分布式全局優化(DGO)[13]在MP-1和NCUBE并行計算機上的并行實作表明，該算法的性能有近似O(n)的提高。是以，在并行處理器上實作DGO可以彌補該算法的唯一缺點，即随着維數的增加，執行時間的O(n2)。DGO的并行實作的加速系數是以SPARC IV計算機上相同問題的順序執行時間來衡量的。該算法在MP-1上的SIMD實作的提速效果最好，對于一個n=9的優化問題，總提速為126。該優化問題分布在Mas-Par的128個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.