TSS: Applying two-stage sampling in micro-architecture simulations

Zhibin Yu, Hai Jin, Jing Chen, L. John
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引用次数: 8

Abstract

Accelerating micro-architecture simulation is becoming increasingly urgent as the complexity of workload and simulated processor increases. This paper presents a novel two-stage sampling (TSS) scheme to accelerate the sampling-based simulation. It firstly selects some large samples from a dynamic instruction stream as candidates of detail simulation and then samples some small groups from each selected first stage sample to do detail simulation. Since the distribution of standard deviation of cycle per instruction (CPI) is insensitive to microarchitecture, TSS could be used to speedup design space exploration by splitting the sampling process into two stages, which is able to remove redundant instruction samples from detail simulation when the program is in stable program phase (standard deviation of CPI is near zero). It also adopts systematic sampling to accelerate the functional warm-up in sampling simulation. Experimental results show that, by combining these two techniques, TSS achieves an average and maximum speedup of 1.3 and 2.29 over SMARTS, with the average CPI relative error is less than 3%. TSS could significantly accelerate the time consuming iterative early design evaluation process.
TSS:在微架构模拟中应用两阶段采样
随着工作负载和仿真处理器复杂性的增加,加速微体系结构仿真变得越来越迫切。本文提出了一种新的两阶段采样(TSS)方案来加速基于采样的仿真。首先从动态指令流中选取一些大样本作为详细仿真的候选样本,然后从每个选取的第一阶段样本中选取一些小样本进行详细仿真。由于CPI (cycle per instruction)的标准差分布对微体系结构不敏感,TSS可以通过将采样过程分为两个阶段来加速设计空间的探索,当程序处于稳定的程序阶段(CPI的标准差接近于零)时,可以从细节仿真中去除冗余的指令样本。在采样仿真中采用系统采样加速功能预热。实验结果表明,结合这两种技术,TSS比SMARTS平均和最大加速分别提高了1.3和2.29,平均CPI相对误差小于3%。TSS可以显著加快耗时的迭代早期设计评估过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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