Area Optimization of Open-Source Low-Power INA in 130nm CMOS using Hybrid Mixed-Variable PSO
This addresses area optimization for designers in open-source silicon initiatives, though it is incremental as it builds on existing methods like gm/ID and PSO.
The paper tackled the problem of minimizing silicon area for open-source integrated circuits without compromising performance, achieving a 90.33% reduction in gate area for a low-power instrumentation amplifier.
As open-source silicon initiatives democratize access to integrated circuit development using multi-project environments, silicon area has become a premium resource. However, minimizing this layout area traditionally forces designers to compromise on core performance specifications. To address this challenge, this paper presents an open-source framework based on a hybrid mixed-variable particle swarm optimization algorithm and the gm/ID methodology to minimize the layout area of complex analog circuits while meeting design requirements. The framework's efficacy is demonstrated by designing a low-power instrumentation amplifier that achieves a 90.33% reduction in gate area over existing implementations.