Abstract
When more processors are used for a calculation, the probability that one will fail during the calculation increases. Fault tolerance is a technique for allowing a calculation to survive a failure, and includes recovering lost data. A common method of recovery is diskless checkpointing. However, it has high overhead when a large amount of data is involved, as is the case with matrix operations. A checksum-based method allows fault tolerance of matrix operations with lower overhead. This technique is applicable to the LU decomposition in the benchmark HPL.
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