Extraction of Compact Model Parameters for ULSI MOSFETs Using a Genetic Algorithm
Extraction of Compact Model Parameters for ULSI MOSFETs Using a Genetic Algorithm
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发表时间：
1999-04
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通讯作者：
Josef Watts;Calvin Bittner;Douglas Heaberlin;James Hoffmann
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作者：
Josef Watts;Calvin Bittner;Douglas Heaberlin;James Hoffmann
提取FET器件模型的最佳参数值集是一个复杂的问题。最终模型不仅必须将一组硬件的性能描述到可接受的准确度水平，而且必须满足设备允许的操作机制之外的标准，以确保仿真期间鲁棒的收敛特性。传统的参数提取方法依赖于梯度技术，可以产生远离最优的解决方案，因为在解空间中的局部最优的存在。因此，传统上，参数提取更多的是艺术而不是科学，需要经验丰富的工程师进行多次迭代。遗传算法非常适合于在不规则参数空间中寻找近似最优解。我们已经应用了遗传算法的问题，设备模型参数提取，并能够产生模型的上级精度在更短的时间内，并与较少的依赖于人类的专业知识。
Extracting an optimal set of parameter values for an FET device model is a complex problem. The final model must not only describe the performance of a set of hardware to an acceptable level of accuracy, but must satisfy criteria outside the device’s allowed operating regime to ensure robust convergence properties during simulation. Traditional methods of parameter extraction which rely on gradient techniques can produce far-from-optimal solutions because of the presence of local optima in the solution space. As a result, parameter extraction has traditionally been more art than science, requiring several iterations by an experienced engineer. Genetic algorithms are well-suited for finding nearoptimal solutions in irregular parameter spaces. We have applied a genetic algorithm to the problem of device model parameter extraction and are able to produce models of superior accuracy in much less time and with less reliance on human expertise.