Applying Swarm Intelligence to Distributed On-Chip Power Management

An on-chip power management technique is developed that makes use of particle swarm optimization (PSO) to improve the performance per watt of the circuit while maintaining the power integrity. On-line learning is applied to determine the optimum reference voltages of the on-chip voltage regulators set through the PSO to reduce the energy consumption of the system while preventing any timing failure due to process variation, voltage variation, temperature, and aging. The runtime adaptive voltage delivery technique is applicable to any processor architecture. Simulation results on a streaming multiprocessor similar to the NVIDIA GV100 GPU in a 7 nm FinFET technology indicate an average reduction of 35%, 40%, and 5% in, respectively, the power consumption, the threshold voltage drift, and the operating temperature as compared to existing techniques that implement static voltage guardbands.