Confidence in Computer Architecture Modeling and Simulation

计算机体系结构建模和模拟中的可信度这项工作研究了基于抽样的计算机体系结构模拟的统计基础，目的是提供模拟数据的可信度的量化度量。采样技术可以加快模拟速度，但由于需要重新创建执行上下文以确保有效性，因此变得复杂。该项目将：利用已知的抽样误差特征来研究误差来源，研究针对各种系统特征的适当的样本设计，当程序状态具有未知分布时确定有效的技术，以及表征现有的当前状态估计技术并开发新的方法。

Confidence in Computer Architecture Modeling and SimulationAbstractThe work addresses the statistical underpinnings of sampling-based simulation of computer architectures, with the aim of providing quantitative measures of confidence of simulation data. Sampling techniques can speed up simulation but are complicated by the need to recreate the execution context to ensure validity. This project will: investigate the sources of error using known sampling error characterizations, study proper sample design for various system features, determine effective techniques when program state has unknown distributions, and characterize existing current-state estimation techniques and develop new approaches.