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Probabilistic timing analysis of asychronous systems with moments of delays

机译:延迟时刻异步系统的概率定时分析

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Finding time separation of events is a fundamental problem in the analysis of asynchronous Systems. When component delays have statistical variations, it is both interesting and useful to compute moments of time separation of events. Traditionally, Monte Carlo simulation has been used for this purpose. However, Monte Carlo simulation requires knowledge of the probability distributions of component delays, which is often difficult to ascertain. Much more easily available are parameters like the statistical mean and variance of component delays. Unfortunately, with only these parameters, Monte Carlo simulation cannot be reliably applied. Yet another disadvantage of Monte Carlo simulation is the large number of runs needed before the error term becomes small enough to be acceptable. This paper describes a polynomial-time algorithm for computing bounds on the first two moments of times of occurrence of events in an acyclic timing constraint graph, given only means and variances of component delays. We present experimental results demonstrating the effectiveness of our algorithm.
机译:发现事件的时间分离是异步系统分析中的一个基本问题。当组件延迟具有统计变异时,计算事件的时间分离的时刻既有趣,也很有用。传统上,Monte Carlo仿真已用于此目的。然而,Monte Carlo仿真需要了解组件延迟的概率分布,这通常难以确定。更容易可用的是像统计均值和组件延迟方差的参数。不幸的是,只有这些参数,蒙特卡罗模拟无法可靠地应用。蒙特卡罗模拟的另一个缺点是在误差术语变得足够小之前需要的大量运行是可以接受的。本文介绍了在非环状定时约束图中发生事件发生的前一段时间的多项式时间算法,仅给出了组件延迟的装置和差异。我们提出了实验结果,展示了算法的有效性。

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