Software Systems for Irregular Application on Scalable Multiprocessors

该项目将实现系统软件，以支持可伸缩多处理器上的非常规并行程序。具有物理分布式内存的机器提供了实现可伸缩性能的最佳机会，但目前这些机器的编程技术非常繁琐，而且往往效率低下。对于具有不规则数据结构或不规则通信和控制模式的应用程序尤其如此。主要关注的两个问题是数据布局和调度。数据布局是避免通信开销的关键，但好的布局策略在编译期间很难确定，因为它们取决于程序的全局属性和输入数据。类似地，对不规则问题的调度必须适应程序执行期间的不同负载。对于这两个问题，在编译期间做出的决策的不灵活性和在运行时做出的决策的开销之间存在权衡。将开发高级语言机制，允许程序员指定数据布局和调度策略，并使用编译器和运行时支持的组合来实施这些策略。重点将放在不规则的应用上：例如，布局将描述逻辑全局图的子图的放置，而调度原语将允许控制和数据并行。在整个项目期间，将开发用于激励和测试系统工作的应用程序。

This project will implement systems software to support irregular parallel programs on scalable multiprocessors. Machines with physically distributed memory offer the best opportunity for scalable performance, but current programming techniques for these machines are cumbersome and often inefficient. This is particularly true for applications with irregular data structures or irregular patterns of communication and control. Two issues of primary concern are data layout and scheduling. Data layout is critical to avoiding communication overhead, but good layout strategies are difficult to determine during compilation because they depend on global properties of the program and on input data. Similarly, scheduling for irregular problems must adapt to varying loads during program execution. For both problems, there is a trade-off between the inflexibility of decisions made during compilation and the overhead of decisions made at runtime. High level language mechanisms to allow the programmer to specify data layout and scheduling strategies, and implement them using a combination of compiler and runtime support will be developed. The emphasis will be on irregular applications: the layouts, for example, will describe the placement of subgraphs of a logically global graph, and the scheduling primitives will allow for both control and data parallelism. Throughout the project's duration applications to motivate and test the systems work will be developed.