A Compositional Approach to Scalable Parallel Software

高端计算系统需要研究重要的、计算密集型的应用，如科学模拟、多媒体流处理和地理信息系统。虽然这些系统仍在发展，但很明显，它们将非常庞大和复杂，有数万到数十万个处理器提供系统和资源的深层层次结构。这项研究将开发理论、技术和构建块，这些理论、技术和构建块可以被领域科学家使用，他们不是并行编程专家，可以为这样复杂的系统编写高效的应用程序。因此，这项研究的结果应该会大大增加高端机器的潜在用户的数量，包括基本上所有的科学家，他们的问题可以利用这些系统。这项研究所产生的软件，包括计算生物学和物理学中重要问题的试验台应用程序，将向公众开放。组合是构建和推理大型复杂系统的一种自然方式。本研究将开发用于构建应用程序、优化和控制应用程序及其对系统资源的使用的组合策略。该项目将使用STAPL（标准模板自适应并行库）基础设施来并行c++代码。STAPL包括一组通用并行算法和分布式容器。在这项研究中，STAPL现有的自适应能力将进一步完善，并将开发新的技术，用于组合性能建模，并提供可为程序中的每个容器或算法实例单独设置的容错能力。现代编程接口将基于并行操作的组合来设计，这些并行操作将以STAPL和c++ 0x中的范围抽象为模型，并由高级编译器直接支持。

High-end computing systems are needed to study important, compute-intensive applications such as scientific simulations, multimedia stream processing, and geographical information systems. While these systems are still evolving, it is clear that they will be extremely large and complex, with tens to hundreds of thousands of processors providing a deep hierarchy of systems and resources. This research will develop the theory, techniques, and building blocks that can be used by domain scientists who are not expert parallel programmers to compose efficient applications for such complex systems.Hence, the outcomes of the research should greatly increase the number of potential users of high-end machines to include essentially all scientists whose problems could take advantage of such systems. The software resulting from this research, including the testbed applications for important problems in computational biology and physics, will be made publically available.Composition is a natural way to construct and reason about large, complex systems. This research will develop compositional strategies for building applications and for optimizing and controlling the application and its use of system resources.This project will use the STAPL (the Standard Template Adaptive Parallel Library) infrastructure for parallel C++ code. STAPL includes of a collection of generic parallel algorithms and distributed containers. In this research, STAPL's existing adaptive capabilities will be further refined and novel techniques will be developed for compositional performance modeling and for providing fault-tolerance capabilities that can be set individually for each container or algorithm instance in the program. A modern programming interface will be designed based on composition of parallel operations that will be modeled on the range abstractions in STAPL and C++0x and directly supported by a high-level compiler.