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Algorithm-Based Fault Tolerance For Two-Sided Dense Matrix Factorizations, Yulu Jia
Algorithm-Based Fault Tolerance For Two-Sided Dense Matrix Factorizations, Yulu Jia
Doctoral Dissertations
The mean time between failure (MTBF) of large supercomputers is decreasing, and future exascale computers are expected to have a MTBF of around 30 minutes. Therefore, it is urgent to prepare important algorithms for future machines with such a short MTBF. Eigenvalue problems (EVP) and singular value problems (SVP) are common in engineering and scientific research. Solving EVP and SVP numerically involves two-sided matrix factorizations: the Hessenberg reduction, the tridiagonal reduction, and the bidiagonal reduction. These three factorizations are computation intensive, and have long running times. They are prone to suffer from computer failures.
We designed algorithm-based fault tolerant (ABFT) …