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Parallel task scheduling (also called parallel job scheduling [1] [2] or parallel processing scheduling [3]) is an optimization problem in computer science and operations research. It is a variant of optimal job scheduling .
This determines the shortest time possible to complete the project. "Total float" (unused time) can occur within the critical path. For example, if a project is testing a solar panel and task 'B' requires 'sunrise', a scheduling constraint on the testing activity could be that it would not start until the scheduled time for sunrise. This might ...
Optimal job scheduling is a class of optimization problems related to scheduling. The inputs to such problems are a list of jobs (also called processes or tasks) and a list of machines (also called processors or workers). The required output is a schedule – an assignment of jobs to machines. The schedule should optimize a certain objective ...
In distinction, with fork-and-join approaches, the program starts executing on one processor and the execution splits in a parallel region, which is started when parallel directives are encountered; in a parallel region, the processors execute a parallel task on different data. A typical example is the parallel DO loop, where different ...
PERT is a method of analyzing the tasks involved in completing a project, especially the time needed to complete each task, and to identify the minimum time needed to complete the total project. It incorporates uncertainty by making it possible to schedule a project while not knowing precisely the details and durations of all the activities. It ...
Unrelated-machines scheduling is an optimization problem in computer science and operations research. It is a variant of optimal job scheduling . We need to schedule n jobs J 1 , J 2 , ..., J n on m different machines, such that a certain objective function is optimized (usually, the makespan should be minimized).
In computer science, gang scheduling is a scheduling algorithm for parallel systems that schedules related threads or processes to run simultaneously on different processors. Usually these will be threads all belonging to the same process, but they may also be from different processes, where the processes could have a producer-consumer ...
The open-shop scheduling problem can be solved in polynomial time for instances that have only two workstations or only two jobs. It may also be solved in polynomial time when all nonzero processing times are equal: in this case the problem becomes equivalent to edge coloring a bipartite graph that has the jobs and workstations as its vertices, and that has an edge for every job-workstation ...