In the Parallel and Distributed Systems (PDS) Group of the Faculty of Electrical Engineering, Mathematics, and Computer Science of Delft University of Technology (TUD), and in Computer Systems research cluster at the Leiden Institute of Advanced Computer Science (LIACS) of Leiden University, both in the Netherlands, there are job openings for
two PhD Students and one Postdoc in COMPUTER SCIENCE
in the area of Resource Management and Scheduling in GRIDS
in the project GUARanteed Delivery in Grids (GUARD-G), which is funded by NWO in the context of the GLANCE programme on parallel and distributed computing.
DESCRIPTION OF THE RESEARCH
In the vision of grids as a computing utility, similar to the power grid for electricity and the telephone system for voice connections, users should be able to tap their resources and get guaranteed or at least predictable responses. However, in current grids, such guarantees and predictability are all but absent due to the lack of
support for reservations in most local resource managers of the sites making up grids, the variability in the grid workloads, the variability in the available grid resources due to failures and to the background load of local users, and the variability of application runtimes. It is the purpose of this research project to answer the fundamental question to what extent grid schedulers can be built that do give performance guarantees to applications. We will therefore explore novel methods for performance predictions (data-mining techniques, confidence levels, failure inclusion), for application-level and Virtual-Organization-level scheduling (combining malleability and co-allocation in their interface to grid schedulers), and for grid schedulers (overdimensioning, job access control). We will assess these methods with statistical techniques, simulations, implementations in the context of the KOALA grid scheduler developed in Delft, and experimentation in the new DAS3 wide-area computer system which is currently being installed.
The research of PhD student 1 (to be employed by LIACS) will focus on information models for disseminating performance predictions in grids, obtained by statistical data-mining
techniques on performance data…detalii [sursa]