Statistical Techniques for Computer Performance Evaluation

计算机性能评估的统计技术

• 批准号: 0429806
• 负责人: Lizy John
• 金额: --
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0429806&HistoricalAwards=false
• 关键词: Statistical; Techniques; Computer; Performance; Evaluation

Statistical Techniques for Computer Performance EvaluationAbstractThe proposed research seeks to investigate mathematical and formal methods for evaluating new computer system architectures. It involves adapting fundamental techniques from existing statistical and mathematical theory to permit the use of simulation-based evaluation in exploratory design. Specific issues to be studied deal with workload compression using sampling, and benchmark synthesis based on workload and parameterized models. Detailed full-system simulation with real-world workloads is the preferred method of performance analysis in the microprocessor and computer system design community today, in preference to analytic modeling or the use of synthetic benchmarks. However, the very large simulation times taken by this methodology prohibits good design space exploration needed for increasingly complex designs. In addition, the project will address the training of computer architecture students in neglected areas of statistical or analytical modeling techniques.

计算机性能评估的统计技术摘要拟议的研究旨在研究用于评估新的计算机系统体系结构的数学和形式方法。它涉及采用现有统计和数学理论的基本技术，以允许在探索性设计中使用基于模拟的评估。要研究的具体问题涉及使用采样的工作负载压缩，以及基于工作负载和参数化模型的基准合成。在当今微处理器和计算机系统设计领域，使用真实工作负载进行详细的全系统模拟是性能分析的首选方法，而不是使用分析建模或使用合成基准。然而，这种方法所花费的大量模拟时间阻碍了越来越复杂的设计所需的良好设计空间探索。此外，该项目将解决计算机体系结构专业学生在被忽视的统计或分析建模技术领域的培训问题。