Scheduling Multiprocessor Tasks to Minimize Schedule Length
IEEE Transactions on Computers
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SIAM Journal on Discrete Mathematics
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Mathematics of Operations Research
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Discrete Applied Mathematics
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Mathematics of Operations Research
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STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
A polynomial time approximation scheme for general multiprocessor job scheduling (extended abstract)
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Linear-time approximation schemes for scheduling malleable parallel tasks
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
Scheduling Independent Multiprocessor Tasks
ESA '97 Proceedings of the 5th Annual European Symposium on Algorithms
A Simple Linear-Time Approximation Algorithm for Multi-processor Job Scheduling on Four Processors
ISAAC '00 Proceedings of the 11th International Conference on Algorithms and Computation
Semi-normal Schedulings: Improvement on Goemans' Algorithm
ISAAC '01 Proceedings of the 12th International Symposium on Algorithms and Computation
On Minimizing Average Weighted Completion Time: A PTAS for Scheduling General Multiprocessor Tasks
FCT '01 Proceedings of the 13th International Symposium on Fundamentals of Computation Theory
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We study the problem of scheduling a set of n independent tasks on a fixed number of parallel processors, where the execution time of a task is a function of the subset of processors assigned to the task. We propose a fully polynomial approximation scheme that for any fixed Ɛ 0 finds a preemptive schedule of length at most (1 + Ɛ) times the optimum in O(n) time. We also discuss the non-preemptive variant of the problem, and present a polynomial approximation scheme that computes an approximate solution of any fixed accuracy in linear time. In terms of the running time, this linear complexity bound gives a substantial improvement of the best previously known polynomial bound [5].