Statistical Techniques for Computer Performance Evaluation

计算机性能评估的统计技术AbstractThe拟议的研究旨在调查评估新的计算机系统架构的数学和形式化的方法。它涉及适应现有的统计和数学理论的基本技术，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量压缩，以及基于工作量和参数化模型的基准综合。 详细的全系统仿真与真实世界的工作负载是当今微处理器和计算机系统设计社区的首选性能分析方法，而不是分析建模或使用合成基准。然而，这种方法所需的非常大的仿真时间，阻止了越来越复杂的设计所需的良好的设计空间探索。此外，该项目将解决在统计或分析建模技术的被忽视的领域的计算机体系结构的学生的培训。

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.