Improving scalability of Bag-of-Tasks applications running on master–slave platforms (original) (raw)
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On clustering DAGs for task-hungry computing platforms
Open Computer Science, 2011
Many modern computing platforms are “task-hungry”: their performance is enhanced by always having as many tasks available for execution as possible. IC-scheduling, a master-worker framework for executing static computations that have intertask dependencies (modeled as dags), was developed with precisely the goal of rendering a computation-dag’s tasks eligible for execution at the maximum possible rate. The current paper addresses the problem of enhancing IC-scheduling so that it can accommodate the varying computational resources of different workers, by clustering a computation-dag’s tasks, while still producing eligible (now, clustered) tasks at the maximum possible rate. The task-clustering strategies presented exploit the structure of the computation being performed, ranging from a strategy that works for any dag, to ones that build increasingly on the explicit structure of the dagbeing scheduled.
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