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Modeling of signal integrity in bus communications with timed data flow SystemC-AMS

机译:具有定时数据流SystemC-AMS的总线通信中信号完整性的建模

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The paper presents a new method for modeling the functionality and Signal Integrity (SI) performances of bus communications at a high level of abstraction. Using neural networks, we build a SystemC/SystemC-AMS virtual platform that combines functional modules, which represent the operative behavior of the system, and non-functional modules based on neural network approximation, which display the systems SI characteristics. Our method was demonstrated by modeling a Universal Serial Bus 3.0 (USB 3.0) system and was applied to the prediction of transient waveforms and eye diagrams. Compared to a HSPICE simulation, our method achieves excellent accuracy (mean absolute error of 1%) with a much shorter simulation time (×6000 speedup).
机译:本文提出了一种用于在高度抽象的水平上对总线通信的功能和信号完整性(SI)性能进行建模的新方法。使用神经网络,我们构建了一个SystemC / SystemC-AMS虚拟平台,该平台结合了代表系统操作行为的功能模块和基于神经网络逼近的非功能模块,这些模块显示了系统的SI特性。我们的方法通过对通用串行总线3.0(USB 3.0)系统进行建模来证明,并被用于预测瞬态波形和眼图。与HSPICE仿真相比,我们的方法实现了极好的精度(平均绝对误差为1%),仿真时间更短(加速6000倍)。

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