The Chare Kernal Parallel Programming System

并行化编译器的所有常用方法，高级 语言，如函数式语言和显式并行 语言-需要共同的支持基础。 这项工作将 将这种支持封装在一种语言中， 管理决策和机器细节，并开发一个运行时 支持系统在不同类别的MIMD机器上实现 这种语言。 然后，该语言可以由其他 并行编程的高级方法， 高效的后端 它也可以用于高效应用 编程. 语言和运行时系统将支持动态 负载平衡和中小计算粒度，以满足 上述目标。 为了表现力和效率， 语言将支持一组丰富的原语， 信息共享的形式。 该语言的运行时支持系统已经实现 已经在分布式内存机器上，如iPSC/2， 记忆机器，如顺序对称，和一个初步的编译器 已经写好了。 这些机器的性能结果已经 在简单的基准上获得，非常令人鼓舞：它们表明 我们可以用许多处理器获得出色的加速比， 成本只有百分之几的开销超过最好的顺序C 程序，在一个处理器上。

All common approaches to parallelizing compilers, high-level languages such as functional languages, and explicitly parallel languages - require a common base of support. This work will encapsulate this support in a language that abstracts over resource management decisions and machine details, and develops a runtime support system on different classes of MIMD machines for implementing this language. The language can then be used by implementors of other high level approaches to parallel programming as a universal and efficient back-end. It can also be used for efficient application programming. The language and the runtime system will support dynamic load balancing, and small to medium computational grainsize, to meet the above objectives. For expressiveness as well as efficiency, the language will support a rich set of primitives for expressing specific forms of information sharing. The runtime support system for the language has been implemented already on distributed memory machines such as iPSC/2, and shared memory machines such as Sequent Symmetry, and a preliminary compiler has been written. Performance results on these machines have been obtained on simple benchmarks and are very encouraging: they show that we can obtain excellent speedups with many processors, while costing only a few percent overhead over the best sequential C programs, on one processor.