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2009.3: Algorithmic Based Fault Tolerance Applied to High Performance Computing

2009.3: George Bosilca, Remi Delmas, Jack Dongarra and Julien Langou (2009) Algorithmic Based Fault Tolerance Applied to High Performance Computing.

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We 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 matrixmatrix 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 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.

Item Type:MIMS Preprint
Additional Information:

Appears also as Technical Report UT-CS-08-620, Department of Computer Science, University of Tennessee, Knoxville, TN, USA, June 2008 and as LAPACK Working Note 205"

Subjects:MSC 2000 > 65 Numerical analysis
MSC 2000 > 68 Computer science
MIMS number:2009.3
Deposited By:Ms Lucy van Russelt
Deposited On:13 January 2009

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