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Search results for: MULTIPROCESSOR SCHEDULING
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Shared processor scheduling of multiprocessor jobs
PublicationWe study a problem of shared processor scheduling of multiprocessor weighted jobs. Each job can be executed on its private processor and simultaneously on possibly many processors shared by all jobs. This simultaneous execution reduces their completion times due to the processing time overlap. Each of the m shared processors may charge a different fee but otherwise the processors are identical. The goal is to maximize the total...
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Artificial Neural Network for Multiprocessor Tasks Scheduling
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A polynomial algorithm for some preemptive multiprocessor task scheduling problems.
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A graph coloring approach to scheduling of multiprocessor tasks on dedicated machines with availability constraints
PublicationWe address a generalization of the classical 1- and 2-processor unit execution time scheduling problem on dedicated machines. In our chromatic model of scheduling machines have non-simultaneous availability times and tasks have arbitrary release times and due dates. Also, the versatility of our approach makes it possible to generalize all known classical criteria of optimality. Under these stipulations we show that the problem...
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On-Line Partitioning for On-Line Scheduling with Resource Conflicts
PublicationWithin this paper, we consider the problem of on-line partitioning the sequence of jobs which are competing for non-sharable resources. As a result of partitioning we get the subsets of jobs that form separate instances of the on-line scheduling problem. The objective is to generate a partition into the minimum number of instances such that the response time of any job in each instance is bounded by a given constant. Our research...
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Energy-Aware High-Performance Computing: Survey of State-of-the-Art Tools, Techniques, and Environments
PublicationThe paper presents state of the art of energy-aware high-performance computing (HPC), in particular identification and classification of approaches by system and device types, optimization metrics, and energy/power control methods. System types include single device, clusters, grids, and clouds while considered device types include CPUs, GPUs, multiprocessor, and hybrid systems. Optimization goals include various combinations of...