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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.
The algorithms used in scheduling analysis “can be classified as pre-emptive or non-pre-emptive". [1] A scheduling algorithm defines how tasks are processed by the scheduling system. In general terms, in the algorithm for a real-time scheduling system, each task is assigned a description, deadline and an identifier (indicating priority).
That is, EDF can guarantee that all deadlines are met provided that the total CPU utilization is not more than 100%. Compared to fixed-priority scheduling techniques like rate-monotonic scheduling, EDF can guarantee all the deadlines in the system at higher loading. Note that use the schedulability test formula under deadline as period.
This solved the problem of slow interactive response times on multi-core and multi-CPU systems when they were performing other tasks that use many CPU-intensive threads in those tasks. A simple explanation is that, with this patch applied, one is able to still watch a video, read email and perform other typical desktop activities without ...
An interval scheduling problem can be described by an intersection graph, where each vertex is an interval, and there is an edge between two vertices if and only if their intervals overlap. In this representation, the interval scheduling problem is equivalent to finding the maximum independent set in this intersection graph. Finding a maximum ...
A valid schedule for the disjunctive graph may be obtained by finding an acyclic orientation of the undirected edges – that is, deciding for each pair of non-simultaneous tasks which is to be first, without introducing any circular dependencies – and then ordering the resulting directed acyclic graph. In particular, suppose that all tasks ...
Conceptually, it repeatedly selects a source of the dependency graph, appends it to the current instruction schedule and removes it from the graph. This may cause other vertices to be sources, which will then also be considered for scheduling. The algorithm terminates if the graph is empty. To arrive at a good schedule, stalls should be prevented.