Parallel and Large-Scale Nonlinear Programming

这是一个开发非线性算法的项目， 编程，特别是有许多变量的问题， 强调适合并行计算机的算法。 重点 是牛顿式的方法 这项研究的动机是， 成功开发并行算法和软件 无约束优化 该研究主要针对 适用于粗粒度并行计算机的方法，其中每个 处理器本身是中等强大的。 其中包括现有的 英特尔iPSC超立方体和Sequent并行计算等计算机 电脑 大规模非线性规划问题经常出现 然而，在工业、经济和军事应用中， 非线性模型可能难以求解。 本研究旨在 生成易于使用的通用算法（和软件）， 将使用户可以使用并行计算机的能力， 扩展了非线性规划的范围 作为日常的建模工具。

This is a project to develop algorithms for nonlinear programming, particularly problems with many variables, with an emphasis on algorithms suitable for parallel computers. The focus is on Newton-like methods. The research is motivated by earlier success in developing algorithms and software for parallel unconstrained optimization. The research is primarily aimed at methods suitable for coarse-grained parallel computers, where each processor is itself moderately powerful. This includes existing machines such as the Intel iPSC hypercube and the Sequent parallel computers. Large-scale nonlinear programming problems arise frequently in industrial, economic, and military applications, however nonlinear models can be difficult to solve. This research aims to produce easy-to-use, general purpose algorithms (and software) that will make available the power of parallel computers to the users of nonlinear models, extending the range of nonlinear programming as a day-to-day modelling tool.//