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| Title | Self-Adaptive Multiprecision Preconditioners on Multicore and Manycore Architectures |
| Publication Type | Conference Paper |
| Year of Publication | 2014 |
| Authors | Anzt, H., D. Lukarski, S. Tomov, and J. Dongarra |
| Conference Name | VECPAR 2014 |
| Date Published | 2014-06 |
| Conference Location | Eugene, OR |
| Abstract | Based on the premise that preconditioners needed for scientific computing are not only required to be robust in the numerical sense, but also scalable for up to thousands of light-weight cores, we argue that this two-fold goal is achieved for the recently developed self-adaptive multi-elimination preconditioner. For this purpose, we revise the underlying idea and analyze the performance of implementations realized in the PARALUTION and MAGMA open-source software libraries on GPU architectures (using either CUDA or OpenCL), Intel’s Many Integrated Core Architecture, and Intel’s Sandy Bridge processor. The comparison with other well-established preconditioners like multi-coloured Gauss-Seidel, ILU(0) and multi-colored ILU(0), shows that the twofold goal of a numerically stable cross-platform performant algorithm is achieved. |
