Strategies for job allocation in a hypercube concurrent computer
Thesis/Dissertation
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OSTI ID:5923068
The author studies the problem of how to effectively use hypercube resources (processor) for the hypercube systems which supports multiple users. When each job arrives at hypercube, the operating system will allocate a dedicate free subcube to it. One way to attack this problem is to try to minimize finishing time of a sequence of jobs. The other way is to try to reduce the fragmentation, like memory fragmentation, occurs after subcubes allocation and release. Several strategies have been studied. These are non-preemptive scheduling, preemptive scheduling, and virtual subcube formation. The problem of scheduling k independent jobs on an n-dimensional hypercube system is to minimize finishing time, where each job J, is associates with a dimension d{sub i} and a processing time t{sub i}, meaning that J{sub i} requires a d{sub i}-dimensional subcube (call J{sub i} a d{sub i}-dimensional job) for t{sub i} units of time. This problem is NP - complete if no preemption is allowed. The author proposes a simple heuristic called LDLPT (Largest Dimension Largest Processing Time) for this problem and analyze its worse -case performance: the ratio of the heuristic finishing time to the optimal does not exceed 2-1/2{sup n-1}. If preemption is allowed, and O(k{sup 2}) algorithm is presented that decides if all k jobs can be finished by a given deadline. Using this algorithm, one may obtain a minimum-finishing-time schedule in polynomial time. The characteristic of the hypercube fragmentation is that even if a sufficient number of processors are available in the hypercube, they do not form a subcube large enough to accommodate an incoming job.
- Research Organization:
- Ohio State Univ., Columbus, OH (USA)
- OSTI ID:
- 5923068
- Country of Publication:
- United States
- Language:
- English
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