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In the context of the dataflow process network mapping problem, we propose a parallel solutionmethod based on a semi-greedy heuristic to improve the solution quality of a greedy regret-based mapping algorithm (RBA). In this method, several executions of a randomized version of RBA are performed in parallel togenerate different solutions. We exploit a correlation between solution quality and execution...
In the context of networks of massively parallel execution models, optimizing the locality if inter-process communication is a major performance issue. We propose two heuristics to solve a dataflow process network mapping problem, where a network of communicating tasks is placed into a set of processors with limited resource capacities, while minimizing the overall communication bandwidth between...
Optimization methods generally do not fall into the most suitable algorithms for parallelization on a GPU. However, a relatively good efficiency still can be obtained if the method is properly adapted to the GPU programming model, which is the case for dynamic programming. In this article, we propose a parallelization strategy for thread grouping for dynamic programming in CUDA. We show that parametrizing...
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