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Combining Cluster Sampling with Single Pass Methods for Efficient Sampling Regimen Design

机译:将集群采样与单通方法相结合,以实现高效采样方案设计

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Microarchitectural simulation is orders of magnitude slower than native execution. As more elements are accurately modeled, problems associated with slow simulation are further exacerbated. Given these issues, many researchers have devised sampling techniques to reduce simulation time. When cluster sampling techniques are used, care must be taken to remove sampling and non-sampling biases. Researchers have devised clever methods for effectively reducing non-sampling bias, but little work has been proposed for efficient reduction of sampling bias (sampling regimen design). Traditionally, sampling regimen design has been an iterative process that required a full workload simulation for error comparison. In this study, a single-pass simulation technique for sampling regimen design is proposed. Using this method, thousands of sampling regimen candidates can be simultaneously evaluated. With this technique, simulation speed was increased by an average factor of 17 with a maximum increase of 73 times relative to the total workload simulation. Additionally, this technique allows the user to effectively estimate the sample error without running the entire workload.
机译:微体建筑模拟比本机执行的数量较慢。随着更多元素的准确建模,与慢仿真相关的问题进一步加剧。鉴于这些问题,许多研究人员设计了对模拟时间来减少模拟时间的采样技术。使用群集采样技术时,必须注意删除采样和非采样偏差。研究人员设计了有效减少非采样偏差的巧妙方法,但已经提出了很少的工作,以便有效地减少采样偏差(采样方案设计)。传统上,采样方案设计一直是一个迭代过程,需要进行完整的工作负载模拟以进行错误比较。在该研究中,提出了一种用于采样方案设计的单通仿真技术。使用这种方法,可以同时评估数千个采样方案候选者。利用这种技术,仿真速度的平均因子为17,相对于总工作量模拟最大增加73倍。另外,该技术允许用户在不运行整个工作量的情况下有效地估计样本误差。

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