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Using these multicore processors for cluster systems will create systems with thousands of cores and deep memory hierarchies. To efficiently exploit the tremendous parallelism of these hardware platforms, a new generation of programming methodologies is needed. This article proposes a parallel programming methodology exploiting a task-based representation of application software. For the specification of task-based programs, a coordination language is presented, which uses external variables to express the cooperation between tasks. For the actual execution of a task-based program on a specific parallel architecture, different dynamic scheduling algorithms embedded into an execution environment are introduced. 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