Scheduling of tasks for distributed processors

Authors:
Ravi Mehrotra;Sarosh N. Talukdar
Affiliations:
Electrical and Computer Engineering Department, N.C. State University, Raleigh, North Carolina;Department of Electrical Engineering, Carnegie-Mellon University, Pittsburgh, PA
Venue:
ISCA '84 Proceedings of the 11th annual international symposium on Computer architecture
Year:
1984

Citing 4
Cited 1

Exact and Approximate Algorithms for Scheduling Nonidentical Processors

Journal of the ACM (JACM)
Scheduling independent tasks to reduce mean finishing time

Communications of the ACM
Polynomial complete scheduling problems

SOSP '73 Proceedings of the fourth ACM symposium on Operating system principles
Heuristic programming applied to scheduling problems

Heuristic programming applied to scheduling problems

Non-preemptive time warp scheduling algorithms

ACM SIGOPS Operating Systems Review

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Abstract

The paper describes a technique for estimating the minimum execution time of an algorithm or a mix of algorithms on a distributed processing system. Bottlenecks that would have to be removed to further reduce the execution time are identified. The main applications are for the high level design of special purpose distributed processing systems. The distributed systems are modelled by P, a set of nonidentical processors and R, a set of resources that the processors can use. The algorithms are modelled by T, an ordered set of tasks. The problem of optimally assigning the processors to the tasks while meeting the resource constraints is NP-complete. However, a heuristic using maximum weighted matchings on graphs has been devised that is extremely fast and comes reasonably close to the optimal solutions.