Abstract
AbstractThe utilization of all computational resources is significant to achieve efficient computation. In order to exploit the available computation resources, we combine two parallel programming models such as MPI and CUDA. Combining of these two programming models ensures usage of the whole computation resources available in one computer system (CPU and GPU). In this paper, we present a way to use the available parallel processing resources to their full potential utilizing different strategies and techniques regarding data transfer. We perform experimental computation of well know algorithm for computing Walsh spectra of Boolean functions by combining these two parallel programming models. Experiments are performed on two different class of parallel processing capability hardware. Randomly generated Boolean functions of fourteen, sixteen, eighteen and twenty variables represent the used data set for experiments evaluations. Performed experiments show how the growth of the data size results in gaining more parallelization and therefore accelerate the execution.KeywordsMPICUDABoolean functionWalsh spectraParallel algorithm
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
