Parallel Implementation of Conjugate Gradient Method on Graphics Processors

Author:

Wozniak Marcin,Olas Tomasz,Wyrzykowski Roman

Publisher

Springer Berlin Heidelberg

Reference22 articles.

1. Basermann, A., Reichel, B., Schelthoff, C.: Preconditioned CG methods for sparse matrices on massively parallel machines. Parallel Computing Journal 23(3), 381–393 (1997)

2. Baskaran, M.M., Bordawekar, R.: Optimizing Sparse Matrix-Vector Multiplication on GPUs. IBM Research Report No. RC24704, W0812-047 (2009)

3. Bell, N., Garland, M.: Efficient Sparse Matrix-Vector Multiplication on CUDA. NVIDIA Tech. Report No. NVR-2008-004 (2008)

4. CUDPP: CUDA Data Parallel Primitives Library, http://gpgpu.org/developer/cudpp

5. Dokken, T., Hagen, T.R., Hjelmervik, J.M.: An Introduction to General-Purpose Computing on Programmable Graphics Hardware. In: Geometric Modelling, Numerical Simulation, and Optimization: Applied Mathematics at SINTEF, pp. 123–161. Springer, Heidelberg (2007)

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