A performance, power, and energy analysis of ultrasound B‐mode imaging on a GPU with VFS

Abstract

Summary Because of the power and energy constraints in modern computing systems, it is important to find a balance between performance and power/energy consumption to produce not only energy efficient portable devices but also reliable computing systems. In this paper, we present an analytical investigation of the performance and power/energy consumption of a well‐known medical application, “ultrasound B‐mode imaging,” which is implemented on modern commercial graphics processing units (GPUs). With this target application, we investigate the impact of GPU hardware features on performance, power, and energy by experimentally applying voltage and frequency scaling on various GPU devices. Based on our results, we mathematically build a performance prediction model to show the analytical relationship between the architectural features of those GPUs and the application performance. Our results show that the performance prediction model has errors of less than 8.71% and that there exists an energy‐optimal point in the design space spanned by the core clock frequency. We expect that our model can help engineers to design an ultrasound diagnosis system with the most suitable GPU that satisfies cost, performance, and power/energy constraints.