alexa A Survey on Optimization and Parallelization of Conjuga
ISSN: 2165- 7866

Journal of Information Technology & Software Engineering
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Review Article

A Survey on Optimization and Parallelization of Conjugate Gradient Solver

Khirodkar PP*

Department of Information Technology, Savitribai Phule University, Pune, India

*Corresponding Author:
Khirodkar PP
Department of Information Technology
Savitribai Phule University
Pune, India
Tel: 020 2569 6064
E-mail: [email protected]

Rec date: Jan 20, 2016; Acc date: Apr 24, 2016; Pub date: Apr 30, 2016

Citation: Khirodkar PP (2016) A Survey on Optimization and Parallelization of Conjugate Gradient Solver. J Inform Tech Softw Eng 6:177. doi:10.4172/2165-7866.1000177

Copyright: © 2016 Khirodkar PP. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



Conjugate Gradient Solver is a well-known iterative technique for solving sparse symmetric positive definite (SPD) systems of linear equations. The aim of this paper is to optimize and parallelize the currently available Conjugate Gradient Solver for OpenFOAM (Open source Field Operation and Manipulation) on GPU using CUDA which stands for Compute Unified Device Architecture, is a parallel computing platform and application programming interface (API) model created by NVIDIA. OpenFOAM is a C++ toolbox for development of customized numerical solvers of continuum mechanics problems, including Computational Fluid Dynamics. Existing Conjugate Gradient Solver can be optimized with the help of some techniques available for sparse matrix storage like Compressed Sparse Vecto (CSV).


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