Abstract
SummaryIn this paper, different variants of the block Gauss–Huard algorithm with column pivoting and correspondingly interchanging of columns are presented and implemented on a hybrid CPU–GPU architecture. The study gives numerical evidence that the algorithms yield numerical solutions as good as those obtained by Gaussian elimination with partial pivoting and performance evidence that they are more suitable for parallel architectures. This is confirmed by solving systems of linear equations for a set of randomly generated matrices. Copyright © 2016 John Wiley & Sons, Ltd.
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 callMore From: Concurrency and Computation: Practice and Experience
Disclaimer: 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.
