Abstract
A multigrid preconditioned conjugate gradient (MGCG) method, which uses the multigrid method as a preconditioner for the conjugate gradient method, has a good convergence rate even for problems on which the standard multigrid method does not converge efficiently. This paper considers a parallelization of the MGCG method and proposes an efficient parallel MGCG method on distributed memory machines. For a good convergence rate of the MGCG method, several difficulties in parallelizing the multigrid method are successfully settled. It is also shown that the parallel MGCG method has high performance on the Fujitsu AP1000 multicomputer, and it is more than 10 times faster than the scaled conjugate gradient (SCG) method. >
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.
