Data Parallel Programming on Diverse Architectures: Tools and Algorithms

不同架构上的数据并行编程：工具和算法

• 批准号: 8906622
• 负责人: Philip Hatcher
• 金额: $ 34.29万
• 依托单位: University of New Hampshire
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-08-15 至 1994-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8906622&HistoricalAwards=false
• 关键词: Data; Parallel; Programming; Diverse; Architectures

This project investigates the power of the synchronous, data- parallel approach to parallel algorithms development. Many numerical and nonnumerical algorithms can be expressed in an elegant fashion using this methodology. This project focuses on C*, a data parallel language development by Thinking Machines Corporation. If C* compilers can be written that allow for the efficient execution of parallel algorithms on the Connection Machine, multicomputers, and shared memory multiprocessors, then there would be a whole class of algorithms for which no reprogramming would be necessary in order to move an application from one parallel architecture to another. Preliminary results are encouraging, and the PIs are in the process of implementing an optimizing C* compiler for hypercube multicomputers. The focus of this project is to build upon earlier successes by improving the efficiency of the compiled programs, implementing an interactive debugger, exploring more data parallel algorithms and the optimization they require, and porting the C* programming environment to different architectures.

这个项目研究了同步、数据并行方法在并行算法开发中的作用。许多数值和非数值算法可以使用这种方法以一种优雅的方式表示。这个项目的重点是C*，一种由思维机器公司开发的数据并行语言。如果可以编写C*编译器，允许在连接机、多计算机和共享内存多处理器上有效地执行并行算法，那么将会有一整类算法，为了将应用程序从一个并行体系结构移动到另一个并行体系结构，不需要重新编程。初步结果令人鼓舞，pi正在为超立方体多计算机实现一个优化的C*编译器。这个项目的重点是通过提高编译程序的效率，实现交互式调试器，探索更多的数据并行算法及其所需的优化，以及将C*编程环境移植到不同的体系结构，从而在早期成功的基础上进行构建。