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To schedule a job , an algorithm has to choose a machine count and assign j to a starting time and to machines during the time interval [, +,). A usual assumption for this kind of problem is that the total workload of a job, which is defined as d ⋅ p j , d {\displaystyle d\cdot p_{j,d}} , is non-increasing for an increasing number of machines.
The scheduler will list all the tasks and their dependencies on each other in terms of execution and start times. The scheduler will produce the optimal schedule in terms of number of processors to be used or the total execution time for the application.
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 idea of work stealing goes back to the implementation of the Multilisp programming language and work on parallel functional programming languages in the 1980s. [2] It is employed in the scheduler for the Cilk programming language, [3] the Java fork/join framework, [4] the .NET Task Parallel Library, [5] and the Rust Tokio runtime. [6] [7]
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 ...
The basic form of the problem of scheduling jobs with multiple (M) operations, over M machines, such that all of the first operations must be done on the first machine, all of the second operations on the second, etc., and a single job cannot be performed in parallel, is known as the flow-shop scheduling problem.
Fork–join is the main model of parallel execution in the OpenMP framework, although OpenMP implementations may or may not support nesting of parallel sections. [6] It is also supported by the Java concurrency framework, [7] the Task Parallel Library for .NET, [8] and Intel's Threading Building Blocks (TBB). [1]
Uniform machine scheduling (also called uniformly-related machine scheduling or related machine scheduling) is an optimization problem in computer science and operations research. It is a variant of optimal job scheduling. We are given n jobs J 1, J 2, ..., J n of varying processing times, which need to be scheduled on m different machines.