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Context-sensitive timing automata for fast source level simulation

机译:上下文相关定时自动机,用于快速源级仿真

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We present a novel technique for efficient source level timing simulation of embedded software execution on a target platform. In contrast to existing approaches, the proposed technique can accurately approximate time without requiring a dynamic cache model. Thereby the dramatic reduction in simulation performance inherent to dynamic cache modeling is avoided. Consequently, our approach enables an exploitation of the performance potential of source level simulation for complex microarchitectures that include caches. Our approach is based on recent advances in context-sensitive binary level timing simulation. However, a direct application of the binary level approach to source level simulation reduces simulation performance similarly to dynamic cache modeling. To overcome this performance limitation, we contribute a novel pushdown automaton based simulation technique. The proposed context-sensitive timing automata enable an efficient evaluation of complex simulation logic with little overhead. Experimental results show that the proposed technique provides a speed up of an order of magnitude compared to existing context selection techniques and simple source level cache models. Simulation performance is similar to a state of the art accelerated cache simulation. The accelerated simulation is only applicable in specific circumstances, whereas the proposed approach does not suffer this limitation.
机译:我们提出了一种新颖的技术,可以有效地对目标平台上的嵌入式软件执行源代码级时序仿真。与现有方法相比,所提出的技术可以精确地估计时间,而无需动态缓存模型。因此,避免了动态缓存建模固有的仿真性能的显着降低。因此,我们的方法使得能够利用源级仿真的性能潜力来处理包含缓存的复杂微体系结构。我们的方法基于上下文相关的二进制级时序仿真的最新进展。但是,直接将二进制级别方法应用于源级别模拟会降低模拟性能,这与动态缓存建模类似。为克服此性能限制,我们贡献了一种新颖的基于下推自动机的仿真技术。所提出的上下文相关定时自动机能够以很少的开销有效地评估复杂的仿真逻辑。实验结果表明,与现有的上下文选择技术和简单的源级缓存模型相比,该技术可将速度提高一个数量级。仿真性能类似于最新的加速缓存仿真。加速仿真仅适用于特定情况,而所提出的方法则不受此限制。

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