Marko Krznaric

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Many Grid architectures have been developed in recent years. These range from the large community Grids such as LHG and EGEE to single site deployments such as Condor. However, these Grid architec-tures have tended to focus on the execution of executables. Application scientists are now seeking to deploy their entire workflows onto these Grids, which will(More)
The Grid is a concept which allows the sharing of resources between distributed communities, allowing each to progress towards potentially different goals. As adoption of the Grid increases so are the activities that people wish to conduct through it. The GRIDCC project is a European Union funded project addressing the issues of integrating instruments into(More)
  • Rob Allan, David Baker, David Boyd, Dharmesh Chohan, Simon Cox, Hakki Eres +19 others
  • 2003
Over the period September 2002-April 2003 the UK Grid Engineering Task Force and staff at Regional e-Science Centres and CCLRC deployed the Globus Toolkit GT2 at 14 sites and on approximately 80 compute resources to set up the first production-quality e-Science Grid for the UK. This work is proving to be exemplary of what can be achieved using heterogeneous(More)
The GENIE project aims to deliver a Grid-based, modular, distributed and scalable Earth System Model for long-term and paleo-climate studies to the environmental sciences community. In this paper we address the scientific problem of the vulnerability of the thermohaline circulation to the global climate, and describe our e-scientific solution using a(More)
BACKGROUND Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large data sets. This, together with the proliferation of tools and techniques for microarray data analysis, makes it very challenging for a laboratory scientist to keep up-to-date with(More)
  • Li Guo, Steve Mcgough, Asif Akram, David Colling, Janusz Martyniak, Marko Krznaric
  • 2008
As the main computing paradigm for resource-intensive scientific applications, Grid[1] enables resource sharing and dynamic allocation of computational resources. Large-scale grids are normally composed of huge numbers of components from different sites, which increases the requirements of workflows and quality of service (QoS) upon these workflows as many(More)