Introduction to parallel computing
Introduction to parallel computing
Ordering methods for preconditioned conjugate gradient methods applied to unstructured grid problems
SIAM Journal on Matrix Analysis and Applications
Introduction to parallel computing: design and analysis of algorithms
Introduction to parallel computing: design and analysis of algorithms
Ordering strategies for modified block incomplete factorizations
SIAM Journal on Scientific Computing
Performance and Scalability of Preconditioned Conjugate Gradient Methods on Parallel Computers
IEEE Transactions on Parallel and Distributed Systems
Matrix computations (3rd ed.)
Scheduling Algorithms for Parallel Gaussian Elimination With Communication Costs
IEEE Transactions on Parallel and Distributed Systems
Developments and trends in the parallel solution of linear systems
Parallel Computing - Special Anniversary issue
Parallel Computing - Special Anniversary issue
Advances in Randomized Parallel Computing
Advances in Randomized Parallel Computing
Parallel algorithms for global optimization problems
Solving Combinatorial Optimization Problems in Parallel - Methods and Techniques
Performance Prediction for Parallel Iterative Solvers
The Journal of Supercomputing
A parallel implementation of Chebyshev preconditioned conjugate gradient method
ISPDC'03 Proceedings of the Second international conference on Parallel and distributed computing
| Hi-index | 0.00 |
The conjugate gradient method is an iterative technique used to solve systems of linear equations. The paper analyzes the performance of parallel preconditioned conjugate gradient algorithms. First, a theoretical model is proposed for estimation of the complexity of PPCG method and a scalability analysis is done for three different data decomposition cases. Computational experiments are done on IBM SP4 computer and some results are presented. It is shown that theoretical predictions agree well with computational results.