Data Parallel Programming on Diverse Architectures: Tools and Algorithms

这个项目研究了同步、数据- 并行算法开发的并行方法。 许多数值 而非数值算法可以用一种优雅的方式来表达 使用这种方法。 这个项目的重点是C*，一个数据并行 由Thinking Machines Corporation开发。 如果C* 编译器 可以编写，以允许高效执行并行 连接机、多计算机和共享内存上的算法 多处理器，那么就会有一整类的算法， 不需要重新编程就能移动 从一个并行架构到另一个并行架构。 初步结果令人鼓舞，PI正在进行中 实现一个优化的C* 编译器的超立方体多计算机。 该项目的重点是在先前成功的基础上， 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和 他们需要的优化，以及移植C* 编程环境 to different不同architectures架构.

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.