Multi - Processor Mapping
نویسنده
چکیده
The problem of scheduling a set of tasks to a set of processors can be divided into two categories: job scheduling and scheduling and mapping. In the former category, independent jobs are to be scheduled among the processors of a distributed computing system to optimize overall system performance [1][2]. In contrast, the scheduling and mapping problem requires the allocation of multiple interacting tasks of a single parallel program in order to minimize the completion time on the parallel computer system. While job scheduling requires dynamic run-time scheduling that is not a priori decidable, the scheduling and mapping problem can be addressed in both static as well as dynamic. In static scheduling [2], which is usually done at compile time, the characteristics of a parallel program (such as task processing times, communication, data dependencies, and synchronization requirements) are known before program execution. In dynamic scheduling only, a few assumptions about the parallel program can be made before execution, and thus, scheduling decisions have to be made on-the-fly [3][4]. Finding an optimal scheduling and mapping strategy is an NP-complete problem in general. So heuristics algorithms are proposed which solve the problem under some constraints; i.e, energy constraints [5][6] or memory constraints [7].
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