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TurboSMARTs: Accurate Microarchitecture Simulation Sampling in Minutes

机译:TurboSMARTs:数分钟内精确的微体系结构仿真采样

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Recent research proposes accelerating processor microarchitecture simulation through statistical sampling. Prior simulation sampling approaches construct accurate model state for each measurement by continuously warming large microarchitectural structures (e.g., caches and the branch predictor) while emulating the billions of instructions between measurements. This approach, called functional warming, occupies hours of runtime while the detailed simulation that is measured requires mere minutes. To eliminate the functional warming bottleneck, we propose TurboSMARTS, a simulation framework that stores functionally-warmed state in a library of small, reusable checkpoints. TurboSMARTS enables the creation of the thousands of checkpoints necessary for accurate sampling by storing only the subset of warmed state accessed during simulation of each brief execution window. TurboSMARTS matches the accuracy of prior simulation sampling techniques (i.e., ± 3% error with 99.7% confidence), while estimating the performance of an 8-way out-of-order superscalar processor running SPEC CPU2000 in 91 seconds per benchmark, on average, using a 12 GB checkpoint library.
机译:最近的研究提出通过统计采样来加速处理器微体系结构仿真。现有的模拟采样方法通过连续加热大型微体系结构(例如,缓存和分支预测器),同时模拟测量之间的数十亿条指令,为每次测量构建准确的模型状态。这种称为功能预热的方法需要几个小时的运行时间,而所测量的详细模拟仅需几分钟。为了消除功能变暖的瓶颈,我们提出了TurboSMARTS,这是一个模拟框架,可将功能加热状态存储在小的可重用检查点库中。 TurboSMARTS通过仅存储在每个简短执行窗口的仿真过程中访问的预热状态子集,来创建精确采样所需的数千个检查点。 TurboSMARTS与先前的模拟采样技术的精度相匹配(即,±3%的误差,置信度为99.7%),同时估计平均每个基准测试运行SPEC CPU2000的8路无序超标量处理器的性能为91秒,使用12 GB的检查点库。

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