Exploiting program microarchitecture independent characteristics and phase behavior for reduced benchmark suite simulation

L. Eeckhout, Jack Sampson, Brad Calder
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引用次数: 73

Abstract

Modern architecture research relies heavily on detailed pipeline simulation. Simulating the full execution of an industry standard benchmark can take weeks to complete. Simulating the full execution of the whole benchmark suite for one architecture configuration can take months. To address this issue researchers have examined using targetted sampling based on phase behavior to significantly reduce the simulation time of each program in the benchmark suite. However, even with this sampling approach, simulating the full benchmark suite across a large range of architecture designs can take days to weeks to complete. The goal of this paper is to further reduce simulation time for architecture design space exploration. We reduce simulation time by finding similarity between benchmarks and program inputs at the level of samples (100M instructions of execution). This allows us to use a representative sample of execution from one benchmark to accurately represent a sample of execution of other benchmarks and inputs. The end result of our analysis is a small number of sample points of execution. These are selected across the whole benchmark suite in order to accurately represent the complete simulation of the whole benchmark suite for design space exploration. We show that this provides approximately the same accuracy as the SimPoint sampling approach while reducing the number of simulated instructions by a factor of 1.5.
利用程序微体系结构独立特性和相位行为进行简化基准套件仿真
现代建筑研究很大程度上依赖于详细的管道模拟。模拟行业标准基准的完整执行可能需要数周才能完成。模拟一个体系结构配置的整个基准测试套件的完整执行可能需要数月时间。为了解决这个问题,研究人员已经研究了基于相位行为的目标采样,以显着减少基准套件中每个程序的模拟时间。然而,即使使用这种抽样方法,在大范围的体系结构设计中模拟完整的基准测试套件也可能需要几天到几周的时间才能完成。本文的目标是进一步减少建筑设计空间探索的仿真时间。我们通过在样本级别(执行100条指令)上找到基准测试和程序输入之间的相似性来减少模拟时间。这允许我们使用一个基准的执行代表性样本来准确地表示其他基准和输入的执行样本。我们分析的最终结果是少量的执行点样本。这些是在整个基准测试套件中选择的,以便准确地表示整个基准测试套件的完整模拟,以进行设计空间探索。我们表明,这提供了与SimPoint采样方法大致相同的精度,同时将模拟指令的数量减少了1.5倍。
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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