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Simulation study demonstrates automated parameter tuning across five transistor-level converters, indicating reduced computational overhead in nano-scale integrated circuit optimization.
In application-specific designs, owing to the trade-off between power consumption and speed, the optimization of various circuit parameters has become a challenging task. Several of the performance metrics, viz. energy efficiency, gain, performance, and noise immunity, are interrelated and difficult to tune. Such efforts may result in a great deal of manual iterations which in turn increase the computational overhead. Thus it is important to develop a methodology that not only explores large design space but also reduces the computational time. In this work, we investigate the viability of using a SPICE and Python Integrated Development Environment (PIDE) interface to optimize integrated circuits. The SPICE simulations are carried out using 22 nm technology node with a nominal supply voltage of 0.8 V. The SPICE-PIDE optimizer, as delineated in this work, is able to provide the best solution sets considering various performance metrics and design complexities for five transistor level converters.
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Taraporewalla et al. (2026) studied this question.
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