Abstract
This paper discusses an extension of the pipelined Givens method for computing the QR factorization of a real m× n matrix to the case in which the matrix is sparse. When restricted to one process, the algorithm performs the same computation as the serial sparse Givens algorithm of George and Heath. Our implementation is compatible with the data structures used in sparspak. The pipelined algorithm is well suited to parallel computers having globally shared memory and low-overhead synchronization primitives, such as the Denelcor HEP, for which computational results are presented. We point out certain synchronization problems that arise in the adaptation to the sparse setting and discuss the effect on parallel speedup of accessing a serial data file.
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.
