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“Self-Adaptive Multiprecision Preconditioners on Multicore and Manycore Architectures”


Hartwig Anzt and Dimitar Lukarski and Stanimire Tomov and Jack Dongarra

Published  April 15, 2014  as  ut-eecs-14-728



Based on the premise that preconditioners needed for scienti c 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 under-lying 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.



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