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OpenCL Parallel Programming Development Cookbook by Raymond Tay

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Solving SpMV (Sparse Matrix Vector Multiplication) using the Conjugate Gradient Method

The conjugate gradient method is the most popular iterative method for solving sparse linear systems, and I will attempt to make you understand how it works. Along this journey, we will look into steepest descent, conjugate gradient convergence, and so on.

Tip

I wanted to say a big thank you to Jonathan Richard Shewchuk (AP of University of California), without whom I might not have understood why conjugate gradients matter You can learn more about him at http://www.cs.cmu.edu/~jrs/.

A reason why the CG method is popular in solving sparse systems is that it not only handles really large sparse matrices well but it is also very efficient.

In the previous chapter ...

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