The Chare Kernal Parallel Programming System

所有并行化编译器、高级语言(如函数式语言)和显式并行语言的常见方法都需要一个公共的支持基础。这项工作将把这种支持封装在一种抽象资源管理决策和机器细节的语言中，并在不同类别的MIMD机器上开发一个运行时支持系统来实现这种语言。然后，并行编程的其他高级方法的实现者可以将该语言用作通用且高效的后端。它还可以用于高效的应用程序编程。该语言和运行时系统将支持动态负载平衡和中小型计算粒度，以满足上述目标。为了表达能力和效率，该语言将支持丰富的原语集，用于表达特定形式的信息共享。该语言的运行时支持系统已经在分布式存储机器如IPSC/2和共享存储机器如序列对称机器上实现，并且已经编写了初步的编译器。在这些机器上的性能结果是在简单的基准测试上获得的，非常令人鼓舞：它们表明，我们可以在使用多个处理器的情况下获得极好的加速比，而在一个处理器上，与最好的连续C程序相比，开销只有几个百分点。

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.