Abstract
We present several algorithms to compute the solution of a linear system of equations on a GPU, as well as general techniques to improve their performance, such as padding and hybrid GPU-CPU computation. We also show how iterative refinement with mixed-precision can be used to regain full accuracy in the solution of linear systems. Experimental results on a G80 using CUBLAS 1.0, the implementation of BLAS for NVIDIA® GPUs with unified architecture, illustrate the performance of the different algorithms and techniques proposed. © 2008 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Barrachina, S., Castillo, M., Igual, F. D., Mayo, R., & Quintana-Ortí, E. S. (2008). Solving dense linear systems on graphics processors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5168 LNCS, pp. 739–748). https://doi.org/10.1007/978-3-540-85451-7_79
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