Efficient Parallel Computing for Solving Linear Systems of Equations
Permanent Link
Author/Creator
Author/Creator ORCID
Date
Type of Work
Department
Program
Citation of Original Publication
Allen, Kevin P. “Efficient Parallel Computing for Solving Linear Systems of Equations.” UMBC Review: Journal of Undergraduate Research 5 (2004): 8–19. https://userpages.umbc.edu/~gobbert/kali/papers/AllenReview.pdf
Rights
This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
Subjects
Abstract
Linear systems of equations are common throughout the disciplines of science. The conjugate gradient method is a common iterative method used to solve systems with symmetric positive definite system matrices. With a matrix-free implementation, themethod is optimal with respect to both memory usage and performance, and we are ableto solve problems that are much too large for single processor computers. Using a high performance Myrinet interconnect, excellent speedup is possible for at least up to 32 processors. This illustrates the power of parallel computing in solving large problems much faster than on a single processor.