Improving e-Science with Interoperability of the e-Infrastructures EGEE and DEISA

• In the last couple of years, many e-Science infrastructures have begun to offer production services to e- Scientists with an increasing number of applications that require access to different kinds of computational resources. Within Europe two rather different multi-national e-Science infrastructures evolved over time namely Distributed European Infrastructure for Supercomputing Applications (DEISA) and Enabling Grids for E-SciencE (EGEE). DEISA provides access to massively parallel systems such as supercomputers that are well suited for scientific applications that require many interactions between their typically high numbers of CPUs. EGEE on the other hand provides access to a world-wide Grid of university clusters and PC pools that are well suited for farming applications that require less or even no interactions between the distributed CPUs. While DEISA uses the HPC-driven Grid technology UNICORE, EGEE is based on the gLite Grid middleware optimized for farming jobs. Both have less adoption of open standards and therefore both systems are technically non-interoperable, which means that no e-Scientist can easily leverage the DEISA and EGEE infrastructure with one suitable client environment for scientific applications. This paper argues that future interoperability of such large e-Science infrastructures is required to improve e-Science in general and to increase the real scientific impact of world-wide Grids in particular. We discuss the interoperability achieved by the OMII-Europe project that fundamentally improved the interoperability between UNICORE and gLite by using open standards. We also outline one specific scientific scenario of the WISDOM initiative that actually benefits from the recently established interoperability.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)

Nyckelord

Computational resources

E-science infrastructures

Grid technologies

Massively parallel systems

Production services

Scientific applications

Supercomputing applications

University clusters

Grid computing

Microelectronics

Middleware

Program processors

Supercomputers

Visualization

Interoperability

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