Toward Software Tools for Memory-Efficient Matrix Algebra

面向内存高效矩阵代数的软件工具

• 批准号: 0830458
• 负责人: Elizabeth Jessup
• 金额: $ 10万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-15 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0830458&HistoricalAwards=false
• 关键词: Toward; Software; Tools; Memory; Efficient

A scientific program is a mathematical one so there are two factorscontributing to its performance. One is the time required to performarithmetic. The other is the time needed to move data through thememory hierarchy of the computer. In today's large applications, thelatter cost often dominates. The work funded by this grant focuses onefficient computational methods for solving the problems in matrix algebrathat arise in a wide variety of science and engineering applications.Codes for such problems are typically constructed as sequences of calls tothe routines known as the Basic Linear Algebra Subprograms (BLAS). Writingprograms in this way promotes readability and maintainability but canbe costly in terms of memory efficiency especially for matrices oflarge order.The grant will be used primarily to support a Ph.D. student who willstudy ways to combine multiple BLAS routines into a single routine thatperforms the functions of more than one BLAS. He will examine ways tocreate composed BLAS via novel algorithms and performance programmingtechniques, developing a general methodology for their creation in theprocess. His work will ultimately form the basis for a tool that createscomposed BLAS automatically. Composed routines can significantly reducethe amount of data read from main memory. Preliminary results includespeedups as large as 90\%.

一个科学计划是一种数学计划，因此有两个因素对其表现构成。 一个是执行操作所需的时间。 另一个是通过计算机的主体层次结构移动数据所需的时间。 在当今的大型应用程序中，Thelters的成本通常会占主导地位。 该赠款资助的工作集中于一种用于解决矩阵代数中问题的计算方法。以这种方式的写作计划可促进可读性和可维护性，但就记忆效率而言，尤其是对于大小写的矩阵而言，赠款将主要用于支持博士学位。将研究多个BLAS例程中的学生将进行单个例程，以表现多个Blas的功能。 他将通过新颖的算法和性能编程技术来研究造物创作的blas的方法，从而为其在进程中创建一种通用方法。 他的工作最终将构成自动创建blas的工具的基础。 组成的例程可以大大减少从主内存中读取的数据量。 初步结果包括高达90 \％的速度。