Abstract
The general-purpose graphics processing unit programming has been widely used and has achieved satisfactory results across many knowledge areas and it keeps evolving since its earlier stages. This paper presents an implementation of a modified Simplex method using the computational power brought from graphics processing unit (GPU) computing using the Nvidia framework for GPU programming, compute unified device architecture (CUDA). The results achieved shown that the parallel GPU implementation reached 15x and 22x maximum speedup measuring the overall time (data transfer plus kernel work time) and the kernel computation time respectively, in comparison with the standard sequential implementation using central processing unit (CPU).
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.
