Auto-tuning Static Schedules for Task Data-flow Applications
Paper i proceeding, 2017
In this work we use the synchronization graph of a task-based parallel application that is produced during compilation and try to automatically tune the scheduling policy on top of any underlying hardware using heuristic-based Genetic Algorithm techniques. This tool is integrated into an actual task-based parallel programming platform called SWITCHES and is evaluated using real applications from the SWITCHES benchmark suite. We compare our results with the execution time of predefined schedules within SWITCHES and observe that the tool can converge close to an optimal solution with no effort from the user and using fewer resources.
University of Cyprus
Pedro Petersen Moura Trancoso
Chalmers, Data- och informationsteknik, Datorteknik
Portland, Oregon, USA,