Challenges in CISE: TUNE: System Support for Memory-Friendly Programming

9726370 Trivedi，Kishor董事会，John A.Duke University在CEISE：TUNE：系统对内存友好编程的支持中的挑战基于微处理器的机器中普遍使用的多级内存层次结构使应用程序的性能主要由其内存映射决定，并对其极其敏感，需要内存友好编程：仔细布局数据结构和重组代码以改善数据局部性。从高级算法和数据结构，通过编译时分析和程序重构，到允许应用程序更好地管理存储器层次结构的特殊体系结构原语，用于提高存储器系统性能的技术在不同级别上表现出来。目前，由于缺乏改善数据局部性的自动工具，许多应用程序程序员不得不手动重新构造代码。不幸的是，现代科学计算中的复杂算法需要同样复杂的重组技术。这些技术需要计算机体系结构方面的专业知识，给程序员带来与程序正确性无关的乏味的机器特定细节的负担，并降低了重新构造的代码的可读性、可维护性和可移植性。由于所有这些原因，手动重组任何规模的程序都是站不住脚的，需要某种类型的系统支持。这个项目针对这个问题的所有方面，从开发表示和操作数据局部性的相关数学技术，到实施交互式和自动的数据局部性管理工具，到为未来一代系统提出创新的存储器体系结构。结果系统的有效性将使用代表现代科学计算的程序来演示，包括分而治之的科学计算，例如N体解算器(例如，快速多极)和许多线性代数内核(例如，Strassens的矩阵乘法算法)。

9726370 Trivedi, Kishor Board, John A. Duke University Challenges in CISE: TUNE: System Support for Memory-Friendly Programming The pervasive use of multi-level memory hierarchies in microprocessor-based machines makes the performance of an application primarily determined by and extremely sensitive to its memory mapping, and requires memory-friendly programming: careful layout of data structures and restructuring of code to improve data locality. Techniques for improving memory system performance manifest themselves at various levels, from high-level algorithms and data structures, through compile-time analysis and restructuring of programs, to special architectural primitives that allow an application to better manage the memory hierarchy. The lack of automatic tools for improving data locality currently forces many application programmers to manually restructure their codes. Unfortunately, the sophisticated algorithms seen in modern scientific computing require equally sophisticated restructuring techniques. These techniques require expertise in computer architecture, burden the programmer with tedious machine-specific details unrelated to program correctness, and reduce the readability, maintainability, and portability of the restructured code. For all these reasons, manual restructuring of programs of any significant size is untenable, and some kind of system support is necessary. This project targets all aspects of this problem, from developing the relevant mathematical techniques for representing and manipulating data locality, through implementing interactive and automatic data locality management tools, to proposing innovative memory architectures for future-generation systems. The efficacy of the resulting system will be demonstrated using programs representative of modern scientific computations including divide-and-conquer scientific computations such as N-body solvers (e.g., fastmultipole) and many linear algebra kernels (e.g., Strassens's matrix multiplication algo rithm).