NSF Young Investigator: Concurrent Object-Oriented Programming Support for Irregular Parallel Applications

NSF 青年研究员：对不规则并行应用程序的并发面向对象编程支持

• 批准号: 9457809
• 负责人: Andrew Chien
• 金额: $ 27.5万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-09-15 至 1998-10-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9457809&HistoricalAwards=false
• 关键词: NSF; Young; Investigator; Concurrent; Object

For parallel computing to become the vehicle of choice for a broad variety of computing problems, not just regular numeric ones, the expression and exploitation of irregular parallelism must be efficient. This research addresses the major challenge, programmability, by 1) supporting the expression of irregular parallelism with concurrent object-oriented programming languages and 2) supporting the exploitation of irregular parallelism with high performance routing networks and network interfaces. Concurrent object-oriented languages enable programmers to hide concurrency and distribution, allowing incremental parallelization and also confining the complexity arising from irregular parallelism to a small part of the program. However, efficient implementation requires aggressive locality and grain size optimizations in the underlying compiler and runtime system. This project is exploring aggressive type inference and dynamic data structure analysis techniques to enable such program optimizations. Type inference is used to discover program control flow, and dynamic data structure analysis approximates the program storage map. Runtime techniques are also being explored. These techniques are embodied in the publicly available Illinois Concert System. This system is being used to develop a number of parallel application programs.

为了使并行计算成为各种计算问题的首选工具，而不仅仅是常规数值问题，非常规并行的表达和利用必须是有效的。 这项研究解决了主要的挑战，可编程性，1）支持表达不规则并行与并发面向对象的编程语言和2）支持开发不规则并行与高性能路由网络和网络接口。 并发面向对象语言使程序员能够隐藏并发和分布，允许增量并行化，并将不规则并行产生的复杂性限制在程序的一小部分。 然而，高效的实现需要在底层编译器和运行时系统中进行积极的局部性和粒度优化。 这个项目正在探索积极的类型推理和动态数据结构分析技术，以实现这样的程序优化。 类型推理用于发现程序控制流，动态数据结构分析近似程序存储映射。 也在探索新的技术。 这些技术体现在公开可用的伊利诺伊州音乐会系统。 该系统已被用于开发多个并行应用程序。