SHF: Small: Generation of Scientific Software Libraries

SHF：小型：科学软件库的生成

• 批准号: 1421211
• 负责人: Don Batory
• 金额: $ 51.55万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-15 至 2020-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1421211&HistoricalAwards=false
• 关键词: SHF; Small; Generation; Scientific; Software

Making experts more productive is critically important to software development. This is particularly so in Scientific Computing (SC) where experts are rare and whose task is to develop software libraries on which SC research in academia, government labs, and industry depends. This project strives to create programming practices and tools that will revolutionize library development in SC. By encoding expert knowledge about the science, mathematics, and software of a domain, a transformative approach called Design by Transformation (DxT) can automatically generate software that experts would have to write manually. DxT-generation is faster, cheaper, and produces better-trusted code. In dense linear algebra libraries, DxT has exposed errors in manually-written code and found faster algorithms than those produced by experts. This research applies DxT to three new software domains: fault-tolerant dense linear algebra, graph analysis, and tensor computation. While improving the performance of their software libraries will itself have an impact in national labs and industry, the lessons learned about automating software development will have broad effects. SC software is growing more complicated as hardware complexity evolves (e.g., multi-core, many-core, co-processors, and GPUs). Automatic generation will aid experts in being more productive in this increasingly complicated engineering endeavor. It will enable American scientists and engineers to maintain their advantage in scientific library engineering. Further, there is evidence that the DxT approach to engineering has a pedagogical value in teaching students and new engineers about software. Encoding new domains will test these benefits.

提高专家的工作效率对软件开发至关重要。 这在科学计算（SC）中尤其如此，因为科学计算专家很少，他们的任务是开发学术界、政府实验室和工业界的科学计算研究所依赖的软件库。该项目致力于创建编程实践和工具，这将彻底改变SC图书馆的开发。通过编码有关科学，数学和软件领域的专家知识，一种称为转换设计（DxT）的变革方法可以自动生成专家必须手动编写的软件。DxT生成更快、更便宜，并生成更可信的代码。 在密集的线性代数库中，DxT暴露了手工编写的代码中的错误，并找到了比专家编写的算法更快的算法。本研究将DxT应用于三个新的软件领域：容错稠密线性代数，图形分析和张量计算。 虽然提高软件库的性能本身会对国家实验室和行业产生影响，但有关自动化软件开发的经验教训将产生广泛的影响。 随着硬件复杂性的发展，SC软件变得越来越复杂（例如，多核、众核、协处理器和GPU）。自动生成将帮助专家在这个日益复杂的工程奋进中提高生产力。它将使美国科学家和工程师保持他们在科学图书馆工程方面的优势。 此外，有证据表明，DxT工程方法在教授学生和新工程师有关软件方面具有教学价值。 对新域进行编码将测试这些好处。