Collaborative Research: Hierarchically Parallel Algorithms for Portable and Scalable Performance

协作研究：可移植和可扩展性能的分层并行算法

• 批准号: 9123452
• 负责人: Ahmed Sameh
• 金额: --
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-05-15 至 1992-06-16
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9123452&HistoricalAwards=false
• 关键词: Collaborative; Research; Hierarchically; Parallel; Algorithms

The goal of this research proposed is to develop parallel sparse system solvers for symmetric indefinite and non-symmetric linear systems such as those occurring in computational fluid dynamics, develop parallel techniques for solving time-dependent problems, and construct a rapid prototyping environment for developing and experimenting with algorithms in sparse matrix computations on shared and distributed memory multiprocessors. In particular, the following will be examined: o parallel solution schemes for solving Stokes-like linear problems arising in CFD and other augmented Lagrangian problems such as interior point methods of linear programming, o incomplete Newton methods with Krylov or row projection iterative solvers for the inner iteration, o solution of time-dependent problems using high-order parallel methods in time, o defining and developing sparse matrix primitives analogous to the highly effective BLAS-3's for dense computations, and o implementing sparse factorization and solution schemes. The goal is portable efficiency and scalability, by exploiting parallelism on multiple levels. This in turn will allow the work to be used across a wide spectrum of existing and future computer architectures, instead of simply a particular machine.

本研究的目标是为计算流体力学中出现的对称不定和非对称线性系统开发并行稀疏系统求解器，开发求解时间相关问题的并行技术，并为在共享和分布式存储多处理器上开发和实验稀疏矩阵计算的算法而构建一个快速原型环境。具体地，将检查以下内容：用于解决CFD中出现的类Stokes线性问题和诸如线性规划的内点法之类的其他增广拉格朗日问题的并行求解方案，O内部迭代采用Krylov或行投影迭代求解器的不完全牛顿方法，O用时间上的高阶并行方法求解时间相关问题，O定义和开发类似于用于密集计算的高效BLAS-3‘S的稀疏矩阵基元，以及实现稀疏因式分解和解决方案。目标是通过在多个级别上利用并行性来实现可移植的效率和可伸缩性。这反过来将允许工作在现有和未来的计算机体系结构的广泛范围内使用，而不仅仅是一台特定的机器。