Design and Implementation of an Adaptive Task Mapping Environment for Parallel Programming
نویسندگان
چکیده
Task scheduling is concerned with the allocation of tasks onto underlying physical processors and the determination of the execution order of tasks residing on the same processor. EEcient scheduling of user tasks is critical to system and application performance in parallel programming. This paper proposes a new task mapping environment, ATME, dealing with the generation of an eecient scheduling policy when task computation time and communication data size may change, and when different execution paths through the task model may be followed. ATME manages the task execution by an adaptively-produced scheduling policy which is tailored for an individual user by following usage patterns of previous executions.
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