Computing and Informatics / Computers and Artificial Intelligence · 2008 · 13 citations · 0 references
Cluster ComputingEngineeringComputer ArchitectureData GridTransparent WayGrid NetworkParallel SoftwareWorkload Management SystemSystems EngineeringModeling And SimulationParallel ComputingHybrid ProgrammingComputer EngineeringComputer ScienceGrid ApplicationGrid ClustersSmart GridEdge ComputingParallel Performance EvaluationCloud ComputingGrid ComputingParallel Programming
Grids as infrastructures offer access to computing, storage and other resources in a transparent way. The user does not have to be aware where and how the job is being executed. Grid clusters in particular are an interesting target for running computation-intensive calculations. Running MPI-parallel applications on such clusters is a logical approach that is of interest to both computer scientists and to engineers. This paper gives an overview of the issues connected to running MPI applications on a heterogenous Grid consisting of different clusters located at different sites within the Int.EU.Grid project. The role of a workload management system (WMS) for such a scenario, as well as important modifications that need to be made to a WMS oriented towards sequential batch jobs for better support of MPI applications and tools are discussed. In order to facilitate the adoption of MPI-parallel applications on heterogeneous Grids, the application developer should be made aware of performance problems, as well as MPI-standard issues within its code. Therefore tools for these issues are also supported within Int.EU.Grid. Also, the special case of running MPI applications on different clusters simultaneously as a more Grid-oriented computational approach is described.