分布式全局优化(DGO)[13]在MP-1和NCUBE并行计算机上的并行实现表明，该算法的性能有近似O(n)的提高。因此，在并行处理器上实现DGO可以弥补该算法的唯一缺点，即随着维数的增加，执行时间的O(n2)。DGO的并行实现的加速系数是以SPARC IV计算机上相同问题的顺序执行时间来衡量的。该算法在MP-1上的SIMD实现的提速效果最好，对于一个n=9的优化问题，总提速为126。该优化问题分布在Mas-Par的128个PE上。
原文：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.