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Statistical performance modeling of modern out-of-order processors using Monte Carlo methods.

机译:使用蒙特卡洛方法的现代故障处理器的统计性能建模。

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摘要

Simulation is an indispensable tool used by computer architects for processor performance research and design. Due to the numerous problems of current performance simulation methods, there exits a pressing need for new modeling techniques that can improve simulation speeds while maintaining accuracy and robustness. It is no longer practical to use only cycle-accurate processor simulation (the predominant simulation method) for design space and performance studies due to its extremely slow speed that is exacerbated by the increasing complexity of today's processors. As a result, designing and researching future processors can be hindered. This work presents an extension to the Monte Carlo processor performance (MCPP) modeling technique that enables the creation of fast, accurate, and robust statistical models of modern out-of-order processors. Using this new method, we show that our MCPP models can achieve highly accurate performance predictions within 7% of measurements and achieve speed-ups of tens of thousands of times over cycle-accurate simulation. As a result, such models can be faithfully used for quick processor performance evaluation studies, bottleneck analysis, and design space exploration. We have successfully validated the new MCPP modeling technique using two models: one for the modern AVID Magny-Cours processor and one for the popular PTLsim cycle-accurate simulator.
机译:仿真是计算机架构师用于处理器性能研究和设计的必不可少的工具。由于当前性能仿真方法存在许多问题,因此迫切需要新的建模技术,该技术可以在保持精度和鲁棒性的同时提高仿真速度。仅使用周期精确的处理器仿真(主要的仿真方法)进行设计空间和性能研究已不再可行,因为它的极慢速度会因当今处理器的日益复杂化而加剧。结果,可能会阻碍设计和研究未来的处理器。这项工作提出了对蒙特卡洛处理器性能(MCPP)建模技术的扩展,该技术可以创建现代无序处理器的快速,准确和健壮的统计模型。使用这种新方法,我们证明了我们的MCPP模型可以在7%的测量范围内实现高度准确的性能预测,并在精确周期的仿真中实现数万倍的加速。结果,这些模型可以忠实地用于处理器性能快速评估研究,瓶颈分析和设计空间探索。我们已经使用两种模型成功验证了新的MCPP建模技术:一种模型用于现代AVID Magny-Cours处理器,另一种模型用于流行的PTLsim周期精确模拟器。

著录项

  • 作者

    Alkohlani, Waleed.;

  • 作者单位

    New Mexico State University.;

  • 授予单位 New Mexico State University.;
  • 学科 Engineering Computer.;Computer Science.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 292 p.
  • 总页数 292
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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