Language Support for Parallel Scientific Computation on Distributed Memory Multiprocessors

该奖项支持在分布式内存多处理器(MIMD)上支持并行科学计算的编程语言支持的持续研究。越来越明显的是，这类并行计算机将在未来的大规模科学计算中发挥重要作用。然而，目前这样的计算机很难编程。这项研究的目标是在不牺牲结果代码的运行时效率的情况下，使对这些计算机进行大规模并行科学计算的编程变得更加容易和自然。第二个目标是使这样的程序可以在不同的分布式内存多处理器之间移植。主要问题是高级语言对使用动态数据和进程结构的并行数值算法的支持。研究人员将与这些计算机的(潜在)用户科学家进行广泛的互动。这种互动旨在增加对强调科学家并行算法的范例的理解，将这些范例整合到编程语言研究中，并评估这项研究在多大程度上满足了他们的需求。//

This award supports continued research into programming language support for parallel scientific computation on (MIMD) distributed memory multiprocessors. It is becoming clear that this class of parallel computers will play an important role in the future of large scale scientific computation. Currently, however, such computers are very difficult to program. The goal of this research is to make it considerably easier and more natural to program these computers for large scale parallel scientific computation, without sacrificing the run-time efficiency of the resultant code. A second goal is to make such programs portable between different distributed memory multiprocessors. The main issues are high-level language support for parallel numerical algorithms that use dynamic data and process structures. The researchers will interact extensively with scientists who are (potential) users of these computers. This interaction is aimed at increasing understanding of the paradigms that underline the scientists' parallel algorithms, integrating these paradigms into programming language research, and assessing how well this research is meeting their needs.//