Performance and energy optimization of ternary optical computers based on tandem queuing system

As an emerging computer technology with numerous bits, bit-wise allocation, and extensive parallelism, the ternary optical computer (TOC) will play an important role in platforms such as cloud computing and big data. Previous studies on TOC in handling computational request tasks have mainly focused on performance enhancement while ignoring the impact of performance enhancement on power consumption. The main objective of this study is to investigate the optimization trade-off between performance and energy consumption in TOC systems. To this end, the service model of the TOC is constructed by introducing the M/M/1 and M/M/c models in queuing theory, combined with the framework of the tandem queueing system, and the optimization problem is studied by adjusting the processor partitioning strategy and the number of small TOC (STOC) in the service process. The results show that the value of increasing active STOCs is prominent when system performance significantly depends on response time. However, marginal gains decrease as the number of STOCs grows, accompanied by rising energy costs. Based on these findings, this paper constructs a bi-objective optimization model using response time and energy consumption. It proposes an optimization strategy to achieve bi-objective optimization of performance and energy consumption for TOC by identifying the optimal partitioning strategy and the number of active small optical processors for different load conditions.