reliability programming model that requires reliability only when and where needed, such checks can make algorithms reliable despite unbounded faults. Resilience in Numerical Methods: A Position on Fault Models and Methodologies. However, resilience research struggles to come up with useful abstract programming models for reasoning about SDC.
More, future extreme-scale computer systems may expose silent data corruption (SDC) to applications, in order to save energy or increase performance. Sanity checks, and in general a healthy skepticism about the correctness of subroutines, are wise even if hardware is perfectly reliable.
Also, we know so little about how SDC may manifest in future hardware, that it seems premature to draw conclusions about the average case. Algorithms can use inexpensive "sanity" checks that bound or exclude error in the results of computations. Algorithm developers need to understand worst-case behavior with the higher-level data types they actually use, in order to make their algorithms more resilient. Download, edit, views PaperRank. We argue instead that numerical algorithms can benefit from a numerical unreliability fault model, where faults manifest as unbounded perturbations to floating-point data. Communication-optimal parallel and sequential QR and LU factorizations. J Demmel, L Grigori, M Hoemmen, J Langou. Siam Journal on Scientific Computing. In beethoven essay pdf the context of Recycled gmres the thesis. Can also make similar statements about the case p 1, though they are omitted here. Second authors would like to thank Mark Hoemmen for engaging in many helpful. In this PhD thesis, we address three challenges faced by linear al gebra.
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