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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 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.
This answer requires a reliable estimation (modeling) of the program workload and the capacity of the parallel system. The first pass of the compiler performs a data dependence analysis of the loop to determine whether each iteration of the loop can be executed independently of the others.
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 ...
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]
Flow Shop Ordonnancement. Flow-shop scheduling is an optimization problem in computer science and operations research.It is a variant of optimal job scheduling.In a general job-scheduling problem, we are given n jobs J 1, J 2, ..., J n of varying processing times, which need to be scheduled on m machines with varying processing power, while trying to minimize the makespan – the total length ...
Parallelism executes tasks independently on multiple CPU cores, while concurrency manages multiple tasks on one or more cores, switching between threads or time-slicing without completing each one. Programs may exhibit parallelism only, concurrency only, both parallelism and concurrency, neither. [6] Parallelism vs concurrency
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).