ITR/NGS: A Software Infrastructure for Computational Biology and Physics

ITR/NGS：计算生物学和物理学的软件基础设施

• 批准号: 0326350
• 负责人: Lawrence Rauchwerger
• 金额: --
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-11-01 至 2008-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0326350&HistoricalAwards=false
• 关键词: ITR; NGS; Software; Infrastructure; Computational

STAPL (the Standard Template Adaptive Parallel Library) is a library of ISO Standard C++ components with interfaces similar to the (sequential) ISO C++ standard library, and encouraging results have been obtained with a shared memory prototype. This project will extend this library significantly in the range of systems it can support (notably systems without shared memory), the range of optimization performed, and the degree to which a program is automaticall y adapted to its run-time environment and workload. The project will extend the STAPL library, redesign the STAPL run-time system, and build a compiler to allow high-level (source-level) optimizations and to generate information and code needed by the run-time system for adaptive algorithms and lower-level optimizations. Thus, STAPL will be a framework for highly-optimizable, adaptable, and portable parallel computations. In addition to the usual vector-based operations, it will support parallel use of less regular structures (such as lists and sparse matrices) and ease the evolution of programs from a serial to a parallel environment. Importantly, this will be done in ways that take advantage of the huge investment in mainstream programming environments and tools and make STAPL's parallel computation facilities accessible to mainstream programmers.

STAPL（Standard Template Adaptive Parallel Library）是一个ISO标准C++组件库，其接口类似于（顺序）ISO C++标准库，并且已经通过共享内存原型获得了令人鼓舞的结果。 该项目将在它可以支持的系统范围（特别是没有共享内存的系统），执行的优化范围以及程序自动适应其运行时环境和工作负载的程度方面显着扩展该库。该项目将扩展STAPL库，重新设计STAPL运行时系统，并建立一个编译器，以允许高级（源代码级）优化，并生成运行时系统所需的信息和代码，用于自适应算法和较低级别的优化。因此，STAPL将是一个高度优化，适应性强，可移植的并行计算框架。除了有 通常的基于向量的操作，它将支持并行使用不太规则的结构（如列表和稀疏矩阵），并简化程序从串行到并行环境的演变。重要的是，这将以利用主流编程环境和工具的巨大投资的方式来实现，并使主流程序员可以使用STAPL的并行计算设施。