论文标题
分布式全局优化（DGO）的并行实施
Parallel Implementation of Distributed Global Optimization (DGO)
论文作者
论文摘要
在MP-1和NCUBE平行计算机上的分布式全局优化（DGO）[13]的并行实现显示，该算法的性能大约增加了O（n）。因此，在并行处理器上实现DGO可以纠正该算法的唯一绘制，该算法是执行时间的O（n2），随着尺寸数量的增加。 DGO的并行实现的速度因子是根据SPARC IV计算机上相同问题的顺序执行时间测量的。最佳速度是通过在MP-1上实现了算法的SIMD实现，总速度为126，对于n = 9的优化问题。此优化问题分布在128 PES MAS-PAR上。
Parallel implementations of distributed global optimization (DGO) [13] on MP-1 and NCUBE parallel computers revealed an approximate O(n) increase in the performance of this algorithm. Therefore, the implementation of the DGO on parallel processors can remedy the only draw back of this algorithm which is the O(n2) of execution time as the number of the dimensions increase. The speed up factor of the parallel implementations of DGO is measured with respect to the sequential execution time of the identical problem on SPARC IV computer. The best speed up was achieved by the SIMD implementation of the algorithm on the MP-1 with the total speedup of 126 for an optimization problem with n = 9. This optimization problem was distributed across 128 PEs of Mas-Par.
