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IMPLEMENTATIONS OF ASYNCHRONOUS SELF-ORGANIZING MAPS ON OPENMP AND MPI PARALLEL COMPUTERS

机译:OpenMP和MPI并行计算机上异步自组织地图的实现

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In we presented an asynchronous parallel algorithm for self-organizing maps based on a recently defined energy function which leads to a self-organizing map. We generalized the existing stochastic gradient approach to an asynchronous parallel stochastic gradient method for generating a topological map on a distributed computer system (MIMD). We theoretically proved that our algorithm was convergent and the simulations showed our algorithm was effective. In this paper, we implement this algorithm on practical parallel computers with two different types: open MP and MPI, in the Supercomputing Institution at University of Minnesota. By analyzing the experimental results, we demonstrate the convergence, efficiency and speed-up of our algorithm.
机译:在我们介绍了一种基于最近定义的能量函数的自组织地图的异步并行算法,这导致了自组织地图。我们将现有的随机梯度方法推广到分布式计算机系统(MIMD)上生成拓扑图的异步并行随机梯度方法。理论上我们证明了我们的算法是收敛的,模拟显示我们的算法是有效的。在本文中,我们在明尼苏达大学的超级仿制机构,在具有两种不同类型的实际并行计算机上实现了这种算法。通过分析实验结果,我们展示了我们算法的收敛性,效率和加速。

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