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» On Advantages of Grid Computing for Parallel Job Scheduling
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CORR
2007
Springer
95views Education» more  CORR 2007»
13 years 7 months ago
Scheduling in Data Intensive and Network Aware (DIANA) Grid Environments
In Grids scheduling decisions are often made on the basis of jobs being either data or computation intensive: in data intensive situations jobs may be pushed to the data and in co...
Richard McClatchey, Ashiq Anjum, Heinz Stockinger,...
EUROPAR
2004
Springer
14 years 1 months ago
Scheduling of MPI Applications: Self-co-scheduling
Scheduling parallel jobs has been an active investigation area. The scheduler has to deal with heterogeneous workloads and try to obtain throughputs and response times such that en...
Gladys Utrera, Julita Corbalán, Jesú...
GRID
2008
Springer
13 years 8 months ago
User- and job-centric monitoring: Analysing and presenting large amounts of monitoring data
For data analysis or simulations (e.g. in particle physics) single users submit hundreds or thousands of jobs to the Grid. This puts a new burden on the users side - keeping an ov...
Henrik Eichenhardt, Ralph Müller-Pfefferkorn,...
IPPS
2000
IEEE
14 years 3 days ago
Buffered Coscheduling: A New Methodology for Multitasking Parallel Jobs on Distributed Systems
Buffered coscheduling is a scheduling methodology for time-sharing communicating processes in parallel and distributed systems. The methodology has two primary features: communica...
Fabrizio Petrini, Wu-chun Feng
CCGRID
2005
IEEE
14 years 1 months ago
User group-based workload analysis and modelling
Knowledge about the workload is an important aspect for scheduling of resources as parallel computers or Grid components. As the scheduling quality highly depends on the character...
Baiyi Song, Carsten Ernemann, Ramin Yahyapour