Understanding and Improving Memory System Performance via a New Approach to Cache Analysis and Access Ordering

通过缓存分析和访问排序的新方法了解和提高内存系统性能

• 批准号: 0331767
• 负责人: Sally McKee
• 金额: --
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-12-01 至 2003-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0331767&HistoricalAwards=false
• 关键词: Understanding; Improving; Memory; System; Performance

ABSTRACTTitle: Understanding and Improving Memory System Performance via a New Approach to Cache Analysis and Access orderingPI: Sally McKee, University of UtahMicroprocessor speed is increasing much faster than memory system speed: both speed-growth curves are exponential, but they represent diverging exponentials. This proposed research strives to develop a comprehensive approach to bridging the processor/memory performance gap by developing better measures of performance, better tools for observing memory system behavior and understanding memory usage patterns, and combined compiler and architectural schemes to exploit these patterns.The first component of this research investigates methods and tools by which to better measure and interpret complex system behavior in the cache and memory hierarchy. The PI and others are developing a new framework for the analysis of caching systems; this new "caches as filters" framework focuses on properties of a memory trace rather than artifacts of a particular memory organization. This research will support the development of the tools and technology necessary to apply the new framework to real problems and systems.The second component of this research investigates combined compiler and architectural approaches to improving memory system performance in modern microprocessors via smarter scheduling of memory activity and hardware support for streaming.

摘要题目：通过缓存分析和访问排序的新方法来理解和提高存储系统的性能pi: Sally McKee，犹他大学微处理器的速度比存储系统的速度增长得快得多：两者的速度增长曲线都是指数增长，但它们代表的是发散的指数。本研究旨在通过开发更好的性能测量、更好的工具来观察内存系统行为和理解内存使用模式，并结合编译器和架构方案来利用这些模式，从而开发一种综合的方法来弥合处理器/内存性能差距。本研究的第一个组成部分调查了在缓存和内存层次结构中更好地测量和解释复杂系统行为的方法和工具。PI和其他人正在开发一个新的框架来分析缓存系统；这个新的“缓存作为过滤器”框架关注的是内存跟踪的属性，而不是特定内存组织的工件。这项研究将支持开发将新框架应用于实际问题和系统所需的工具和技术。本研究的第二个组成部分研究了编译器和架构结合的方法，通过更智能的内存活动调度和对流的硬件支持来提高现代微处理器的内存系统性能。