Paper Info
Title
Convergence and resilience of the fine-grained parallel incomplete LU factorization for non-symmetric problems.
Abstract
This paper presents an investigation into the convergence of the fine-grained parallel algorithm for computing an incomplete LU factorization for non-symmetric and indefinite matrices. The fine-grained parallel incomplete LU factorization is a nonlinear fixed point iteration and convergence has not been extensively studied for problems that are not symmetric positive definite. This work investigates the convergence of the algorithm for these more difficult problems and additionally investigates how the occurrence of a computing fault may impact the convergence of the algorithm for the problems being studied. The results obtained suggest that this class of problems presents challenges for the fine-grained parallel incomplete LU factorization (less than 30% of configurations converge naturally), and that while the occurrence of a fault can cause significant negative effects, the simple algorithmic change advocated here can completely ameliorate the effects of a fault.
Year
Venue
Keywords
2018
Simulation Series
incomplete LU factorizations,preconditioning,fine-grained parallelism,fault tolerance
Field
DocType
Volume
Convergence (routing),Applied mathematics,Nonlinear system,Matrix (mathematics),Computer science,Parallel algorithm,Positive-definite matrix,Fixed-point iteration,Fault tolerance,Incomplete LU factorization
Conference
50
Issue
ISSN
Citations 
4
0735-9276
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Evan Coleman112.72
Masha Sosonkina227245.62