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Optimization processing unit (OPU) applied to integrated circuit design and manufacturing

机译:优化处理单元(OPU)应用于集成电路设计和制造

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The authors proposed a general purpose parameter optimizer, Optimization Processing Unit (OPU), which can handle multi-objective parameter optimization in a multi-input multi-output (MIMO) system (applying parameter optimization to a system implies that it is a functional system). Practical computer-aided methods are used to avoid the difficulty of deriving equations that are usually required for system modeling. For multi-objective optimization, OPU only needs the known data of the system input, the corresponding output data, the objectives, the tolerances of objectives, and required fitting accuracy of the system approximation. In current practice, singular points are avoided or limited. Hence, we demonstrate OPU can handle all the field parameter optimization by its very nature. OPU includes four sub-units: Data-adjusted Automatic Taylor Expansion Unit, Tolerance and Constraint Adjustment Unit, Accuracy and Result Self-confirm Unit, and Automatic Optimizer. The fully automatic flow of optimization by OPU has been proposed in this paper. The optimizer applied simulated annealing algorithm [1]–[2] together with dynamic energy threshold and weighted sum method [3]. An Algorithm of Data-adjusted Automatic Taylor Expansion Unit is proposed to translate the system input data and corresponding output to system equations in a Taylor Series format. In addition, the tolerance and constraint adjustment method in OPU was presented. This OPU has been verified and reduced to practice through performance estimation of circuits for various transistor device indexes by using the BSIM4 [4] and BSIM-CMG [5] modeling optimization system. A Vdd-Vth (Vdd: operation voltage, Vth: threshold voltage) driven relation was used to co-optimizes both design and process for logic circuit power minimization.
机译:作者提出了一种通用参数优化器,即优化处理单元(OPU),它可以处理多输入多输出(MIMO)系统中的多目标参数优化(将参数优化应用于系统意味着它是一个功能系统)。 )。使用实用的计算机辅助方法来避免派生系统建模通常需要的方程式的困难。对于多目标优化,OPU只需要系统输入的已知数据,相应的输出数据,目标,目标公差以及系统逼近所需的拟合精度。在当前实践中,避免或限制了奇异点。因此,我们证明了OPU的本质可以处理所有现场参数优化。 OPU包括四个子单元:数据调整的自动泰勒扩展单元,公差和约束调整单元,准确性和结果自确认单元以及自动优化器。本文提出了OPU的全自动优化流程。优化程序应用了模拟退火算法[1] – [2]以及动态能量阈值和加权和方法[3]。提出了一种数据调整自动泰勒扩展单元算法,将系统输入数据和相应的输出转换为泰勒级数格式的系统方程。此外,提出了OPU中的公差和约束调整方法。该OPU已通过使用BSIM4 [4]和BSIM-CMG [5]建模优化系统对各种晶体管器件指标的电路性能进行了评估,从而得到了验证和简化,可以付诸实践。使用Vdd-Vth(Vdd:工作电压,Vth:阈值电压)驱动关系来共同优化逻辑电路功耗最小化的设计和工艺。

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