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Conference Papers Year : 2016

Reproducible, Accurately Rounded and Efficient BLAS


Numerical reproducibility failures rise in parallel computation because floating-point summation is non-associative. Massively parallel and optimized executions dynamically modify the floating-point operation order. Hence, numerical results may change from one run to another. We propose to ensure reproducibility by extending as far as possible the IEEE-754 correct rounding property to larger operation sequences. We introduce our RARE-BLAS (Reproducible, Accurately Rounded and Efficient BLAS) that benefits from recent accurate and efficient summation algorithms. Solutions for level 1 (asum, dot and nrm2) and level 2 (gemv) routines are presented. Their performance is studied compared to Intel MKL library and other existing reproducible algorithms. For both shared and distributed memory parallel systems, we exhibit an extra-cost of 2× in the worst case scenario, which is satisfying for a wide range of applications. For Intel Xeon Phi accelerator a larger extra-cost (4× to 6×) is observed, which is still helpful at least for debugging and validation steps.
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Dates and versions

lirmm-01280324 , version 1 (29-02-2016)
lirmm-01280324 , version 2 (28-07-2016)



Chemseddine Chohra, Philippe Langlois, David Parello. Reproducible, Accurately Rounded and Efficient BLAS. Euro-Par: Parallel Processing Workshops., Aug 2016, Grenoble, France. pp.609-620, ⟨10.1007/978-3-319-58943-5_49⟩. ⟨lirmm-01280324v2⟩
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