Reliable and Scalable Software for Linear Algebra Computations on High End Computers

该项目旨在通过改进两个广泛使用的标准库LAPACK和ScaLAPCK来解决高性能计算软件支持不足的问题，这两个标准库都提供了数值线性代数内核。通过算法研究、正在进行的用户和供应商调查(网址：icl.cs.utk.edu/laapack-Survey.html)以及对新架构和现代编程语言的需求和机会的预测，对当前版本进行了以下重大改进。使用新的、改进的算法。提高了易用性。性能调整。提高了可靠性和支持能力。首先，新的最先进的算法将提高速度、精度和内存效率。其次，利用现代编程语言功能的改进的用户界面对于更好地易用性以及隐藏一些底层的复杂的、可能是分布式的数据结构非常重要。第三，这两个库的性能关键取决于许多与机器相关的参数，这些参数的设置可以受益于在ATLAS项目中非常成功地开发的自动调优技术。最后，对LAPACK和ScaLAPACK的持续支持和维护有巨大的需求，需要安装一种正式的机制，用于用户反馈、跟踪错误、版本管理和简化安装。更广泛的影响：LAPACK和ScaLAPACK已经被许多供应商用作他们自己的库的基础：SGI/Cray、IBM、HP-Convex、Fujitsu、NEC、NAG和IMSL，以及Mathworks(Matlab的生产者)。因此，拟议的改革将产生很大影响。此外，本提案中描述的大多数算法都是最近才出现的，这意味着还没有任何适合教育的易于理解的描述。作为项目文件的一部分，将编写适合课堂教学和广泛教育宣传的辅导材料。LAPACK和ScaLAPACK的发展是PI之间漫长而成功的合作历史的一部分。此外，对于目前的改进，许多外部合作者提供了从软件和想法到编程和开发帮助的各种支持。

This project aims to address the issue of inadequate software support for High Performance Computing by improving two widely used standard libraries, LAPACK and ScaLAPCK, both of which provide numerical linear algebra kernels. By a combination of algorithmic research, an on-going user and vendor survey (at icl.cs.utk.edu/lapack-survey.html), and anticipation of the demands and opportunities of new architectures and modern programming languages, the following key improvements to the current versions have been identified. The use of novel, improved algorithms. Improved ease of use. Performance Tuning. Improved reliability and support. First, new state-of-the-art algorithms will improve speed, accuracy, and memory efficiency. Second, improved user interfaces that exploit features of modern programming languages are important for better ease of use and also hide some of the underlying complex, possibly distributed, data structures. Third, the performance of both libraries crucially depends on a number of machine-dependent parameters whose setting can benefit from automatic tuning techniques developed very successfully in the ATLAS project. Last, there is a huge demand for ongoing support and maintenance of both LAPACK and ScaLAPACK, and there is a need for installing a formal mechanism for user feedback, for tracking bugs, for version management, and facilitated installation. Broader Impacts: LAPACK and ScaLAPACK have been adopted by many vendors as the basis of their own libraries: SGI/Cray, IBM, HP-Convex, Fujitsu, NEC, NAG and IMSL, and the Mathworks (producers of Matlab). For this reason, the proposed changes will have a large impact. Furthermore, recent origin of most of the algorithms described in this proposal means that there are not yet any easily accessible descriptions suitable for education. As part of the project documentation, tutorial material will be developed that is suitable for classroom instruction and wide educational outreach. The development of LAPACK and ScaLAPACK is part of a long and successful history of collaboration between the PIs. In addition, for the current improvements, numerous outside collaborators have offered support ranging from software and ideas to help in programming and development.