Algorithmic Based Fault Tolerance Applied to High Performance Computing

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dc.creatorBosilca, George
dc.creatorDelmas, Remi
dc.creatorDongarra, Jack
dc.creatorLangou, Julien
dc.date2008-06-19
dc.date.accessioned2026-07-07T09:45:33Z
dc.date.available2026-07-07T09:45:33Z
dc.descriptionWe present a new approach to fault tolerance for High Performance Computing system. Our approach is based on a careful adaptation of the Algorithmic Based Fault Tolerance technique (Huang and Abraham, 1984) to the need of parallel distributed computation. We obtain a strongly scalable mechanism for fault tolerance. We can also detect and correct errors (bit-flip) on the fly of a computation. To assess the viability of our approach, we have developed a fault tolerant matrix-matrix multiplication subroutine and we propose some models to predict its running time. Our parallel fault-tolerant matrix-matrix multiplication scores 1.4 TFLOPS on 484 processors (cluster jacquard.nersc.gov) and returns a correct result while one process failure has happened. This represents 65% of the machine peak efficiency and less than 12% overhead with respect to the fastest failure-free implementation. We predict (and have observed) that, as we increase the processor count, the overhead of the fault tolerance drops significantly.
dc.identifierhttps://arxiv.org/abs/0806.3121
dc.identifierhttp://arxiv.org/abs/0806.3121
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/163231
dc.subjectDistributed, Parallel, and Cluster Computing
dc.subjectMathematical Software
dc.titleAlgorithmic Based Fault Tolerance Applied to High Performance Computing
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