摘要
分析了并行优化算法中同步运算与异步运算的优缺点,提出完全异步的PGD算法,并且在一定的条件下,给出了算法的收敛性证明。最后结合大规模分布式并行计算机系统曙光-2000做出数值试验,结果说明异步的并行优化算法的效率高于同步的算法。
The paper analyzes the advantages and disadvantages of synchronous and asynchronous operations in parallel optimization algorithm, and presents the complete asynchronous PGD algorithm and under a certain condition, the proof of its global convergence is given. Finally, numerical tests are provided combined with the distributed large-scale parallel computer system, Dawning 2000, and its results show that the efficiency of asynchronous parallel optimization algorithm is better than that of its synchronous counterpart.
出处
《山东科技大学学报（自然科学版）》
CAS
2006年第4期110-112,共3页
Journal of Shandong University of Science and Technology(Natural Science)
基金
国家自然科学基金资助项目(10571109)
关键词
无约束非线性最优化问题
并行梯度分配算法
加速比
unconstrained nonlinear optimization
parallel gradient distribution
speedup ratio
