science Conference, Baden-Baden, Germany, 2007.
[2]
A. Hoheisel, Grid Workflow Execution Service - Dynamic and interactive execution and visualization of distributed workflows. In Proceedings of the Cracow Grid Workshop 2006, Cracow, 2006.
[3]
C. Baru, R. Moore, A. Rajasekar, M. Wan, The SDSC storage resource broker. In CASCON '98: Proceedings of the 1998 conference of the Centre for Advanced Studies on Collaborative research, IBM Press, 1998, p. 5.
[4]
M. Stanke, O. Schoffmann, B. Morgenstern, and S. Waack, Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources, BMC Bioinformatics, vol. 7, p. 62, 2006.

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MG '08: Proceedings of the 15th ACM Mardi Gras conference: From lightweight mash-ups to lambda grids: Understanding the spectrum of distributed computing requirements, applications, tools, infrastructures, interoperability, and the incremental adoption of key capabilities
January 2008
178 pages
ISBN:9781595938350
DOI:10.1145/1341811
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • National e-Science Institute (Edinburgh, UK)
  • Louisiana State University (USA)

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Association for Computing Machinery

New York, NY, United States

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Published: 29 January 2008

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Mardi Gras'08
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Mardi Gras'08: 15th Mardi Gras Conference on Distributed Applications
January 29 - February 3, 2008
Louisiana, Baton Rouge, USA

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