Tools for the Development of Memory-Efficient Sparse Linear Solvers

开发内存高效的稀疏线性解算器的工具最近在硬件和算法开发方面的进步增加了内存访问对大规模线性代数应用程序运行时间的影响。PI建议创建工具，为代码开发人员提供准备代码的内存成本信息以及旨在降低这些成本的软件构建块。首先，将提供一个框架，用于实现稀疏基本线性代数子程序序列的内存高效实现，这些子程序通常构成稀疏线性求解器。其次，将开发一组用于线性代数软件的内存使用预测的指标，并在这些指标的基础上构建一个自动化预测过程的工具。最后，牢记代码的性能最终取决于它是如何编译的，我们将对编译器及其生成的可执行文件的性能进行全面研究。

Tools for the Development of Memory-Efficient Sparse Linear SolversRecent advances in both hardware and algorithm development have increasedthe effect of memory access on the runtime of large scale linear algebraapplications. The PI proposes to create tools that will provide the codedeveloper with information about memory costs of codes in preparationas well as with software building blocks designed to lessen those costs.First, a framework for memory-efficient implementation of the sequences ofsparse Basic Linear Algebra Subprograms that typically constitute a sparselinear solver will be provided. Second, a collection of metrics for theprediction of memory usage of linear algebra software will be developed.Working from those metrics, a tool to automate the prediction processwill be built. Finally, keeping in mind that the performance of a codeultimately depends on how it compiles, a comprehensive study of compilersand the performance of the executables they produce will be carried out.