Publication

Preemptive open shop scheduling with multiprocessors: polynomial cases and applications

Dominique de Werra
2004
Reports

Abstract

This paper addresses a multiprocessor generalization of the preemptive open-shop scheduling problem. The set of processors is partitioned into two groups and the operations of the jobs may require either single processors in either group or simultaneously all processors from the same group. We consider two variants depending on whether preemptions are allowed at any fractional time point or only at integral time points. We shall show that the former problem can be solved in polynomial time, and provide sufficient conditions under which the latter problem is tractable. Applications to course scheduling and hypergraph edge coloring are also discussed.

Official source

https://infoscience.epfl.ch/entities/publication/a9bb2f5d-3985-4f3f-87f8-b50c9e06fc1d

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Dominique de Werra
2004
Reports

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/a9bb2f5d-3985-4f3f-87f8-b50c9e06fc1d

About this result

Related concepts (32)

Scheduling (computing)

In computing, scheduling is the action of assigning resources to perform tasks. The resources may be processors, network links or expansion cards. The tasks may be threads, processes or data flows. The scheduling activity is carried out by a process called scheduler. Schedulers are often designed so as to keep all computer resources busy (as in load balancing), allow multiple users to share system resources effectively, or to achieve a target quality-of-service.

Pseudo-polynomial time

In computational complexity theory, a numeric algorithm runs in pseudo-polynomial time if its running time is a polynomial in the numeric value of the input (the largest integer present in the input)—but not necessarily in the length of the input (the number of bits required to represent it), which is the case for polynomial time algorithms. In general, the numeric value of the input is exponential in the input length, which is why a pseudo-polynomial time algorithm does not necessarily run in polynomial time with respect to the input length.

Polynomial-time reduction

In computational complexity theory, a polynomial-time reduction is a method for solving one problem using another. One shows that if a hypothetical subroutine solving the second problem exists, then the first problem can be solved by transforming or reducing it to inputs for the second problem and calling the subroutine one or more times. If both the time required to transform the first problem to the second, and the number of times the subroutine is called is polynomial, then the first problem is polynomial-time reducible to the second.

Related publications (1)

Preemptive open shop scheduling with multiprocessors: polynomial cases and applications

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Porting a Legacy Global Lagrangian PIC Code on Many-Core and GPU-Accelerated Architectures