Shot boundary detection using Zernike moments in multi-GPU multi-CPU architectures

This paper presents an analysis of a Multi-GPU Multi-CPU environment, along with the different possible hybrid combinations. The analysis has been performed for a shot boundary detection application, based on Zernike moments, although it is general enough to be applied to many different application areas. A deep study of the performance, bottlenecks and design challenges is carried out showing the validity of this approach and achieving very high frame per second rates. In this paper, Zernike calculations are carried out on GPUs, taking advantage of a packing strategy proposed to minimize host-device communication time.

► We have proposed a GPU implementation for Zernike Moments.
► It has been integrated it in shot boundary detection algorithm.
► We have proposed an architecture based on Multi-GPU Multi-CPU.
► A deep experimental study of the performance and bottlenecks has been carried out.
► It has been successfully run on 4 CPUs and 2GPUs taking it far beyond real time.