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Load sharing in large, heterogeneous distributed systems allows users to access vast amount of computing resources scattered around the system and may provide substantial performance improvements to applications. We discuss the design and implementation issues in Utopia, a load sharing facility speciically built for large and heterogeneous systems. The(More)
The purpose of this paper is to propose effective parallelization strategies for the Ant Colony Optimization (ACO) metaheuristic on Graphics Processing Units (GPUs). The Max–Min Ant System (MMAS) algorithm augmented with 3-opt local search is used as a framework for the implementation of the parallel ants and multiple ant colonies general parallelization(More)
Sun Microsystems, Inc. ("Sun") hereby grants you a fully-paid, non-exclusive, non-transferable, worldwide, limited license (without the right to sublicense), under the Sun's applicable intellectual property rights to view, download, use and reproduce the Specification only for the purpose of internal evaluation, which shall be understood to include(More)
This paper presents a parallel implementation of an ant colony optimization metaheuristic for the solution of an industrial scheduling problem in an aluminum casting center. The usefulness and efficiency of the algorithm, in its sequential form, to solve that particular optimization problem has already been shown in previous work. However, even if this(More)
We present a shared memory approach to the parallelization of the Ant Colony Optimization (ACO) metaheuristic and a performance comparison with an existing message passing implementation. Our aim is to show that the shared memory approach is a competitive strategy for the parallelization of ACO algorithms. The sequential ACO algorithm on which are based(More)
The purpose of this paper is to propose an effective implementation of the Ant Colony Optimization metaheuristic on actual shared-memory parallel computers. We deal with the management of multiple colonies which use a global shared-memory to exchange information. We report considerable speedups on a SMP node of multi-core processors while witnessing(More)
— The purpose of this paper is to propose effective parallelization strategies for Local Search algorithms on Graphics Processing Units (GPU). We consider the distribution of the 3-opt neighborhood structure embedded in the Iterated Local Search framework. Three resulting approaches are evaluated and compared on both speedup and solution quality on a(More)
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