On-line soft error correction in matrix-matrix multiplication

Soft errors are one-time events that corrupt the state of a computing system but not its overall functionality. Soft errors normally do not interrupt the execution of the affected program, but the affected computation results cannot be trusted any more. A well known technique to correct soft errors in matrix–matrix multiplication is algorithm-based fault tolerance (ABFT). While ABFT achieves much better efficiency than triple modular redundancy (TMR) – a traditional general technique to correct soft eywords: lgorithm-based fault tolerance atrix multiplication ault tolerant linear algebra n-line algorithm based fault tolerance errors, both ABFT and TMR detect errors off-line after the computation is finished. This paper extends the traditional ABFT technique from off-line to on-line so that soft errors in matrix–matrix multiplication can be detected in the middle of the computation during the program execution and higher efficiency can be achieved by correcting the corrupted computations in a timely manner. Experimental results demonstrate that the proposed technique can correct one error every ten seconds with negligible (i.e. less than over 1%) performance penalty