We present a task duplication based scheduling algorithm for shared memory multiprocessors (SMPs), called S2MP (scheduling for SMP), to address the problem of task scheduling. This algorithm employs heuristics to select duplication of tasks so that schedule length is reduced/minimized. The performan
Scheduling algorithm for nonpreemptive multiprocessor tasks
β Scribed by J.-F. Lin; S.-J. Chen
- Publisher
- Elsevier Science
- Year
- 1994
- Tongue
- English
- Weight
- 619 KB
- Volume
- 28
- Category
- Article
- ISSN
- 0898-1221
No coin nor oath required. For personal study only.
β¦ Synopsis
This paper considers the problem of scheduling nonpreemptive multiprocessor tasks in a homogeneous system of processors. The problem proposed in this paper is different from the conventional scheduling problem, where each task requires only "one" processor whenever it is in processing. In our multiprocessor task scheduling problem, tasks can require more than one processor at a time for their processing, that is, tasks in our problem require simultaneously "j" arbitrary processors when they start to be processed, where 1 5 j 5 k and k is a fixed number. Though multiprocessor tanks considered in this paper are assumed to be independent, i.e., the precedence relation does not exist among them, such a problem of scheduling nonpreemptive multiprocessor tasks is NP-complete.
Therefore, a heuristic algorithm is investigated for this kind of problem and the worst performance bounds of the algorithm are also derived.
Keywords-Multiprocessor
task, Largest processing time first scheduling rule, Performance bound.
π SIMILAR VOLUMES
Most papers in the scheduling field assume that a job can be processed by only one machine at a time. Namely, they use a one-job-on-one-machine model. In many industry settings, this may not be an adequate model. Motivated by human resource planning, diagnosable microprocessor systems, berth allocat
A 'standard task graph set' is proposed for fair evaluation of multiprocessor scheduling algorithms. Developers of multiprocessor scheduling algorithms usually evaluate them using randomly generated task graphs. This makes it di cult to compare the performance of algorithms developed in di erent res