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An application-level synthesis methodology for multidimensional embedded processing systems

机译:多维嵌入式处理系统的应用程序级综合方法

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The implementation of multidimensional systems in embedded devices is a major design challenge due to the high algorithmic complexity of the applications. The authors suggest a novel application-level synthesis methodology for those parts of the embedded application which are characterized by being Lebesgue measurable (the computation involved in signal and image processing systems is Lebesgue measurable). The synthesis methodology, based on perturbation analysis, supports the design of analog, digital, or mixed implementations at the very high level of the system design cycle. The outputs of the methodology are quantitative indications regarding the maximum performance loss tolerable by the subsystems composing the application. Such information, augmented with a stochastic description of the tolerated perturbations, can be related to lower synthesis levels and guide the designer toward the final implementation of the embedded device. The perturbation analysis is based on randomized algorithms for an effective evaluation of the performance loss of the computational flow once affected by behavioral perturbations and a Tabu-search-inspired optimizing algorithm for distributing the tolerable performance loss at the system output along the computational subsystems composing the possibly multidimensional processing.
机译:由于应用程序的高算法复杂性,因此在嵌入式设备中实现多维系统是一项主要的设计挑战。作者提出了一种新颖的应用程序级综合方法​​,用于以Lebesgue可测量为特征的嵌入式应用程序的那些部分(信号和图像处理系统中涉及的计算是Lebesgue可测量的)。基于扰动分析的综合方法论可在系统设计周期的很高水平上支持模拟,数字或混合实现的设计。该方法的输出是关于组成应用程序的子系统所能承受的最大性能损失的定量指示。这种信息,加上对随机扰动的随机描述,可以与较低的合成水平相关,并可以指导设计人员实现嵌入式设备的最终实现。扰动分析基于随机算法,用于有效评估一旦受到行为扰动影响的计算流的性能损失;以及禁忌搜索启发式优化算法,用于沿着系统组成部分的计算子系统在系统输出处分配可容忍的性能损失。可能是多维处理。

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