Hierarchical Lattice Parallelism

当前一代的高性能计算机是分层多处理器机器。这些计算机可以成为解决具有挑战性问题的有效技术。然而，它们的复杂性导致了编写程序时的一系列权衡，从而阻碍了及时实现。特别是，在大多数现有的并行编程模型中内置的平面层次结构假设使得难以在这些机器上表达有效的层次算法。本项目将比较两种编程分层并行机的方法：一种是意识到机器结构的显式分层模型，另一种是抽象通信以隐藏层次结构的模型。我们将通过扩展KeLP2.0框架来研究这两个模型，KeLP2.0框架提供了通过管道屏蔽通信延迟（分层或非分层）的支持。这支持特定于应用程序的重叠技术的设计。研究人员将对几种应用进行详细的性能研究，包括湍流的直接数值模拟（DNS）。这些结果将被合并到KeLP运行时系统中的可选实现策略中。KeLP系统将提供给感兴趣的研究人员，作为进一步研究分层并行编程的可能平台。

The current generation of high-performance computers are hierachical multiprocessor machines. These computers can be an effective technology for solving challenging problems. However, their complexity leads to an array of tradeoffs in writing programs that hinders timely implementation. In particular, the built-in assumptions of a flat hierarchy in most existing parallel programming models makes it difficult to express efficient hierarchical algorithms needed on these machines. This project will compare two approaches to programming hierarchical parallel machines: an explicitly hierarchical model that is aware of the machine's structure, and a model that abstracts the communication to hide the hierarchy. Both models will be investigated by extending the KeLP2.0 framework, which provides support for masking communication latency (either hierarchical or not) by pipelining. This supports the design of application-specific overlap techniques. The investigators will carry out detailed performance studies of several applications, including Direct Numerical Simulation (DNS) of turbulent flows. The results of these will be incorporated in alternative implementation policies within the KeLP runtime system. The KeLP system will be made available to interested researchers as a possible platform for further investigation in hierarchical parallel programmig.