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Robust interconnect communication capacity algorithm by geometric programming

机译:几何编程的鲁棒互连通信容量算法

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This paper proposes a new model for interconnect communication capacity in the presence of process variations. Different from previous research works, this model, for the first time, reveals the dependency of interconnect communication capacity on its parasitic parameters. A new method based on Uncertainty Ellipsoid Method (UEM) is applied to optimize the interconnect capacity considering random parameters variations. This new approach incorporates both spatial correlations of intra-die width and parameters variations in the optimization procedure. As is well known, process variation introduces perturbations in the transfer function of interconnect networks. The perturbed transfer function in turn causes variations in the Bit Error Rate (BER). Becoming random, the perturbed BER leads to a changing communication capacity. Based on robust communication theory, we propose a new capacity model which is a function of interconnect geometric parameters. With the help of Geometric Programming (GP) procedure, we use the new model to conduct optimization with regard to the design parameters. Experimental results show that the new model provides less than 7:3% mean square error in capacity prediction comparing with Monte-Carlo method. Based on this bit error value, GP technique is applied to determine the optimal solution, which in return guides the fabrication of interconnects.
机译:本文提出了一种在存在过程变化的情况下互连通信能力的新模型。与先前的研究工作不同,该模型首次揭示了互连通信能力对其寄生参数的依赖性。考虑不确定参数的变化,基于不确定性椭球法(UEM)的新方法被用于优化互连容量。这种新方法在优化过程中结合了芯片内宽度的空间相关性和参数变化。众所周知,过程变化在互连网络的传递函数中引入了扰动。扰动的传递函数又导致误码率(BER)发生变化。变成随机的BER导致通信容量的变化。基于鲁棒的通信理论,我们提出了一种新的容量模型,该模型是互连几何参数的函数。借助几何编程(GP)程序,我们使用新模型对设计参数进行了优化。实验结果表明,与蒙特卡洛方法相比,新模型在容量预测中提供的均方误差小于7:3%。基于此误码值,可以应用GP技术来确定最佳解决方案,该解决方案反过来将指导互连的制造。

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