Post-Silicon Optimization of a Highly Programmable 64-MHz PLL Achieving 2.7-5.7 μW

Hierarchical optimization methods used in the design of complex mixed-signal systems require accurate behavioral models to avoid the long simulation times of transistor-level SPICE simulations of the whole system. However, robust behavioral models that accurately model circuit non-idealities and their complex interactions must be very complex themselves and are hardly achievable. Post-silicon tuning, which is already widely used for the calibration of analog building blocks, is an interesting alternative to speed up the optimization of these complex systems. However, post-silicon tuning usually focuses on single-objective problems in blocks with a limited number of degrees of freedom. In this paper, we propose a post-silicon “hardware-in-the-loop” optimization method to solve multi-objective problems in mixed-signal systems with numerous degrees of freedom. We use this method to optimize the noise-power trade-off of a 64-MHz phase-locked loop (PLL) based on a back-bias-controlled ring oscillator. A genetic algorithm was run based on measurements of the 22-nm fully-depleted silicon-on-insulator prototype to find the Pareto-optimal configurations in terms of power and long-term jitter. The obtained Pareto front gives a range of power consumption between 2.7 and 5.7 μW, corresponding to an RMS long-term jitter between 88 and 45 ns. Whereas the simulation-based optimization would require more than a year using the genetic algorithm based on SPICE simulations, we conducted the post-silicon optimization in only 17 h.