Publication | Closed Access
An empirical study of static load balancing algorithms
49
Citations
7
References
2002
Year
Unknown Venue
Cluster ComputingLoad Balancing (Computing)EngineeringDynamic Resource AllocationDistributed AlgorithmsCloud Load BalancingStatic LoadParallel AlgorithmsData ScienceSystems EngineeringCurrent AlgorithmsParallel ComputingCombinatorial OptimizationMassively-parallel ComputingGraph AlgorithmsLoad BalancingComputer ScienceAvailable GraphTheory Of ComputingScientific ComputationsParallel ProcessingCloud ComputingParallel Performance EvaluationParallel Programming
Empirically compares a variety of current algorithms used to map scientific computations onto massively parallel computers. The comparison is performed using Chaco, a publicly available graph partitioning code written by the authors. Algorithms are evaluated in terms of both computing cost and quality of partition, as judged by the execution time of the parallel application.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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