A virtualized software based on the NVIDIA cuFFT library for image denoising: performance analysis

Abstract

Generic Virtualization Service (GVirtuS) is a new solution for enabling GPGPU on Virtual Machines or low powered devices. This paper focuses on the performance analysis that can be obtained using a GPGPU virtualized software. Recently, GVirtuS has been extended in order to support CUDA ancillary libraries with good results. Here, our aim is to analyze the applicability of this powerful tool to a real problem, which uses the NVIDIA cuFFT library. As case study we consider a simple denoising algorithm, implementing a virtualized GPU-parallel software based on the convolution theorem in order to perform the noise removal procedure in the frequency domain. We report some preliminary tests in both physical and virtualized environments to study and analyze the potential scalability of such an algorithm