Open Access

Yannick UhlmannORCiD, Till MoldenhauerORCiD, Jürgen ScheibleORCiD

• To this day, the design of analog integrated circuits is a predominantly manual task, heavily reliant on the knowledge and intuition of human experts. Many current automation approaches aim to be holistic solutions, attempting to take the human out of the loop. This work, in turn, does not intend to replace human designers with algorithms, but support their qualities in the established flow. Here, the performance space of analog ICs is modeled by PVT-aware neural networks and visualized with parallel coordinate plots. Such a responsive visualization gives insights into the relations of parameters through interactive exploration where any parameter can be the cause while all others show the immediate effect. Thus, complex decision-making problems based on the experience of seasoned designers, such as circuit sizing or topology selection, are transformed into intuitive perceptual problems. Through the responsiveness and immediacy of the implementation, designers are encouraged to explore the entire performance space instead of basing all decisions on previous designs, never leaving the beaten path. A data generation and training procedure for surrogate models is outlined. Models for three operational amplifiers in three different technologies illustrate the applicability and feasibility of the presented approach. Additionally, a web-based demo, including all source code, is available for review.